Electronic Health Records and US Public Health: Current Realities and Future Promise

PubMed Central

Parrish, R. Gibson; Ross, David A.

2013-01-01

Electronic health records (EHRs) could contribute to improving population health in the United States. Realizing this potential will require understanding what EHRs can realistically offer to efforts to improve population health, the requirements for obtaining useful information from EHRs, and a plan for addressing these requirements. Potential contributions of EHRs to improving population health include better understanding of the level and distribution of disease, function, and well-being within populations. Requirements are improved population coverage of EHRs, standardized EHR content and reporting methods, and adequate legal authority for using EHRs, particularly for population health. A collaborative national effort to address the most pressing prerequisites for and barriers to the use of EHRs for improving population health is needed to realize the EHR’s potential. PMID:23865646

The EHR-ARCHE project: satisfying clinical information needs in a Shared Electronic Health Record system based on IHE XDS and Archetypes.

PubMed

Duftschmid, Georg; Rinner, Christoph; Kohler, Michael; Huebner-Bloder, Gudrun; Saboor, Samrend; Ammenwerth, Elske

2013-12-01

While contributing to an improved continuity of care, Shared Electronic Health Record (EHR) systems may also lead to information overload of healthcare providers. Document-oriented architectures, such as the commonly employed IHE XDS profile, which only support information retrieval at the level of documents, are particularly susceptible for this problem. The objective of the EHR-ARCHE project was to develop a methodology and a prototype to efficiently satisfy healthcare providers' information needs when accessing a patient's Shared EHR during a treatment situation. We especially aimed to investigate whether this objective can be reached by integrating EHR Archetypes into an IHE XDS environment. Using methodical triangulation, we first analysed the information needs of healthcare providers, focusing on the treatment of diabetes patients as an exemplary application domain. We then designed ISO/EN 13606 Archetypes covering the identified information needs. To support a content-based search for fine-grained information items within EHR documents, we extended the IHE XDS environment with two additional actors. Finally, we conducted a formative and summative evaluation of our approach within a controlled study. We identified 446 frequently needed diabetes-specific information items, representing typical information needs of healthcare providers. We then created 128 Archetypes and 120 EHR documents for two fictive patients. All seven diabetes experts, who evaluated our approach, preferred the content-based search to a conventional XDS search. Success rates of finding relevant information was higher for the content-based search (100% versus 80%) and the latter was also more time-efficient (8-14min versus 20min or more). Our results show that for an efficient satisfaction of health care providers' information needs, a content-based search that rests upon the integration of Archetypes into an IHE XDS-based Shared EHR system is superior to a conventional metadata-based XDS search. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

The EHR-ARCHE project: Satisfying clinical information needs in a Shared Electronic Health Record System based on IHE XDS and Archetypes☆

PubMed Central

Duftschmid, Georg; Rinner, Christoph; Kohler, Michael; Huebner-Bloder, Gudrun; Saboor, Samrend; Ammenwerth, Elske

2013-01-01

Purpose While contributing to an improved continuity of care, Shared Electronic Health Record (EHR) systems may also lead to information overload of healthcare providers. Document-oriented architectures, such as the commonly employed IHE XDS profile, which only support information retrieval at the level of documents, are particularly susceptible for this problem. The objective of the EHR-ARCHE project was to develop a methodology and a prototype to efficiently satisfy healthcare providers’ information needs when accessing a patient's Shared EHR during a treatment situation. We especially aimed to investigate whether this objective can be reached by integrating EHR Archetypes into an IHE XDS environment. Methods Using methodical triangulation, we first analysed the information needs of healthcare providers, focusing on the treatment of diabetes patients as an exemplary application domain. We then designed ISO/EN 13606 Archetypes covering the identified information needs. To support a content-based search for fine-grained information items within EHR documents, we extended the IHE XDS environment with two additional actors. Finally, we conducted a formative and summative evaluation of our approach within a controlled study. Results We identified 446 frequently needed diabetes-specific information items, representing typical information needs of healthcare providers. We then created 128 Archetypes and 120 EHR documents for two fictive patients. All seven diabetes experts, who evaluated our approach, preferred the content-based search to a conventional XDS search. Success rates of finding relevant information was higher for the content-based search (100% versus 80%) and the latter was also more time-efficient (8–14 min versus 20 min or more). Conclusions Our results show that for an efficient satisfaction of health care providers’ information needs, a content-based search that rests upon the integration of Archetypes into an IHE XDS-based Shared EHR system is superior to a conventional metadata-based XDS search. PMID:23999002

Ubiquitous information for ubiquitous computing: expressing clinical data sets with openEHR archetypes.

PubMed

Garde, Sebastian; Hovenga, Evelyn; Buck, Jasmin; Knaup, Petra

2006-01-01

Ubiquitous computing requires ubiquitous access to information and knowledge. With the release of openEHR Version 1.0 there is a common model available to solve some of the problems related to accessing information and knowledge by improving semantic interoperability between clinical systems. Considerable work has been undertaken by various bodies to standardise Clinical Data Sets. Notwithstanding their value, several problems remain unsolved with Clinical Data Sets without the use of a common model underpinning them. This paper outlines these problems like incompatible basic data types and overlapping and incompatible definitions of clinical content. A solution to this based on openEHR archetypes is motivated and an approach to transform existing Clinical Data Sets into archetypes is presented. To avoid significant overlaps and unnecessary effort during archetype development, archetype development needs to be coordinated nationwide and beyond and also across the various health professions in a formalized process.

Domain Modeling and Application Development of an Archetype- and XML-based EHRS. Practical Experiences and Lessons Learnt.

PubMed

Kropf, Stefan; Chalopin, Claire; Lindner, Dirk; Denecke, Kerstin

2017-06-28

Access to patient data within the hospital or between hospitals is still problematic since a variety of information systems is in use applying different vendor specific terminologies and underlying knowledge models. Beyond, the development of electronic health record systems (EHRSs) is time and resource consuming. Thus, there is a substantial need for a development strategy of standardized EHRSs. We are applying a reuse-oriented process model and demonstrate its feasibility and realization on a practical medical use case, which is an EHRS holding all relevant data arising in the context of treatment of tumors of the sella region. In this paper, we describe the development process and our practical experiences. Requirements towards the development of the EHRS were collected by interviews with a neurosurgeon and patient data analysis. For modelling of patient data, we selected openEHR as standard and exploited the software tools provided by the openEHR foundation. The patient information model forms the core of the development process, which comprises the EHR generation and the implementation of an EHRS architecture. Moreover, a reuse-oriented process model from the business domain was adapted to the development of the EHRS. The reuse-oriented process model is a model for a suitable abstraction of both, modeling and development of an EHR centralized EHRS. The information modeling process resulted in 18 archetypes that were aggregated in a template and built the boilerplate of the model driven development. The EHRs and the EHRS were developed by openEHR and W3C standards, tightly supported by well-established XML techniques. The GUI of the final EHRS integrates and visualizes information from various examinations, medical reports, findings and laboratory test results. We conclude that the development of a standardized overarching EHR and an EHRS is feasible using openEHR and W3C standards, enabling a high degree of semantic interoperability. The standardized representation visualizes data and can in this way support the decision process of clinicians.

Definition, structure, content, use and impacts of electronic health records: a review of the research literature.

PubMed

Häyrinen, Kristiina; Saranto, Kaija; Nykänen, Pirkko

2008-05-01

This paper reviews the research literature on electronic health record (EHR) systems. The aim is to find out (1) how electronic health records are defined, (2) how the structure of these records is described, (3) in what contexts EHRs are used, (4) who has access to EHRs, (5) which data components of the EHRs are used and studied, (6) what is the purpose of research in this field, (7) what methods of data collection have been used in the studies reviewed and (8) what are the results of these studies. A systematic review was carried out of the research dealing with the content of EHRs. A literature search was conducted on four electronic databases: Pubmed/Medline, Cinalh, Eval and Cochrane. The concept of EHR comprised a wide range of information systems, from files compiled in single departments to longitudinal collections of patient data. Only very few papers offered descriptions of the structure of EHRs or the terminologies used. EHRs were used in primary, secondary and tertiary care. Data were recorded in EHRs by different groups of health care professionals. Secretarial staff also recorded data from dictation or nurses' or physicians' manual notes. Some information was also recorded by patients themselves; this information is validated by physicians. It is important that the needs and requirements of different users are taken into account in the future development of information systems. Several data components were documented in EHRs: daily charting, medication administration, physical assessment, admission nursing note, nursing care plan, referral, present complaint (e.g. symptoms), past medical history, life style, physical examination, diagnoses, tests, procedures, treatment, medication, discharge, history, diaries, problems, findings and immunization. In the future it will be necessary to incorporate different kinds of standardized instruments, electronic interviews and nursing documentation systems in EHR systems. The aspects of information quality most often explored in the studies reviewed were the completeness and accuracy of different data components. It has been shown in several studies that the use of an information system was conducive to more complete and accurate documentation by health care professionals. The quality of information is particularly important in patient care, but EHRs also provide important information for secondary purposes, such as health policy planning. Studies focusing on the content of EHRs are needed, especially studies of nursing documentation or patient self-documentation. One future research area is to compare the documentation of different health care professionals with the core information about EHRs which has been determined in national health projects. The challenge for ongoing national health record projects around the world is to take into account all the different types of EHRs and the needs and requirements of different health care professionals and consumers in the development of EHRs. A further challenge is the use of international terminologies in order to achieve semantic interoperability.

Protection of electronic health records (EHRs) in cloud.

PubMed

Alabdulatif, Abdulatif; Khalil, Ibrahim; Mai, Vu

2013-01-01

EHR technology has come into widespread use and has attracted attention in healthcare institutions as well as in research. Cloud services are used to build efficient EHR systems and obtain the greatest benefits of EHR implementation. Many issues relating to building an ideal EHR system in the cloud, especially the tradeoff between flexibility and security, have recently surfaced. The privacy of patient records in cloud platforms is still a point of contention. In this research, we are going to improve the management of access control by restricting participants' access through the use of distinct encrypted parameters for each participant in the cloud-based database. Also, we implement and improve an existing secure index search algorithm to enhance the efficiency of information control and flow through a cloud-based EHR system. At the final stage, we contribute to the design of reliable, flexible and secure access control, enabling quick access to EHR information.

Archetype Model-Driven Development Framework for EHR Web System.

PubMed

Kobayashi, Shinji; Kimura, Eizen; Ishihara, Ken

2013-12-01

This article describes the Web application framework for Electronic Health Records (EHRs) we have developed to reduce construction costs for EHR sytems. The openEHR project has developed clinical model driven architecture for future-proof interoperable EHR systems. This project provides the specifications to standardize clinical domain model implementations, upon which the ISO/CEN 13606 standards are based. The reference implementation has been formally described in Eiffel. Moreover C# and Java implementations have been developed as reference. While scripting languages had been more popular because of their higher efficiency and faster development in recent years, they had not been involved in the openEHR implementations. From 2007, we have used the Ruby language and Ruby on Rails (RoR) as an agile development platform to implement EHR systems, which is in conformity with the openEHR specifications. We implemented almost all of the specifications, the Archetype Definition Language parser, and RoR scaffold generator from archetype. Although some problems have emerged, most of them have been resolved. We have provided an agile EHR Web framework, which can build up Web systems from archetype models using RoR. The feasibility of the archetype model to provide semantic interoperability of EHRs has been demonstrated and we have verified that that it is suitable for the construction of EHR systems.

Clinical Summarization Capabilities of Commercially-available and Internally-developed Electronic Health Records

PubMed Central

Laxmisan, A.; McCoy, A.B.; Wright, A.; Sittig, D.F.

2012-01-01

Objective Clinical summarization, the process by which relevant patient information is electronically summarized and presented at the point of care, is of increasing importance given the increasing volume of clinical data in electronic health record systems (EHRs). There is a paucity of research on electronic clinical summarization, including the capabilities of currently available EHR systems. Methods We compared different aspects of general clinical summary screens used in twelve different EHR systems using a previously described conceptual model: AORTIS (Aggregation, Organization, Reduction, Interpretation and Synthesis). Results We found a wide variation in the EHRs’ summarization capabilities: all systems were capable of simple aggregation and organization of limited clinical content, but only one demonstrated an ability to synthesize information from the data. Conclusion Improvement of the clinical summary screen functionality for currently available EHRs is necessary. Further research should identify strategies and methods for creating easy to use, well-designed clinical summary screens that aggregate, organize and reduce all pertinent patient information as well as provide clinical interpretations and synthesis as required. PMID:22468161

A Picture is Worth 1,000 Words. The Use of Clinical Images in Electronic Medical Records.

PubMed

Ai, Angela C; Maloney, Francine L; Hickman, Thu-Trang; Wilcox, Allison R; Ramelson, Harley; Wright, Adam

2017-07-12

To understand how clinicians utilize image uploading tools in a home grown electronic health records (EHR) system. A content analysis of patient notes containing non-radiological images from the EHR was conducted. Images from 4,000 random notes from July 1, 2009 - June 30, 2010 were reviewed and manually coded. Codes were assigned to four properties of the image: (1) image type, (2) role of image uploader (e.g. MD, NP, PA, RN), (3) practice type (e.g. internal medicine, dermatology, ophthalmology), and (4) image subject. 3,815 images from image-containing notes stored in the EHR were reviewed and manually coded. Of those images, 32.8% were clinical and 66.2% were non-clinical. The most common types of the clinical images were photographs (38.0%), diagrams (19.1%), and scanned documents (14.4%). MDs uploaded 67.9% of clinical images, followed by RNs with 10.2%, and genetic counselors with 6.8%. Dermatology (34.9%), ophthalmology (16.1%), and general surgery (10.8%) uploaded the most clinical images. The content of clinical images referencing body parts varied, with 49.8% of those images focusing on the head and neck region, 15.3% focusing on the thorax, and 13.8% focusing on the lower extremities. The diversity of image types, content, and uploaders within a home grown EHR system reflected the versatility and importance of the image uploading tool. Understanding how users utilize image uploading tools in a clinical setting highlights important considerations for designing better EHR tools and the importance of interoperability between EHR systems and other health technology.

Archetype Model-Driven Development Framework for EHR Web System

PubMed Central

Kimura, Eizen; Ishihara, Ken

2013-01-01

Objectives This article describes the Web application framework for Electronic Health Records (EHRs) we have developed to reduce construction costs for EHR sytems. Methods The openEHR project has developed clinical model driven architecture for future-proof interoperable EHR systems. This project provides the specifications to standardize clinical domain model implementations, upon which the ISO/CEN 13606 standards are based. The reference implementation has been formally described in Eiffel. Moreover C# and Java implementations have been developed as reference. While scripting languages had been more popular because of their higher efficiency and faster development in recent years, they had not been involved in the openEHR implementations. From 2007, we have used the Ruby language and Ruby on Rails (RoR) as an agile development platform to implement EHR systems, which is in conformity with the openEHR specifications. Results We implemented almost all of the specifications, the Archetype Definition Language parser, and RoR scaffold generator from archetype. Although some problems have emerged, most of them have been resolved. Conclusions We have provided an agile EHR Web framework, which can build up Web systems from archetype models using RoR. The feasibility of the archetype model to provide semantic interoperability of EHRs has been demonstrated and we have verified that that it is suitable for the construction of EHR systems. PMID:24523991

Challenges to EHR implementation in electronic- versus paper-based office practices.

PubMed

Zandieh, Stephanie O; Yoon-Flannery, Kahyun; Kuperman, Gilad J; Langsam, Daniel J; Hyman, Daniel; Kaushal, Rainu

2008-06-01

Challenges in implementing electronic health records (EHRs) have received some attention, but less is known about the process of transitioning from legacy EHRs to newer systems. To determine how ambulatory leaders differentiate implementation approaches between practices that are currently paper-based and those with a legacy EHR system (EHR-based). Qualitative study. Eleven practice managers and 12 medical directors all part of an academic ambulatory care network of a large teaching hospital in New York City in January to May of 2006. Qualitative approach comparing and contrasting perceived benefits and challenges in implementing an ambulatory EHR between practice leaders from paper- and EHR-based practices. Content analysis was performed using grounded theory and ATLAS.ti 5.0. We found that paper-based leaders prioritized the following: sufficient workstations and printers, a physician information technology (IT) champion at the practice, workflow education to ensure a successful transition to a paperless medical practice, and a high existing comfort level of practitioners and support staff with IT. In contrast, EHR-based leaders prioritized: improved technical training and ongoing technical support, sufficient protection of patient privacy, and open recognition of physician resistance, especially for those who were loyal to a legacy EHR. Unlike paper-based practices, EHR-based leadership believed that comfort level with IT and adjustments to workflow changes would not be difficult challenges to overcome. Leadership at paper- and EHR-based practices in 1 academic network has different priorities for implementing a new EHR. Ambulatory practices upgrading their legacy EHR have unique challenges.

ORBDA: An openEHR benchmark dataset for performance assessment of electronic health record servers.

PubMed

Teodoro, Douglas; Sundvall, Erik; João Junior, Mario; Ruch, Patrick; Miranda Freire, Sergio

2018-01-01

The openEHR specifications are designed to support implementation of flexible and interoperable Electronic Health Record (EHR) systems. Despite the increasing number of solutions based on the openEHR specifications, it is difficult to find publicly available healthcare datasets in the openEHR format that can be used to test, compare and validate different data persistence mechanisms for openEHR. To foster research on openEHR servers, we present the openEHR Benchmark Dataset, ORBDA, a very large healthcare benchmark dataset encoded using the openEHR formalism. To construct ORBDA, we extracted and cleaned a de-identified dataset from the Brazilian National Healthcare System (SUS) containing hospitalisation and high complexity procedures information and formalised it using a set of openEHR archetypes and templates. Then, we implemented a tool to enrich the raw relational data and convert it into the openEHR model using the openEHR Java reference model library. The ORBDA dataset is available in composition, versioned composition and EHR openEHR representations in XML and JSON formats. In total, the dataset contains more than 150 million composition records. We describe the dataset and provide means to access it. Additionally, we demonstrate the usage of ORBDA for evaluating inserting throughput and query latency performances of some NoSQL database management systems. We believe that ORBDA is a valuable asset for assessing storage models for openEHR-based information systems during the software engineering process. It may also be a suitable component in future standardised benchmarking of available openEHR storage platforms.

ORBDA: An openEHR benchmark dataset for performance assessment of electronic health record servers

PubMed Central

Sundvall, Erik; João Junior, Mario; Ruch, Patrick; Miranda Freire, Sergio

2018-01-01

The openEHR specifications are designed to support implementation of flexible and interoperable Electronic Health Record (EHR) systems. Despite the increasing number of solutions based on the openEHR specifications, it is difficult to find publicly available healthcare datasets in the openEHR format that can be used to test, compare and validate different data persistence mechanisms for openEHR. To foster research on openEHR servers, we present the openEHR Benchmark Dataset, ORBDA, a very large healthcare benchmark dataset encoded using the openEHR formalism. To construct ORBDA, we extracted and cleaned a de-identified dataset from the Brazilian National Healthcare System (SUS) containing hospitalisation and high complexity procedures information and formalised it using a set of openEHR archetypes and templates. Then, we implemented a tool to enrich the raw relational data and convert it into the openEHR model using the openEHR Java reference model library. The ORBDA dataset is available in composition, versioned composition and EHR openEHR representations in XML and JSON formats. In total, the dataset contains more than 150 million composition records. We describe the dataset and provide means to access it. Additionally, we demonstrate the usage of ORBDA for evaluating inserting throughput and query latency performances of some NoSQL database management systems. We believe that ORBDA is a valuable asset for assessing storage models for openEHR-based information systems during the software engineering process. It may also be a suitable component in future standardised benchmarking of available openEHR storage platforms. PMID:29293556

Safety Assurance Factors for Electronic Health Record Resilience (SAFER): study protocol

PubMed Central

2013-01-01

Background Implementation and use of electronic health records (EHRs) could lead to potential improvements in quality of care. However, the use of EHRs also introduces unique and often unexpected patient safety risks. Proactive assessment of risks and vulnerabilities can help address potential EHR-related safety hazards before harm occurs; however, current risk assessment methods are underdeveloped. The overall objective of this project is to develop and validate proactive assessment tools to ensure that EHR-enabled clinical work systems are safe and effective. Methods/Design This work is conceptually grounded in an 8-dimension model of safe and effective health information technology use. Our first aim is to develop self-assessment guides that can be used by health care institutions to evaluate certain high-risk components of their EHR-enabled clinical work systems. We will solicit input from subject matter experts and relevant stakeholders to develop guides focused on 9 specific risk areas and will subsequently pilot test the guides with individuals representative of likely users. The second aim will be to examine the utility of the self-assessment guides by beta testing the guides at selected facilities and conducting on-site evaluations. Our multidisciplinary team will use a variety of methods to assess the content validity and perceived usefulness of the guides, including interviews, naturalistic observations, and document analysis. The anticipated output of this work will be a series of self-administered EHR safety assessment guides with clear, actionable, checklist-type items. Discussion Proactive assessment of patient safety risks increases the resiliency of health care organizations to unanticipated hazards of EHR use. The resulting products and lessons learned from the development of the assessment guides are expected to be helpful to organizations that are beginning the EHR selection and implementation process as well as those that have already implemented EHRs. Findings from our project, currently underway, will inform future efforts to validate and implement tools that can be used by health care organizations to improve the safety of EHR-enabled clinical work systems. PMID:23587208

Expressing clinical data sets with openEHR archetypes: a solid basis for ubiquitous computing.

PubMed

Garde, Sebastian; Hovenga, Evelyn; Buck, Jasmin; Knaup, Petra

2007-12-01

The purpose of this paper is to analyse the feasibility and usefulness of expressing clinical data sets (CDSs) as openEHR archetypes. For this, we present an approach to transform CDS into archetypes, and outline typical problems with CDS and analyse whether some of these problems can be overcome by the use of archetypes. Literature review and analysis of a selection of existing Australian, German, other European and international CDSs; transfer of a CDS for Paediatric Oncology into openEHR archetypes; implementation of CDSs in application systems. To explore the feasibility of expressing CDS as archetypes an approach to transform existing CDSs into archetypes is presented in this paper. In case of the Paediatric Oncology CDS (which consists of 260 data items) this lead to the definition of 48 openEHR archetypes. To analyse the usefulness of expressing CDS as archetypes, we identified nine problems with CDS that currently remain unsolved without a common model underpinning the CDS. Typical problems include incompatible basic data types and overlapping and incompatible definitions of clinical content. A solution to most of these problems based on openEHR archetypes is motivated. With regard to integrity constraints, further research is required. While openEHR cannot overcome all barriers to Ubiquitous Computing, it can provide the common basis for ubiquitous presence of meaningful and computer-processable knowledge and information, which we believe is a basic requirement for Ubiquitous Computing. Expressing CDSs as openEHR archetypes is feasible and advantageous as it fosters semantic interoperability, supports ubiquitous computing, and helps to develop archetypes that are arguably of better quality than the original CDS.

Structuring clinical workflows for diabetes care: an overview of the OntoHealth approach.

PubMed

Schweitzer, M; Lasierra, N; Oberbichler, S; Toma, I; Fensel, A; Hoerbst, A

2014-01-01

Electronic health records (EHRs) play an important role in the treatment of chronic diseases such as diabetes mellitus. Although the interoperability and selected functionality of EHRs are already addressed by a number of standards and best practices, such as IHE or HL7, the majority of these systems are still monolithic from a user-functionality perspective. The purpose of the OntoHealth project is to foster a functionally flexible, standards-based use of EHRs to support clinical routine task execution by means of workflow patterns and to shift the present EHR usage to a more comprehensive integration concerning complete clinical workflows. The goal of this paper is, first, to introduce the basic architecture of the proposed OntoHealth project and, second, to present selected functional needs and a functional categorization regarding workflow-based interactions with EHRs in the domain of diabetes. A systematic literature review regarding attributes of workflows in the domain of diabetes was conducted. Eligible references were gathered and analyzed using a qualitative content analysis. Subsequently, a functional workflow categorization was derived from diabetes-specific raw data together with existing general workflow patterns. This paper presents the design of the architecture as well as a categorization model which makes it possible to describe the components or building blocks within clinical workflows. The results of our study lead us to identify basic building blocks, named as actions, decisions, and data elements, which allow the composition of clinical workflows within five identified contexts. The categorization model allows for a description of the components or building blocks of clinical workflows from a functional view.

Structuring Clinical Workflows for Diabetes Care

PubMed Central

Lasierra, N.; Oberbichler, S.; Toma, I.; Fensel, A.; Hoerbst, A.

2014-01-01

Summary Background Electronic health records (EHRs) play an important role in the treatment of chronic diseases such as diabetes mellitus. Although the interoperability and selected functionality of EHRs are already addressed by a number of standards and best practices, such as IHE or HL7, the majority of these systems are still monolithic from a user-functionality perspective. The purpose of the OntoHealth project is to foster a functionally flexible, standards-based use of EHRs to support clinical routine task execution by means of workflow patterns and to shift the present EHR usage to a more comprehensive integration concerning complete clinical workflows. Objectives The goal of this paper is, first, to introduce the basic architecture of the proposed OntoHealth project and, second, to present selected functional needs and a functional categorization regarding workflow-based interactions with EHRs in the domain of diabetes. Methods A systematic literature review regarding attributes of workflows in the domain of diabetes was conducted. Eligible references were gathered and analyzed using a qualitative content analysis. Subsequently, a functional workflow categorization was derived from diabetes-specific raw data together with existing general workflow patterns. Results This paper presents the design of the architecture as well as a categorization model which makes it possible to describe the components or building blocks within clinical workflows. The results of our study lead us to identify basic building blocks, named as actions, decisions, and data elements, which allow the composition of clinical workflows within five identified contexts. Conclusions The categorization model allows for a description of the components or building blocks of clinical workflows from a functional view. PMID:25024765

Reducing Misses and Near Misses Related to Multitasking on the Electronic Health Record: Observational Study and Qualitative Analysis

PubMed Central

Matta, George Y; Bohsali, Fuad B; Chisolm, Margaret S

2018-01-01

Background Clinicians’ use of electronic health record (EHR) systems while multitasking may increase the risk of making errors, but silent EHR system use may lower patient satisfaction. Delaying EHR system use until after patient visits may increase clinicians’ EHR workload, stress, and burnout. Objective We aimed to describe the perspectives of clinicians, educators, administrators, and researchers about misses and near misses that they felt were related to clinician multitasking while using EHR systems. Methods This observational study was a thematic analysis of perspectives elicited from 63 continuing medical education (CME) participants during 2 workshops and 1 interactive lecture about challenges and strategies for relationship-centered communication during clinician EHR system use. The workshop elicited reflection about memorable times when multitasking EHR use was associated with “misses” (errors that were not caught at the time) or “near misses” (mistakes that were caught before leading to errors). We conducted qualitative analysis using an editing analysis style to identify codes and then select representative themes and quotes. Results All workshop participants shared stories of misses or near misses in EHR system ordering and documentation or patient-clinician communication, wondering about “misses we don’t even know about.” Risk factors included the computer’s position, EHR system usability, note content and style, information overload, problematic workflows, systems issues, and provider and patient communication behaviors and expectations. Strategies to reduce multitasking EHR system misses included clinician transparency when needing silent EHR system use (eg, for prescribing), narrating EHR system use, patient activation during EHR system use, adapting visit organization and workflow, improving EHR system design, and improving team support and systems. Conclusions CME participants shared numerous stories of errors and near misses in EHR tasks and communication that they felt related to EHR multitasking. However, they brainstormed diverse strategies for using EHR systems safely while preserving patient relationships. PMID:29410388

Reducing Misses and Near Misses Related to Multitasking on the Electronic Health Record: Observational Study and Qualitative Analysis.

PubMed

Ratanawongsa, Neda; Matta, George Y; Bohsali, Fuad B; Chisolm, Margaret S

2018-02-06

Clinicians' use of electronic health record (EHR) systems while multitasking may increase the risk of making errors, but silent EHR system use may lower patient satisfaction. Delaying EHR system use until after patient visits may increase clinicians' EHR workload, stress, and burnout. We aimed to describe the perspectives of clinicians, educators, administrators, and researchers about misses and near misses that they felt were related to clinician multitasking while using EHR systems. This observational study was a thematic analysis of perspectives elicited from 63 continuing medical education (CME) participants during 2 workshops and 1 interactive lecture about challenges and strategies for relationship-centered communication during clinician EHR system use. The workshop elicited reflection about memorable times when multitasking EHR use was associated with "misses" (errors that were not caught at the time) or "near misses" (mistakes that were caught before leading to errors). We conducted qualitative analysis using an editing analysis style to identify codes and then select representative themes and quotes. All workshop participants shared stories of misses or near misses in EHR system ordering and documentation or patient-clinician communication, wondering about "misses we don't even know about." Risk factors included the computer's position, EHR system usability, note content and style, information overload, problematic workflows, systems issues, and provider and patient communication behaviors and expectations. Strategies to reduce multitasking EHR system misses included clinician transparency when needing silent EHR system use (eg, for prescribing), narrating EHR system use, patient activation during EHR system use, adapting visit organization and workflow, improving EHR system design, and improving team support and systems. CME participants shared numerous stories of errors and near misses in EHR tasks and communication that they felt related to EHR multitasking. However, they brainstormed diverse strategies for using EHR systems safely while preserving patient relationships. ©Neda Ratanawongsa, George Y Matta, Fuad B Bohsali, Margaret S Chisolm. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 06.02.2018.

Advance Care Planning Documentation in Electronic Health Records: Current Challenges and Recommendations for Change.

PubMed

Lamas, Daniela; Panariello, Natalie; Henrich, Natalie; Hammes, Bernard; Hanson, Laura C; Meier, Diane E; Guinn, Nancy; Corrigan, Janet; Hubber, Sean; Luetke-Stahlman, Hannah; Block, Susan

2018-04-01

To develop a set of clinically relevant recommendations to improve the state of advance care planning (ACP) documentation in the electronic health record (EHR). Advance care planning (ACP) is a key process that supports goal-concordant care. For preferences to be honored, clinicians must be able to reliably record, find, and use ACP documentation. However, there are no standards to guide ACP documentation in the electronic health record (EHR). We interviewed 21 key informants to understand the strengths and weaknesses of EHR documentation systems for ACP and identify best practices. We analyzed these interviews using a qualitative content analysis approach and subsequently developed a preliminary set of recommendations. These recommendations were vetted and refined in a second round of input from a national panel of content experts. Informants identified six themes regarding current inadequacies in documentation and accessibility of ACP information and opportunities for improvement. We offer a set of concise, clinically relevant recommendations, informed by expert opinion, to improve the state of ACP documentation in the EHR.

Towards semantic interoperability for electronic health records.

PubMed

Garde, Sebastian; Knaup, Petra; Hovenga, Evelyn; Heard, Sam

2007-01-01

In the field of open electronic health records (EHRs), openEHR as an archetype-based approach is being increasingly recognised. It is the objective of this paper to shortly describe this approach, and to analyse how openEHR archetypes impact on health professionals and semantic interoperability. Analysis of current approaches to EHR systems, terminology and standards developments. In addition to literature reviews, we organised face-to-face and additional telephone interviews and tele-conferences with members of relevant organisations and committees. The openEHR archetypes approach enables syntactic interoperability and semantic interpretability -- both important prerequisites for semantic interoperability. Archetypes enable the formal definition of clinical content by clinicians. To enable comprehensive semantic interoperability, the development and maintenance of archetypes needs to be coordinated internationally and across health professions. Domain knowledge governance comprises a set of processes that enable the creation, development, organisation, sharing, dissemination, use and continuous maintenance of archetypes. It needs to be supported by information technology. To enable EHRs, semantic interoperability is essential. The openEHR archetypes approach enables syntactic interoperability and semantic interpretability. However, without coordinated archetype development and maintenance, 'rank growth' of archetypes would jeopardize semantic interoperability. We therefore believe that openEHR archetypes and domain knowledge governance together create the knowledge environment required to adopt EHRs.

Increasing EHR system usability through standards: Conformance criteria in the HL7 EHR-system functional model.

PubMed

Meehan, Rebecca A; Mon, Donald T; Kelly, Kandace M; Rocca, Mitra; Dickinson, Gary; Ritter, John; Johnson, Constance M

2016-10-01

Though substantial work has been done on the usability of health information technology, improvements in electronic health record system (EHR) usability have been slow, creating frustration, distrust of EHRs and the use of potentially unsafe work-arounds. Usability standards could be part of the solution for improving EHR usability. EHR system functional requirements and standards have been used successfully in the past to specify system behavior, the criteria of which have been gradually implemented in EHR systems through certification programs and other national health IT strategies. Similarly, functional requirements and standards for usability can help address the multitude of sequelae associated with poor usability. This paper describes the evidence-based functional requirements for usability contained in the Health Level Seven (HL7) EHR System Functional Model, and the benefits of open and voluntary EHR system usability standards. Copyright © 2016 Elsevier Inc. All rights reserved.

Safety huddles to proactively identify and address electronic health record safety

PubMed Central

Menon, Shailaja; Singh, Hardeep; Giardina, Traber D; Rayburn, William L; Davis, Brenda P; Russo, Elise M

2017-01-01

Objective: Methods to identify and study safety risks of electronic health records (EHRs) are underdeveloped and largely depend on limited end-user reports. “Safety huddles” have been found useful in creating a sense of collective situational awareness that increases an organization’s capacity to respond to safety concerns. We explored the use of safety huddles for identifying and learning about EHR-related safety concerns. Design: Data were obtained from daily safety huddle briefing notes recorded at a single midsized tertiary-care hospital in the United States over 1 year. Huddles were attended by key administrative, clinical, and information technology staff. We conducted a content analysis of huddle notes to identify what EHR-related safety concerns were discussed. We expanded a previously developed EHR-related error taxonomy to categorize types of EHR-related safety concerns recorded in the notes. Results: On review of daily huddle notes spanning 249 days, we identified 245 EHR-related safety concerns. For our analysis, we defined EHR technology to include a specific EHR functionality, an entire clinical software application, or the hardware system. Most concerns (41.6%) involved “EHR technology working incorrectly,” followed by 25.7% involving “EHR technology not working at all.” Concerns related to “EHR technology missing or absent” accounted for 16.7%, whereas 15.9% were linked to “user errors.” Conclusions: Safety huddles promoted discussion of several technology-related issues at the organization level and can serve as a promising technique to identify and address EHR-related safety concerns. Based on our findings, we recommend that health care organizations consider huddles as a strategy to promote understanding and improvement of EHR safety. PMID:28031286

Usability Testing of Two Ambulatory EHR Navigators.

PubMed

Hultman, Gretchen; Marquard, Jenna; Arsoniadis, Elliot; Mink, Pamela; Rizvi, Rubina; Ramer, Tim; Khairat, Saif; Fickau, Keri; Melton, Genevieve B

2016-01-01

Despite widespread electronic health record (EHR) adoption, poor EHR system usability continues to be a significant barrier to effective system use for end users. One key to addressing usability problems is to employ user testing and user-centered design. To understand if redesigning an EHR-based navigation tool with clinician input improved user performance and satisfaction. A usability evaluation was conducted to compare two versions of a redesigned ambulatory navigator. Participants completed tasks for five patient cases using the navigators, while employing a think-aloud protocol. The tasks were based on Meaningful Use (MU) requirements. The version of navigator did not affect perceived workload, and time to complete tasks was longer in the redesigned navigator. A relatively small portion of navigator content was used to complete the MU-related tasks, though navigation patterns were highly variable across participants for both navigators. Preferences for EHR navigation structures appeared to be individualized. This study demonstrates the importance of EHR usability assessments to evaluate group and individual performance of different interfaces and preferences for each design.

The openEHR Java reference implementation project.

PubMed

Chen, Rong; Klein, Gunnar

2007-01-01

The openEHR foundation has developed an innovative design for interoperable and future-proof Electronic Health Record (EHR) systems based on a dual model approach with a stable reference information model complemented by archetypes for specific clinical purposes.A team from Sweden has implemented all the stable specifications in the Java programming language and donated the source code to the openEHR foundation. It was adopted as the openEHR Java Reference Implementation in March 2005 and released under open source licenses. This encourages early EHR implementation projects around the world and a number of groups have already started to use this code. The early Java implementation experience has also led to the publication of the openEHR Java Implementation Technology Specification. A number of design changes to the specifications and important minor corrections have been directly initiated by the implementation project over the last two years. The Java Implementation has been important for the validation and improvement of the openEHR design specifications and provides building blocks for future EHR systems.

A Natural Language Processing System That Links Medical Terms in Electronic Health Record Notes to Lay Definitions: System Development Using Physician Reviews

PubMed Central

Druhl, Emily; Polepalli Ramesh, Balaji; Houston, Thomas K; Brandt, Cynthia A; Zulman, Donna M; Vimalananda, Varsha G; Malkani, Samir; Yu, Hong

2018-01-01

Background Many health care systems now allow patients to access their electronic health record (EHR) notes online through patient portals. Medical jargon in EHR notes can confuse patients, which may interfere with potential benefits of patient access to EHR notes. Objective The aim of this study was to develop and evaluate the usability and content quality of NoteAid, a Web-based natural language processing system that links medical terms in EHR notes to lay definitions, that is, definitions easily understood by lay people. Methods NoteAid incorporates two core components: CoDeMed, a lexical resource of lay definitions for medical terms, and MedLink, a computational unit that links medical terms to lay definitions. We developed innovative computational methods, including an adapted distant supervision algorithm to prioritize medical terms important for EHR comprehension to facilitate the effort of building CoDeMed. Ten physician domain experts evaluated the user interface and content quality of NoteAid. The evaluation protocol included a cognitive walkthrough session and a postsession questionnaire. Physician feedback sessions were audio-recorded. We used standard content analysis methods to analyze qualitative data from these sessions. Results Physician feedback was mixed. Positive feedback on NoteAid included (1) Easy to use, (2) Good visual display, (3) Satisfactory system speed, and (4) Adequate lay definitions. Opportunities for improvement arising from evaluation sessions and feedback included (1) improving the display of definitions for partially matched terms, (2) including more medical terms in CoDeMed, (3) improving the handling of terms whose definitions vary depending on different contexts, and (4) standardizing the scope of definitions for medicines. On the basis of these results, we have improved NoteAid’s user interface and a number of definitions, and added 4502 more definitions in CoDeMed. Conclusions Physician evaluation yielded useful feedback for content validation and refinement of this innovative tool that has the potential to improve patient EHR comprehension and experience using patient portals. Future ongoing work will develop algorithms to handle ambiguous medical terms and test and evaluate NoteAid with patients. PMID:29358159

Content analysis of physical examination templates in electronic health records using SNOMED CT.

PubMed

Gøeg, Kirstine Rosenbeck; Chen, Rong; Højen, Anne Randorff; Elberg, Pia

2014-10-01

Most electronic health record (EHR) systems are built on proprietary information models and terminology, which makes achieving semantic interoperability a challenge. Solving interoperability problems requires well-defined standards. In contrast, the need to support clinical work practice requires a local customization of EHR systems. Consequently, contrasting goals may be evident in EHR template design because customization means that local EHR organizations can define their own templates, whereas standardization implies consensus at some level. To explore the complexity of balancing these two goals, this study analyzes the differences and similarities between templates in use today. A similarity analysis was developed on the basis of SNOMED CT. The analysis was performed on four physical examination templates from Denmark and Sweden. The semantic relationships in SNOMED CT were used to quantify similarities and differences. Moreover, the analysis used these identified similarities to investigate the common content of a physical examination template. The analysis showed that there were both similarities and differences in physical examination templates, and the size of the templates varied from 18 to 49 fields. In the SNOMED CT analysis, exact matches and terminology similarities were represented in all template pairs. The number of exact matches ranged from 7 to 24. Moreover, the number of unrelated fields differed a lot from 1/18 to 22/35. Cross-country comparisons tended to have more unrelated content than within-country comparisons. On the basis of identified similarities, it was possible to define the common content of a physical examination. Nevertheless, a complete view on the physical examination required the inclusion of both exact matches and terminology similarities. This study revealed that a core set of items representing the physical examination templates can be generated when the analysis takes into account not only exact matches but also terminology similarities. This core set of items could be a starting point for standardization and semantic interoperability. However, both unmatched terms and terminology matched terms pose a challenge for standardization. Future work will include using local templates as a point of departure in standardization to see if local requirements can be maintained in a standardized framework. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A comparison of physician pre-adoption and adoption views on electronic health records in Canadian medical practices.

PubMed

Archer, Norm; Cocosila, Mihail

2011-08-12

There is a major campaign involving large expenditures of public money to increase the adoption rate of electronic health record (EHR) systems in Canada. To maximize the chances of success in this effort, physician views on EHRs must be addressed, since user perceptions are key to successful implementation of technology innovations. We propose a theoretical model comprising behavioral factors either favoring or against EHR adoption and use in Canadian medical practices, from the physicians' point of view. EHR perceptions of physicians already using EHR systems are compared with those not using one, through the lens of this model. We conducted an online cross-sectional survey in both English and French among medical practitioners across Canada. Data were collected both from physicians using EHRs and those not using EHRs, and analyzed with structural equation modeling (SEM) techniques. We collected 119 responses from EHR users and 100 from nonusers, resulting in 2 valid samples of 102 and 83 participants, respectively. The theoretical adoption model explained 55.8% of the variance in behavioral intention to continue using EHRs for physicians already using them, and 66.8% of the variance in nonuser intention to adopt such systems. Perception of ease of use was found to be the strongest motivator for EHR users (total effect .525), while perceptions of usefulness and of ease of use were the key determinants for nonusers (total effect .538 and .519, respectively) to adopt the system. Users see perceived overall risk associated with EHR adoption as a major obstacle (total effect -.371), while nonusers perceive risk only as a weak indirect demotivator. Of the 13 paths of the SEM model, 5 showed significant differences between the 2 samples (at the .05 level): general doubts about using the system (P = .02), the necessity for the system to be relevant for their job (P < .001), and the necessity for the system to be useful (P = .049) are more important for EHR nonusers than for users, while perceptions of overall obstacles to adoption (P = .03) and system ease of use (P = .042) count more for EHR users than for nonusers. Relatively few differences in perceptions about EHR system adoption and use exist between physicians already using such systems and those not yet using the systems. To maximize the chances of success for new EHR implementations from a behavioral point of view, general doubts about the rationale for such systems must be mitigated through improving design, stressing how EHRs are relevant to physician jobs, and providing substantiating evidence that EHRs are easier to use and more effective than nonusers might expect.

Process-aware EHR BPM systems: two prototypes and a conceptual framework.

PubMed

Webster, Charles; Copenhaver, Mark

2010-01-01

Systematic methods to improve the effectiveness and efficiency of electronic health record-mediated processes will be key to EHRs playing an important role in the positive transformation of healthcare. Business process management (BPM) systematically optimizes process effectiveness, efficiency, and flexibility. Therefore BPM offers relevant ideas and technologies. We provide a conceptual model based on EHR productivity and negative feedback control that links EHR and BPM domains, describe two EHR BPM prototype modules, and close with the argument that typical EHRs must become more process-aware if they are to take full advantage of BPM ideas and technology. A prediction: Future extensible clinical groupware will coordinate delivery of EHR functionality to teams of users by combining modular components with executable process models whose usability (effectiveness, efficiency, and user satisfaction) will be systematically improved using business process management techniques.

Resistance is futile: but it is slowing the pace of EHR adoption nonetheless.

PubMed

Ford, Eric W; Menachemi, Nir; Peterson, Lori T; Huerta, Timothy R

2009-01-01

The purpose of this study is to reassess the projected rate of Electronic Health Record (EHR) diffusion and examine how the federal government's efforts to promote the use of EHR technology have influenced physicians' willingness to adopt such systems. The study recreates and extends the analyses conducted by Ford et al. (1) The two periods examined come before and after the U.S. Federal Government's concerted activity to promote EHR adoption. Meta-analysis and bass modeling are used to compare EHR diffusion rates for two distinct periods of government activity. Very low levels of government activity to promote EHR diffusion marked the first period, before 2004. In 2004, the President of the United States called for a "Universal EHR Adoption" by 2014 (10 yrs), creating the major wave of activity and increased awareness of how EHRs will impact physicians' practices. EHR adoption parameters--external and internal coefficients of influence--are estimated using bass diffusion models and future adoption rates are projected. Comparing the EHR adoption rates before and after 2004 (2001-2004 and 2001-2007 respectively) indicate the physicians' resistance to adoption has increased during the second period. Based on current levels of adoption, less than half the physicians working in small practices will have implemented an EHR by 2014 (47.3%). The external forces driving EHR diffusion have grown in importance since 2004 relative to physicians' internal motivation to adopt such systems. Several national forces are likely contributing to the slowing pace of EHR diffusion.

Integration of DICOM and openEHR standards

NASA Astrophysics Data System (ADS)

Wang, Ying; Yao, Zhihong; Liu, Lei

2011-03-01

The standard format for medical imaging storage and transmission is DICOM. openEHR is an open standard specification in health informatics that describes the management and storage, retrieval and exchange of health data in electronic health records. Considering that the integration of DICOM and openEHR is beneficial to information sharing, on the basis of XML-based DICOM format, we developed a method of creating a DICOM Imaging Archetype in openEHR to enable the integration of DICOM and openEHR. Each DICOM file contains abundant imaging information. However, because reading a DICOM involves looking up the DICOM Data Dictionary, the readability of a DICOM file has been limited. openEHR has innovatively adopted two level modeling method, making clinical information divided into lower level, the information model, and upper level, archetypes and templates. But one critical challenge posed to the development of openEHR is the information sharing problem, especially in imaging information sharing. For example, some important imaging information cannot be displayed in an openEHR file. In this paper, to enhance the readability of a DICOM file and semantic interoperability of an openEHR file, we developed a method of mapping a DICOM file to an openEHR file by adopting the form of archetype defined in openEHR. Because an archetype has a tree structure, after mapping a DICOM file to an openEHR file, the converted information is structuralized in conformance with openEHR format. This method enables the integration of DICOM and openEHR and data exchange without losing imaging information between two standards.

How to integrate the electronic health record and patient-centered communication into the medical visit: a skills-based approach.

PubMed

Duke, Pamela; Frankel, Richard M; Reis, Shmuel

2013-01-01

Implementation of the electronic health record (EHR) has changed the dynamics of doctor-patient communication. Physicians train to use EHRs from a technical standpoint, giving only minimal attention to integrating the human dimensions of the doctor-patient relationship into the computer-accompanied medical visit. This article reviews the literature and proposes a model to help clinicians, residents, and students improve physician-patient communication while using the EHR. We conducted a literature search on use of communication skills when interfacing with the EHR. We observed an instructional gap and developed a model using evidence-based communication skills. This model integrates patient-centered interview skills and aims to empower physicians to remain patient centered while effectively using EHRs. It may also serve as a template for future educational and practice interventions for use of the EHR in the examination room.

Transformation of standardized clinical models based on OWL technologies: from CEM to OpenEHR archetypes

PubMed Central

Legaz-García, María del Carmen; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás; Chute, Christopher G; Tao, Cui

2015-01-01

Introduction The semantic interoperability of electronic healthcare records (EHRs) systems is a major challenge in the medical informatics area. International initiatives pursue the use of semantically interoperable clinical models, and ontologies have frequently been used in semantic interoperability efforts. The objective of this paper is to propose a generic, ontology-based, flexible approach for supporting the automatic transformation of clinical models, which is illustrated for the transformation of Clinical Element Models (CEMs) into openEHR archetypes. Methods Our transformation method exploits the fact that the information models of the most relevant EHR specifications are available in the Web Ontology Language (OWL). The transformation approach is based on defining mappings between those ontological structures. We propose a way in which CEM entities can be transformed into openEHR by using transformation templates and OWL as common representation formalism. The transformation architecture exploits the reasoning and inferencing capabilities of OWL technologies. Results We have devised a generic, flexible approach for the transformation of clinical models, implemented for the unidirectional transformation from CEM to openEHR, a series of reusable transformation templates, a proof-of-concept implementation, and a set of openEHR archetypes that validate the methodological approach. Conclusions We have been able to transform CEM into archetypes in an automatic, flexible, reusable transformation approach that could be extended to other clinical model specifications. We exploit the potential of OWL technologies for supporting the transformation process. We believe that our approach could be useful for international efforts in the area of semantic interoperability of EHR systems. PMID:25670753

Determination of Minimum Data Set (MSD) in Echocardiography Reporting System to Exchange with Iran's Electronic Health Record (EHR) System.

PubMed

Mahmoudvand, Zahra; Kamkar, Mehran; Shahmoradi, Leila; Nejad, Ahmadreza Farzaneh

2016-04-01

Determination of minimum data set (MDS) in echocardiography reports is necessary for documentation and putting information in a standard way, and leads to the enhancement of electrocardiographic studies through having access to precise and perfect reports and also to the development of a standard database for electrocardiographic reports. to determine the minimum data set of echocardiography reporting system to exchange with Iran's electronic health record (EHR) system. First, a list of minimum data set was prepared after reviewing texts and studying cardiac patients' records. Then, to determine the content validity of the prepared MDS, the expert views of 10 cardiologists and 10 health information management (HIM) specialists were obtained; to estimate the reliability of the set, test-retest method was employed. Finally, the data were analyzed using SPSS software. The highest degree of consensus was found for the following MDSs: patient's name and family name (5), accepting doctor's name and family name, familial death records due to cardiac disorders, the image identification code, mitral valve, aortic valve, tricuspid valve, pulmonary valve, left ventricle, hole, atrium valve, Doppler examination of ventricular and atrial movement models and diagnoses with an average of. To prepare a model of echocardiography reporting system to exchange with EHR system, creation a standard data set is the vital point. Therefore, based on the research findings, the minimum reporting system data to exchange with Iran's electronic health record system include information on entity, management, medical record, carried-out acts, and the main content of the echocardiography report, which the planners of reporting system should consider.

A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data.

PubMed

Tao, Cui; Jiang, Guoqian; Oniki, Thomas A; Freimuth, Robert R; Zhu, Qian; Sharma, Deepak; Pathak, Jyotishman; Huff, Stanley M; Chute, Christopher G

2013-05-01

The clinical element model (CEM) is an information model designed for representing clinical information in electronic health records (EHR) systems across organizations. The current representation of CEMs does not support formal semantic definitions and therefore it is not possible to perform reasoning and consistency checking on derived models. This paper introduces our efforts to represent the CEM specification using the Web Ontology Language (OWL). The CEM-OWL representation connects the CEM content with the Semantic Web environment, which provides authoring, reasoning, and querying tools. This work may also facilitate the harmonization of the CEMs with domain knowledge represented in terminology models as well as other clinical information models such as the openEHR archetype model. We have created the CEM-OWL meta ontology based on the CEM specification. A convertor has been implemented in Java to automatically translate detailed CEMs from XML to OWL. A panel evaluation has been conducted, and the results show that the OWL modeling can faithfully represent the CEM specification and represent patient data.

A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data

PubMed Central

Tao, Cui; Jiang, Guoqian; Oniki, Thomas A; Freimuth, Robert R; Zhu, Qian; Sharma, Deepak; Pathak, Jyotishman; Huff, Stanley M; Chute, Christopher G

2013-01-01

The clinical element model (CEM) is an information model designed for representing clinical information in electronic health records (EHR) systems across organizations. The current representation of CEMs does not support formal semantic definitions and therefore it is not possible to perform reasoning and consistency checking on derived models. This paper introduces our efforts to represent the CEM specification using the Web Ontology Language (OWL). The CEM-OWL representation connects the CEM content with the Semantic Web environment, which provides authoring, reasoning, and querying tools. This work may also facilitate the harmonization of the CEMs with domain knowledge represented in terminology models as well as other clinical information models such as the openEHR archetype model. We have created the CEM-OWL meta ontology based on the CEM specification. A convertor has been implemented in Java to automatically translate detailed CEMs from XML to OWL. A panel evaluation has been conducted, and the results show that the OWL modeling can faithfully represent the CEM specification and represent patient data. PMID:23268487

What do electronic health record vendors reveal about their products: an analysis of vendor websites.

PubMed

Yeung, Natalie K; Jadad, Alejandro R; Shachak, Aviv

2013-02-19

Purchasing electronic health records (EHRs) typically follows a process in which potential adopters actively seek information, compare alternatives, and form attitudes towards the product. A potential source of information on EHRs that can be used in the process is vendor websites. It is unclear how much product information is presented on EHR vendor websites or the extent of its value during EHR purchasing decisions. To explore what features of EHR systems are presented by vendors in Ontario, Canada, on their websites, and the persuasive means they use to market such systems; to compare the online information available about primary care EHR systems with that about hospital EHR systems, and with data compiled by OntarioMD, a regional certifying agency. A list of EHR systems available in Ontario was created. The contents of vendor websites were analyzed. A template for data collection and organization was developed and used to collect and organize information on the vendor, website content, and EHR features. First, we mapped information on system features to categories based on a framework from the Institute of Medicine (IOM). Second, we used a grounded theory-like approach to explore information for building consumer confidence in the vendor and product, and the various persuasive strategies employed on vendor websites. All data were first coded by one researcher. A peer reviewer independently analyzed a randomly chosen subset of the websites (10 of 21; 48%) and provided feedback towards a unified coding scheme. All data were then re-coded and categorized into themes. Finally, we compared information from vendor websites and data gathered by OntarioMD. Vendors provided little specific product information on their websites. Only two of five acute care EHR websites (40%) and nine of 16 websites for primary care systems (56%) featured seven or all eight of the IOM components. Several vendor websites included system interface demonstrations: screenshots (six websites), public videos or slideshows (four websites), or for registered viewers only (three websites). Persuasive means used by vendors included testimonials on 14/21 (67%) websites, and directional language. Except for one free system, trial EHR versions were not available. OntarioMD provided more comprehensive information about primary care systems than the vendors' websites. Of 14 points of comparison, only the inclusion of templates and bilingual interfaces were fully represented in both data sources. For all other categories, the vendor websites were less complete than the OntarioMD site. EHR vendor websites employ various persuasive means, but lack product-specific information and do not provide options for trying systems on a limited basis. This may impede the ability of potential adopters to form perceptions and compare various offerings. Both vendors and clients could benefit from greater transparency and more specific product information on the Web. N/A.

Resistance Is Futile: But It Is Slowing the Pace of EHR Adoption Nonetheless

PubMed Central

Ford, Eric W.; Menachemi, Nir; Peterson, Lori T.; Huerta, Timothy R.

2009-01-01

Objective The purpose of this study is to reassess the projected rate of Electronic Health Record (EHR) diffusion and examine how the federal government's efforts to promote the use of EHR technology have influenced physicians' willingness to adopt such systems. The study recreates and extends the analyses conducted by Ford et al. 1 The two periods examined come before and after the U.S. Federal Government's concerted activity to promote EHR adoption. Design Meta-analysis and bass modeling are used to compare EHR diffusion rates for two distinct periods of government activity. Very low levels of government activity to promote EHR diffusion marked the first period, before 2004. In 2004, the President of the United States called for a “Universal EHR Adoption” by 2014 (10 yrs), creating the major wave of activity and increased awareness of how EHRs will impact physicians' practices. Measurement EHR adoption parameters—external and internal coefficients of influence—are estimated using bass diffusion models and future adoption rates are projected. Results Comparing the EHR adoption rates before and after 2004 (2001–2004 and 2001–2007 respectively) indicate the physicians' resistance to adoption has increased during the second period. Based on current levels of adoption, less than half the physicians working in small practices will have implemented an EHR by 2014 (47.3%). Conclusions The external forces driving EHR diffusion have grown in importance since 2004 relative to physicians' internal motivation to adopt such systems. Several national forces are likely contributing to the slowing pace of EHR diffusion. PMID:19261931

Healthcare information technology's relativity problems: a typology of how patients' physical reality, clinicians' mental models, and healthcare information technology differ.

PubMed

Smith, Sean W; Koppel, Ross

2014-01-01

To model inconsistencies or distortions among three realities: patients' physical reality; clinicians' mental models of patients' conditions, laboratories, etc; representation of that reality in electronic health records (EHR). To serve as a potential tool for quality improvement of EHRs. Using observations, literature, information technology (IT) logs, vendor and US Food and Drug Administration reports, we constructed scenarios/models of how patients' realities, clinicians' mental models, and EHRs can misalign to produce distortions in comprehension and treatment. We then categorized them according to an emergent typology derived from the cases themselves and refined the categories based on insights gained from the literature of interactive sociotechnical systems analysis, decision support science, and human computer interaction. Typical of grounded theory methods, the categories underwent repeated modifications. We constructed 45 scenarios of misalignment between patients' physical realities, clinicians' mental models, and EHRs. We then identified five general types of misrepresentation in these cases: IT data too narrowly focused; IT data too broadly focused; EHRs miss critical reality; data multiplicities-perhaps contradictory or confusing; distortions from data reflected back and forth across users, sensors, and others. The 45 scenarios are presented, organized by the five types. With humans, there is a physical reality and actors' mental models of that reality. In healthcare, there is another player: the EHR/healthcare IT, which implicitly and explicitly reflects many mental models, facets of reality, and measures thereof that vary in reliability and consistency. EHRs are both microcosms and shapers of medical care. Our typology and scenarios are intended to be useful to healthcare IT designers and implementers in improving EHR systems and reducing the unintended negative consequences of their use.

Electronic health record acceptance by physicians: testing an integrated theoretical model.

PubMed

Gagnon, Marie-Pierre; Ghandour, El Kebir; Talla, Pascaline Kengne; Simonyan, David; Godin, Gaston; Labrecque, Michel; Ouimet, Mathieu; Rousseau, Michel

2014-04-01

Several countries are in the process of implementing an Electronic Health Record (EHR), but limited physicians' acceptance of this technology presents a serious threat to its successful implementation. The aim of this study was to identify the main determinants of physician acceptance of EHR in a sample of general practitioners and specialists of the Province of Quebec (Canada). We sent an electronic questionnaire to physician members of the Quebec Medical Association. We tested four theoretical models (Technology acceptance model (TAM), Extended TAM, Psychosocial Model, and Integrated Model) using path analysis and multiple linear regression analysis in order to identify the main determinants of physicians' intention to use the EHR. We evaluated the modifying effect of sociodemographic characteristics using multi-group analysis of structural weights invariance. A total of 157 questionnaires were returned. The four models performed well and explained between 44% and 55% of the variance in physicians' intention to use the EHR. The Integrated model performed the best and showed that perceived ease of use, professional norm, social norm, and demonstrability of the results are the strongest predictors of physicians' intention to use the EHR. Age, gender, previous experience and specialty modified the association between those determinants and intention. The proposed integrated theoretical model is useful in identifying which factors could motivate physicians from different backgrounds to use the EHR. Physicians who perceive the EHR to be easy to use, coherent with their professional norms, supported by their peers and patients, and able to demonstrate tangible results are more likely to accept this technology. Age, gender, specialty and experience should also be taken into account when developing EHR implementation strategies targeting physicians. Copyright © 2013 Elsevier Inc. All rights reserved.

International developments in openEHR archetypes and templates.

PubMed

Leslie, Heather

Electronic Health Records (EHRs) are a complex knowledge domain. The ability to design EHRs to cope with the changing nature of health knowledge, and to be shareable, has been elusive. A recent pilot study1 tested the applicability of the CEN 13606 as an electronic health record standard. Using openEHR archetypes and tools2, 650 clinical content specifi cations (archetypes) were created (e.g. for blood pressure) and re-used across all clinical specialties and contexts. Groups of archetypes were aggregated in templates to support clinical information gathering or viewing (e.g. 80 separate archetypes make up the routine antenatal visit record). Over 60 templates were created for use in the emergency department, antenatal care and delivery of an infant, and paediatric hearing loss assessment. The primary goal is to define a logical clinical record architecture for the NHS but potentially, with archetypes as the keystone, shareable EHRs will also be attainable. Archetype and template development work is ongoing, with associated evaluation occurring in parallel.

Studying the Vendor Perspective on Clinical Decision Support

PubMed Central

Ash, Joan S.; Sittig, Dean F.; McMullen, Carmit K.; McCormack, James L.; Wright, Adam; Bunce, Arwen; Wasserman, Joseph; Mohan, Vishnu; Cohen, Deborah J.; Shapiro, Michael; Middleton, Blackford

2011-01-01

In prior work, using a Rapid Assessment Process (RAP), we have investigated clinical decision support (CDS) in ambulatory clinics and hospitals. We realized that individuals in these settings provide only one perspective related to the CDS landscape, which also includes content vendors and electronic health record (EHR) vendors. To discover content vendors’ perspectives and their perceived challenges, we modified RAP for industrial settings. We describe how we employed RAP, and show its utility by describing two illustrative themes. We found that while the content vendors believe they provide unique much-needed services, the amount of labor involved in content development is underestimated by others. We also found that the content vendors believe their products are resources to be used by practitioners, so they are somewhat protected from liability issues. To promote adequate understanding about these issues, we recommend a “three way conversation” among content vendors, EHR vendors, and user organizations. PMID:22195058

Transformation of standardized clinical models based on OWL technologies: from CEM to OpenEHR archetypes.

PubMed

Legaz-García, María del Carmen; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás; Chute, Christopher G; Tao, Cui

2015-05-01

The semantic interoperability of electronic healthcare records (EHRs) systems is a major challenge in the medical informatics area. International initiatives pursue the use of semantically interoperable clinical models, and ontologies have frequently been used in semantic interoperability efforts. The objective of this paper is to propose a generic, ontology-based, flexible approach for supporting the automatic transformation of clinical models, which is illustrated for the transformation of Clinical Element Models (CEMs) into openEHR archetypes. Our transformation method exploits the fact that the information models of the most relevant EHR specifications are available in the Web Ontology Language (OWL). The transformation approach is based on defining mappings between those ontological structures. We propose a way in which CEM entities can be transformed into openEHR by using transformation templates and OWL as common representation formalism. The transformation architecture exploits the reasoning and inferencing capabilities of OWL technologies. We have devised a generic, flexible approach for the transformation of clinical models, implemented for the unidirectional transformation from CEM to openEHR, a series of reusable transformation templates, a proof-of-concept implementation, and a set of openEHR archetypes that validate the methodological approach. We have been able to transform CEM into archetypes in an automatic, flexible, reusable transformation approach that could be extended to other clinical model specifications. We exploit the potential of OWL technologies for supporting the transformation process. We believe that our approach could be useful for international efforts in the area of semantic interoperability of EHR systems. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Natural Language Processing System That Links Medical Terms in Electronic Health Record Notes to Lay Definitions: System Development Using Physician Reviews.

PubMed

Chen, Jinying; Druhl, Emily; Polepalli Ramesh, Balaji; Houston, Thomas K; Brandt, Cynthia A; Zulman, Donna M; Vimalananda, Varsha G; Malkani, Samir; Yu, Hong

2018-01-22

Many health care systems now allow patients to access their electronic health record (EHR) notes online through patient portals. Medical jargon in EHR notes can confuse patients, which may interfere with potential benefits of patient access to EHR notes. The aim of this study was to develop and evaluate the usability and content quality of NoteAid, a Web-based natural language processing system that links medical terms in EHR notes to lay definitions, that is, definitions easily understood by lay people. NoteAid incorporates two core components: CoDeMed, a lexical resource of lay definitions for medical terms, and MedLink, a computational unit that links medical terms to lay definitions. We developed innovative computational methods, including an adapted distant supervision algorithm to prioritize medical terms important for EHR comprehension to facilitate the effort of building CoDeMed. Ten physician domain experts evaluated the user interface and content quality of NoteAid. The evaluation protocol included a cognitive walkthrough session and a postsession questionnaire. Physician feedback sessions were audio-recorded. We used standard content analysis methods to analyze qualitative data from these sessions. Physician feedback was mixed. Positive feedback on NoteAid included (1) Easy to use, (2) Good visual display, (3) Satisfactory system speed, and (4) Adequate lay definitions. Opportunities for improvement arising from evaluation sessions and feedback included (1) improving the display of definitions for partially matched terms, (2) including more medical terms in CoDeMed, (3) improving the handling of terms whose definitions vary depending on different contexts, and (4) standardizing the scope of definitions for medicines. On the basis of these results, we have improved NoteAid's user interface and a number of definitions, and added 4502 more definitions in CoDeMed. Physician evaluation yielded useful feedback for content validation and refinement of this innovative tool that has the potential to improve patient EHR comprehension and experience using patient portals. Future ongoing work will develop algorithms to handle ambiguous medical terms and test and evaluate NoteAid with patients. ©Jinying Chen, Emily Druhl, Balaji Polepalli Ramesh, Thomas K Houston, Cynthia A Brandt, Donna M Zulman, Varsha G Vimalananda, Samir Malkani, Hong Yu. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.01.2018.

Using ISO 25040 standard for evaluating electronic health record systems.

PubMed

Oliveira, Marília; Novaes, Magdala; Vasconcelos, Alexandre

2013-01-01

Quality of electronic health record systems (EHR-S) is one of the key points in the discussion about the safe use of this kind of system. It stimulates creation of technical standards and certifications in order to establish the minimum requirements expected for these systems. [1] In other side, EHR-S suppliers need to invest in evaluation of their products to provide systems according to these requirements. This work presents a proposal of use ISO 25040 standard, which focuses on the evaluation of software products, for define a model of evaluation of EHR-S in relation to Brazilian Certification for Electronic Health Record Systems - SBIS-CFM Certification. Proposal instantiates the process described in ISO 25040 standard using the set of requirements that is scope of the Brazilian certification. As first results, this research has produced an evaluation model and a scale for classify an EHR-S about its compliance level in relation to certification. This work in progress is part for the acquisition of the degree of master in Computer Science at the Federal University of Pernambuco.

Use of Electronic Health Record Simulation to Understand the Accuracy of Intern Progress Notes

PubMed Central

March, Christopher A.; Scholl, Gretchen; Dversdal, Renee K.; Richards, Matthew; Wilson, Leah M.; Mohan, Vishnu; Gold, Jeffrey A.

2016-01-01

Background With the widespread adoption of electronic health records (EHRs), there is a growing awareness of problems in EHR training for new users and subsequent problems with the quality of information present in EHR-generated progress notes. By standardizing the case, simulation allows for the discovery of EHR patterns of use as well as a modality to aid in EHR training. Objective To develop a high-fidelity EHR training exercise for internal medicine interns to understand patterns of EHR utilization in the generation of daily progress notes. Methods Three months after beginning their internship, 32 interns participated in an EHR simulation designed to assess patterns in note writing and generation. Each intern was given a simulated chart and instructed to create a daily progress note. Notes were graded for use of copy-paste, macros, and accuracy of presented data. Results A total of 31 out of 32 interns (97%) completed the exercise. There was wide variance in use of macros to populate data, with multiple macro types used for the same data category. Three-quarters of notes contained either copy-paste elements or the elimination of active medical problems from the prior days' notes. This was associated with a significant number of quality issues, including failure to recognize a lack of deep vein thrombosis prophylaxis, medications stopped on admission, and issues in prior discharge summary. Conclusions Interns displayed wide variation in the process of creating progress notes. Additional studies are being conducted to determine the impact EHR-based simulation has on standardization of note content. PMID:27168894

Use of Electronic Health Record Simulation to Understand the Accuracy of Intern Progress Notes.

PubMed

March, Christopher A; Scholl, Gretchen; Dversdal, Renee K; Richards, Matthew; Wilson, Leah M; Mohan, Vishnu; Gold, Jeffrey A

2016-05-01

Background With the widespread adoption of electronic health records (EHRs), there is a growing awareness of problems in EHR training for new users and subsequent problems with the quality of information present in EHR-generated progress notes. By standardizing the case, simulation allows for the discovery of EHR patterns of use as well as a modality to aid in EHR training. Objective To develop a high-fidelity EHR training exercise for internal medicine interns to understand patterns of EHR utilization in the generation of daily progress notes. Methods Three months after beginning their internship, 32 interns participated in an EHR simulation designed to assess patterns in note writing and generation. Each intern was given a simulated chart and instructed to create a daily progress note. Notes were graded for use of copy-paste, macros, and accuracy of presented data. Results A total of 31 out of 32 interns (97%) completed the exercise. There was wide variance in use of macros to populate data, with multiple macro types used for the same data category. Three-quarters of notes contained either copy-paste elements or the elimination of active medical problems from the prior days' notes. This was associated with a significant number of quality issues, including failure to recognize a lack of deep vein thrombosis prophylaxis, medications stopped on admission, and issues in prior discharge summary. Conclusions Interns displayed wide variation in the process of creating progress notes. Additional studies are being conducted to determine the impact EHR-based simulation has on standardization of note content.

Modeling healthcare authorization and claim submissions using the openEHR dual-model approach

PubMed Central

2011-01-01

Background The TISS standard is a set of mandatory forms and electronic messages for healthcare authorization and claim submissions among healthcare plans and providers in Brazil. It is not based on formal models as the new generation of health informatics standards suggests. The objective of this paper is to model the TISS in terms of the openEHR archetype-based approach and integrate it into a patient-centered EHR architecture. Methods Three approaches were adopted to model TISS. In the first approach, a set of archetypes was designed using ENTRY subclasses. In the second one, a set of archetypes was designed using exclusively ADMIN_ENTRY and CLUSTERs as their root classes. In the third approach, the openEHR ADMIN_ENTRY is extended with classes designed for authorization and claim submissions, and an ISM_TRANSITION attribute is added to the COMPOSITION class. Another set of archetypes was designed based on this model. For all three approaches, templates were designed to represent the TISS forms. Results The archetypes based on the openEHR RM (Reference Model) can represent all TISS data structures. The extended model adds subclasses and an attribute to the COMPOSITION class to represent information on authorization and claim submissions. The archetypes based on all three approaches have similar structures, although rooted in different classes. The extended openEHR RM model is more semantically aligned with the concepts involved in a claim submission, but may disrupt interoperability with other systems and the current tools must be adapted to deal with it. Conclusions Modeling the TISS standard by means of the openEHR approach makes it aligned with ISO recommendations and provides a solid foundation on which the TISS can evolve. Although there are few administrative archetypes available, the openEHR RM is expressive enough to represent the TISS standard. This paper focuses on the TISS but its results may be extended to other billing processes. A complete communication architecture to simulate the exchange of TISS data between systems according to the openEHR approach still needs to be designed and implemented. PMID:21992670

Clinic Workflow Simulations using Secondary EHR Data

PubMed Central

Hribar, Michelle R.; Biermann, David; Read-Brown, Sarah; Reznick, Leah; Lombardi, Lorinna; Parikh, Mansi; Chamberlain, Winston; Yackel, Thomas R.; Chiang, Michael F.

2016-01-01

Clinicians today face increased patient loads, decreased reimbursements and potential negative productivity impacts of using electronic health records (EHR), but have little guidance on how to improve clinic efficiency. Discrete event simulation models are powerful tools for evaluating clinical workflow and improving efficiency, particularly when they are built from secondary EHR timing data. The purpose of this study is to demonstrate that these simulation models can be used for resource allocation decision making as well as for evaluating novel scheduling strategies in outpatient ophthalmology clinics. Key findings from this study are that: 1) secondary use of EHR timestamp data in simulation models represents clinic workflow, 2) simulations provide insight into the best allocation of resources in a clinic, 3) simulations provide critical information for schedule creation and decision making by clinic managers, and 4) simulation models built from EHR data are potentially generalizable. PMID:28269861

What Do Electronic Health Record Vendors Reveal About Their Products: An Analysis of Vendor Websites

PubMed Central

Yeung, Natalie K; Jadad, Alejandro R

2013-01-01

Background Purchasing electronic health records (EHRs) typically follows a process in which potential adopters actively seek information, compare alternatives, and form attitudes towards the product. A potential source of information on EHRs that can be used in the process is vendor websites. It is unclear how much product information is presented on EHR vendor websites or the extent of its value during EHR purchasing decisions. Objective To explore what features of EHR systems are presented by vendors in Ontario, Canada, on their websites, and the persuasive means they use to market such systems; to compare the online information available about primary care EHR systems with that about hospital EHR systems, and with data compiled by OntarioMD, a regional certifying agency. Methods A list of EHR systems available in Ontario was created. The contents of vendor websites were analyzed. A template for data collection and organization was developed and used to collect and organize information on the vendor, website content, and EHR features. First, we mapped information on system features to categories based on a framework from the Institute of Medicine (IOM). Second, we used a grounded theory–like approach to explore information for building consumer confidence in the vendor and product, and the various persuasive strategies employed on vendor websites. All data were first coded by one researcher. A peer reviewer independently analyzed a randomly chosen subset of the websites (10 of 21; 48%) and provided feedback towards a unified coding scheme. All data were then re-coded and categorized into themes. Finally, we compared information from vendor websites and data gathered by OntarioMD. Results Vendors provided little specific product information on their websites. Only two of five acute care EHR websites (40%) and nine of 16 websites for primary care systems (56%) featured seven or all eight of the IOM components. Several vendor websites included system interface demonstrations: screenshots (six websites), public videos or slideshows (four websites), or for registered viewers only (three websites). Persuasive means used by vendors included testimonials on 14/21 (67%) websites, and directional language. Except for one free system, trial EHR versions were not available. OntarioMD provided more comprehensive information about primary care systems than the vendors’ websites. Of 14 points of comparison, only the inclusion of templates and bilingual interfaces were fully represented in both data sources. For all other categories, the vendor websites were less complete than the OntarioMD site. Conclusions EHR vendor websites employ various persuasive means, but lack product-specific information and do not provide options for trying systems on a limited basis. This may impede the ability of potential adopters to form perceptions and compare various offerings. Both vendors and clients could benefit from greater transparency and more specific product information on the Web. Trial Registration N/A PMID:23422722

Developing a theoretical model and questionnaire survey instrument to measure the success of electronic health records in residential aged care

PubMed Central

Yu, Ping; Qian, Siyu

2018-01-01

Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: system quality, information quality, service quality, use, user satisfaction and net benefits. Two variables training and self-efficacy were also incorporated into the model. A questionnaire survey instrument was designed to measure the eight variables in the model. After a pilot test, the measurement scale was used to collect data from 243 nursing staff members in 10 residential aged care homes belonging to three management groups in Australia. Partial least squares path modeling was conducted to validate the model. The validated EHR systems success model predicts the impact of the four antecedent variables—training, self-efficacy, system quality and information quality—on the net benefits, the indicator of EHR systems success, through the intermittent variables use and user satisfaction. A 24-item measurement scale was developed to quantitatively evaluate the performance of an EHR system. The parsimonious EHR systems success model and the measurement scale can be used to benchmark EHR systems success across organizations and units and over time. PMID:29315323

Developing a theoretical model and questionnaire survey instrument to measure the success of electronic health records in residential aged care.

PubMed

Yu, Ping; Qian, Siyu

2018-01-01

Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: system quality, information quality, service quality, use, user satisfaction and net benefits. Two variables training and self-efficacy were also incorporated into the model. A questionnaire survey instrument was designed to measure the eight variables in the model. After a pilot test, the measurement scale was used to collect data from 243 nursing staff members in 10 residential aged care homes belonging to three management groups in Australia. Partial least squares path modeling was conducted to validate the model. The validated EHR systems success model predicts the impact of the four antecedent variables-training, self-efficacy, system quality and information quality-on the net benefits, the indicator of EHR systems success, through the intermittent variables use and user satisfaction. A 24-item measurement scale was developed to quantitatively evaluate the performance of an EHR system. The parsimonious EHR systems success model and the measurement scale can be used to benchmark EHR systems success across organizations and units and over time.

Access Control Model for Sharing Composite Electronic Health Records

NASA Astrophysics Data System (ADS)

Jin, Jing; Ahn, Gail-Joon; Covington, Michael J.; Zhang, Xinwen

The adoption of electronically formatted medical records, so called Electronic Health Records (EHRs), has become extremely important in healthcare systems to enable the exchange of medical information among stakeholders. An EHR generally consists of data with different types and sensitivity degrees which must be selectively shared based on the need-to-know principle. Security mechanisms are required to guarantee that only authorized users have access to specific portions of such critical record for legitimate purposes. In this paper, we propose a novel approach for modelling access control scheme for composite EHRs. Our model formulates the semantics and structural composition of an EHR document, from which we introduce a notion of authorized zones of the composite EHR at different granularity levels, taking into consideration of several important criteria such as data types, intended purposes and information sensitivities.

Evaluating a scalable model for implementing electronic health records in resource-limited settings.

PubMed

Were, Martin C; Emenyonu, Nneka; Achieng, Marion; Shen, Changyu; Ssali, John; Masaba, John P M; Tierney, William M

2010-01-01

Current models for implementing electronic health records (EHRs) in resource-limited settings may not be scalable because they fail to address human-resource and cost constraints. This paper describes an implementation model which relies on shared responsibility between local sites and an external three-pronged support infrastructure consisting of: (1) a national technical expertise center, (2) an implementer's community, and (3) a developer's community. This model was used to implement an open-source EHR in three Ugandan HIV-clinics. Pre-post time-motion study at one site revealed that Primary Care Providers spent a third less time in direct and indirect care of patients (p<0.001) and 40% more time on personal activities (p=0.09) after EHRs implementation. Time spent by previously enrolled patients with non-clinician staff fell by half (p=0.004) and with pharmacy by 63% (p<0.001). Surveyed providers were highly satisfied with the EHRs and its support infrastructure. This model offers a viable approach for broadly implementing EHRs in resource-limited settings.

Dynamic User Interfaces for Service Oriented Architectures in Healthcare.

PubMed

Schweitzer, Marco; Hoerbst, Alexander

2016-01-01

Electronic Health Records (EHRs) play a crucial role in healthcare today. Considering a data-centric view, EHRs are very advanced as they provide and share healthcare data in a cross-institutional and patient-centered way adhering to high syntactic and semantic interoperability. However, the EHR functionalities available for the end users are rare and hence often limited to basic document query functions. Future EHR use necessitates the ability to let the users define their needed data according to a certain situation and how this data should be processed. Workflow and semantic modelling approaches as well as Web services provide means to fulfil such a goal. This thesis develops concepts for dynamic interfaces between EHR end users and a service oriented eHealth infrastructure, which allow the users to design their flexible EHR needs, modeled in a dynamic and formal way. These are used to discover, compose and execute the right Semantic Web services.

Business analysis for a sustainable, multi-stakeholder ecosystem for leveraging the Electronic Health Records for Clinical Research (EHR4CR) platform in Europe.

PubMed

Dupont, Danielle; Beresniak, Ariel; Sundgren, Mats; Schmidt, Andreas; Ainsworth, John; Coorevits, Pascal; Kalra, Dipak; Dewispelaere, Marc; De Moor, Georges

2017-01-01

The Electronic Health Records for Clinical Research (EHR4CR) technological platform has been developed to enable the trustworthy reuse of hospital electronic health records data for clinical research. The EHR4CR platform can enhance and speed up clinical research scenarios: protocol feasibility assessment, patient identification for recruitment in clinical trials, and clinical data exchange, including for reporting serious adverse events. Our objective was to seed a multi-stakeholder ecosystem to enable the scalable exploitation of the EHR4CR platform in Europe, and to assess its economic sustainability. Market analyses were conducted by a multidisciplinary task force to define an EHR4CR emerging ecosystem and multi-stakeholder value chain. This involved mapping stakeholder groups and defining their unmet needs, incentives, potential barriers for adopting innovative solutions, roles and interdependencies. A comprehensive business model, value propositions, and sustainability strategies were developed accordingly. Using simulation modelling (including Monte Carlo simulations) and a 5-year horizon, the potential financial outcomes of the business model were forecasted from the perspective of an EHR4CR service provider. A business ecosystem was defined to leverage the EHR4CR multi-stakeholder value chain. Value propositions were developed describing the expected benefits of EHR4CR solutions for all stakeholders. From an EHR4CR service provider's viewpoint, the business model simulation estimated that a profitability ratio of up to 1.8 could be achieved at year 1, with potential for growth in subsequent years depending on projected market uptake. By enhancing and speeding up existing processes, EHR4CR solutions promise to transform the clinical research landscape. The ecosystem defined provides the organisational framework for optimising the value and benefits for all stakeholders involved, in a sustainable manner. Our study suggests that the exploitation of EHR4CR solutions appears profitable and sustainable in Europe, with a growth potential depending on the rates of market and hospital adoption. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Electronic health record use to classify patients with newly diagnosed versus preexisting type 2 diabetes: infrastructure for comparative effectiveness research and population health management.

PubMed

Kudyakov, Rustam; Bowen, James; Ewen, Edward; West, Suzanne L; Daoud, Yahya; Fleming, Neil; Masica, Andrew

2012-02-01

Use of electronic health record (EHR) content for comparative effectiveness research (CER) and population health management requires significant data configuration. A retrospective cohort study was conducted using patients with diabetes followed longitudinally (N=36,353) in the EHR deployed at outpatient practice networks of 2 health care systems. A data extraction and classification algorithm targeting identification of patients with a new diagnosis of type 2 diabetes mellitus (T2DM) was applied, with the main criterion being a minimum 30-day window between the first visit documented in the EHR and the entry of T2DM on the EHR problem list. Chart reviews (N=144) validated the performance of refining this EHR classification algorithm with external administrative data. Extraction using EHR data alone designated 3205 patients as newly diagnosed with T2DM with classification accuracy of 70.1%. Use of external administrative data on that preselected population improved classification accuracy of cases identified as new T2DM diagnosis (positive predictive value was 91.9% with that step). Laboratory and medication data did not help case classification. The final cohort using this 2-stage classification process comprised 1972 patients with a new diagnosis of T2DM. Data use from current EHR systems for CER and disease management mandates substantial tailoring. Quality between EHR clinical data generated in daily care and that required for population health research varies. As evidenced by this process for classification of newly diagnosed T2DM cases, validation of EHR data with external sources can be a valuable step.

Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.

PubMed

Goldstein, Benjamin A; Navar, Ann Marie; Pencina, Michael J; Ioannidis, John P A

2017-01-01

Electronic health records (EHRs) are an increasingly common data source for clinical risk prediction, presenting both unique analytic opportunities and challenges. We sought to evaluate the current state of EHR based risk prediction modeling through a systematic review of clinical prediction studies using EHR data. We searched PubMed for articles that reported on the use of an EHR to develop a risk prediction model from 2009 to 2014. Articles were extracted by two reviewers, and we abstracted information on study design, use of EHR data, model building, and performance from each publication and supplementary documentation. We identified 107 articles from 15 different countries. Studies were generally very large (median sample size = 26 100) and utilized a diverse array of predictors. Most used validation techniques (n = 94 of 107) and reported model coefficients for reproducibility (n = 83). However, studies did not fully leverage the breadth of EHR data, as they uncommonly used longitudinal information (n = 37) and employed relatively few predictor variables (median = 27 variables). Less than half of the studies were multicenter (n = 50) and only 26 performed validation across sites. Many studies did not fully address biases of EHR data such as missing data or loss to follow-up. Average c-statistics for different outcomes were: mortality (0.84), clinical prediction (0.83), hospitalization (0.71), and service utilization (0.71). EHR data present both opportunities and challenges for clinical risk prediction. There is room for improvement in designing such studies. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Towards plug-and-play integration of archetypes into legacy electronic health record systems: the ArchiMed experience.

PubMed

Duftschmid, Georg; Chaloupka, Judith; Rinner, Christoph

2013-01-22

The dual model approach represents a promising solution for achieving semantically interoperable standardized electronic health record (EHR) exchange. Its acceptance, however, will depend on the effort required for integrating archetypes into legacy EHR systems. We propose a corresponding approach that: (a) automatically generates entry forms in legacy EHR systems from archetypes; and (b) allows the immediate export of EHR documents that are recorded via the generated forms and stored in the EHR systems' internal format as standardized and archetype-compliant EHR extracts. As a prerequisite for applying our approach, we define a set of basic requirements for the EHR systems. We tested our approach with an EHR system called ArchiMed and were able to successfully integrate 15 archetypes from a test set of 27. For 12 archetypes, the form generation failed owing to a particular type of complex structure (multiple repeating subnodes), which was prescribed by the archetypes but not supported by ArchiMed's data model. Our experiences show that archetypes should be customized based on the planned application scenario before their integration. This would allow problematic structures to be dissolved and irrelevant optional archetype nodes to be removed. For customization of archetypes, openEHR templates or specialized archetypes may be employed. Gaps in the data types or terminological features supported by an EHR system will often not preclude integration of the relevant archetypes. More work needs to be done on the usability of the generated forms.

Towards plug-and-play integration of archetypes into legacy electronic health record systems: the ArchiMed experience

PubMed Central

2013-01-01

Background The dual model approach represents a promising solution for achieving semantically interoperable standardized electronic health record (EHR) exchange. Its acceptance, however, will depend on the effort required for integrating archetypes into legacy EHR systems. Methods We propose a corresponding approach that: (a) automatically generates entry forms in legacy EHR systems from archetypes; and (b) allows the immediate export of EHR documents that are recorded via the generated forms and stored in the EHR systems’ internal format as standardized and archetype-compliant EHR extracts. As a prerequisite for applying our approach, we define a set of basic requirements for the EHR systems. Results We tested our approach with an EHR system called ArchiMed and were able to successfully integrate 15 archetypes from a test set of 27. For 12 archetypes, the form generation failed owing to a particular type of complex structure (multiple repeating subnodes), which was prescribed by the archetypes but not supported by ArchiMed’s data model. Conclusions Our experiences show that archetypes should be customized based on the planned application scenario before their integration. This would allow problematic structures to be dissolved and irrelevant optional archetype nodes to be removed. For customization of archetypes, openEHR templates or specialized archetypes may be employed. Gaps in the data types or terminological features supported by an EHR system will often not preclude integration of the relevant archetypes. More work needs to be done on the usability of the generated forms. PMID:23339403

The Knowledge Program: an Innovative, Comprehensive Electronic Data Capture System and Warehouse

PubMed Central

Katzan, Irene; Speck, Micheal; Dopler, Chris; Urchek, John; Bielawski, Kay; Dunphy, Cheryl; Jehi, Lara; Bae, Charles; Parchman, Alandra

2011-01-01

Data contained in the electronic health record (EHR) present a tremendous opportunity to improve quality-of-care and enhance research capabilities. However, the EHR is not structured to provide data for such purposes: most clinical information is entered as free text and content varies substantially between providers. Discrete information on patients’ functional status is typically not collected. Data extraction tools are often unavailable. We have developed the Knowledge Program (KP), a comprehensive initiative to improve the collection of discrete clinical information into the EHR and the retrievability of data for use in research, quality, and patient care. A distinct feature of the KP is the systematic collection of patient-reported outcomes, which is captured discretely, allowing more refined analyses of care outcomes. The KP capitalizes on features of the Epic EHR and utilizes an external IT infrastructure distinct from Epic for enhanced functionality. Here, we describe the development and implementation of the KP. PMID:22195124

A data types profile suitable for use with ISO EN 13606.

PubMed

Sun, Shanghua; Austin, Tony; Kalra, Dipak

2012-12-01

ISO EN 13606 is a five part International Standard specifying how Electronic Healthcare Record (EHR) information should be communicated between different EHR systems and repositories. Part 1 of the standard defines an information model for representing the EHR information itself, including the representation of types of data value. A later International Standard, ISO 21090:2010, defines a comprehensive set of models for data types needed by all health IT systems. This latter standard is vast, and duplicates some of the functions already handled by ISO EN 13606 part 1. A profile (sub-set) of ISO 21090 would therefore be expected to provide EHR system vendors with a more specially tailored set of data types to implement and avoid the risk of providing more than one modelling option for representing the information properties. This paper describes the process and design decisions made for developing a data types profile for EHR interoperability.

Case Study: Applying OpenEHR Archetypes to a Clinical Data Repository in a Chinese Hospital.

PubMed

Min, Lingtong; Wang, Li; Lu, Xudong; Duan, Huilong

2015-01-01

openEHR is a flexible and scalable modeling methodology for clinical information and has been widely adopted in Europe and Australia. Due to the reasons of differences in clinical process and management, there are few research projects involving openEHR in China. To investigate the feasibility of openEHR methodology for clinical information modelling in China, this paper carries out a case study to apply openEHR archetypes to Clinical Data Repository (CDR) in a Chinese hospital. The results show that a set of 26 archetypes are found to cover all the concepts used in the CDR. Of all these, 9 (34.6%) are reused without change, 10 are modified and/or extended, and 7 are newly defined. The reasons for modification, extension and newly definition have been discussed, including granularity of archetype, metadata-level versus data-level modelling, and the representation of relationships between archetypes.

Electronic health records: postadoption physician satisfaction and continued use.

PubMed

Wright, Edward; Marvel, Jon

2012-01-01

One goal of public-policy makers in general and health care managers in particular is the adoption and efficient utilization of electronic health record (EHR) systems throughout the health care industry. Consequently, this investigation focused on the effects of known antecedents of technology adoption on physician satisfaction with EHR technology and the continued use of such systems. The American Academy of Family Physicians provided support in the survey of 453 physicians regarding their satisfaction with their EHR use experience. A conceptual model merging technology adoption and computer user satisfaction models was tested using structural equation modeling. Results indicate that effort expectancy (ease of use) has the most substantive effect on physician satisfaction and the continued use of EHR systems. As such, health care managers should be especially sensitive to the user and computer interface of prospective EHR systems to avoid costly and disruptive system selection mistakes.

"Why the hell do we need electronic health records?". EHR acceptance among physicians in private practice in Austria: a qualitative study.

PubMed

Hackl, W O; Hoerbst, A; Ammenwerth, E

2011-01-01

Progress in the medical sciences, together with related technologies, in the past has led to higher specialization and has created a strong need to exchange health information across institutional borders. The concept of electronic health records (EHR) was introduced to fulfill these needs. Remarkably, many EHR introduction projects ran into trouble, not least because they lacked the acceptance of EHR among physicians. Negative emotions, such as anxiety and fear due to a lack of information, may cause change barriers and hamper physicians' acceptance of such projects. The goal of this study was to gain deeper insight into the negative emotions related to the intended implementation of a mandatory national electronic health record system (called ELGA) in Austria among physicians in private practice. Qualitative, problem-centered interviews were conducted with eight physicians in private practice in the capital region of Tyrol. The methods of qualitative content analysis were used to analyze the data. Three hundred and twenty-eight passages in the interviews were selected, annotated, and paraphrased. These passages were assigned to 139 different primary categories. Finally, 18 main categories in the form of statements were derived. They were correlated and a theoretical model was formed to explain the genesis of the detected fears and anxiety related to the ELGA project. The results show that the physicians feel uninformed and snubbed. They fear unknown changes, increased costs, as well as workload and surveillance without obtaining any advantages from using electronic health records in their daily practice. Impartial information campaigns that are tailored to the physicians' needs and questions as along with a comprehensive cost-benefit analysis could benefit the physicians' opinion of EHRs.

Estimating Wisconsin asthma prevalence using clinical electronic health records and public health data.

PubMed

Tomasallo, Carrie D; Hanrahan, Lawrence P; Tandias, Aman; Chang, Timothy S; Cowan, Kelly J; Guilbert, Theresa W

2014-01-01

We compared a statewide telephone health survey with electronic health record (EHR) data from a large Wisconsin health system to estimate asthma prevalence in Wisconsin. We developed frequency tables and logistic regression models using Wisconsin Behavioral Risk Factor Surveillance System and University of Wisconsin primary care clinic data. We compared adjusted odds ratios (AORs) from each model. Between 2007 and 2009, the EHR database contained 376,000 patients (30,000 with asthma), and 23,000 (1850 with asthma) responded to the Behavioral Risk Factor Surveillance System telephone survey. AORs for asthma were similar in magnitude and direction for the majority of covariates, including gender, age, and race/ethnicity, between survey and EHR models. The EHR data had greater statistical power to detect associations than did survey data, especially in pediatric and ethnic populations, because of larger sample sizes. EHRs can be used to estimate asthma prevalence in Wisconsin adults and children. EHR data may improve public health chronic disease surveillance using high-quality data at the local level to better identify areas of disparity and risk factors and guide education and health care interventions.

Physician activity during outpatient visits and subjective workload.

PubMed

Calvitti, Alan; Hochheiser, Harry; Ashfaq, Shazia; Bell, Kristin; Chen, Yunan; El Kareh, Robert; Gabuzda, Mark T; Liu, Lin; Mortensen, Sara; Pandey, Braj; Rick, Steven; Street, Richard L; Weibel, Nadir; Weir, Charlene; Agha, Zia

2017-05-01

We describe methods for capturing and analyzing EHR use and clinical workflow of physicians during outpatient encounters and relating activity to physicians' self-reported workload. We collected temporally-resolved activity data including audio, video, EHR activity, and eye-gaze along with post-visit assessments of workload. These data are then analyzed through a combination of manual content analysis and computational techniques to temporally align streams, providing a range of process measures of EHR usage, clinical workflow, and physician-patient communication. Data was collected from primary care and specialty clinics at the Veterans Administration San Diego Healthcare System and UCSD Health, who use Electronic Health Record (EHR) platforms, CPRS and Epic, respectively. Grouping visit activity by physician, site, specialty, and patient status enables rank-ordering activity factors by their correlation to physicians' subjective work-load as captured by NASA Task Load Index survey. We developed a coding scheme that enabled us to compare timing studies between CPRS and Epic and extract patient and visit complexity profiles. We identified similar patterns of EHR use and navigation at the 2 sites despite differences in functions, user interfaces and consequent coded representations. Both sites displayed similar proportions of EHR function use and navigation, and distribution of visit length, proportion of time physicians attended to EHRs (gaze), and subjective work-load as measured by the task load survey. We found that visit activity was highly variable across individual physicians, and the observed activity metrics ranged widely as correlates to subjective workload. We discuss implications of our study for methodology, clinical workflow and EHR redesign. Copyright © 2017 Elsevier Inc. All rights reserved.

Electronic Health Record (EHR) Organizational Change: Explaining Resistance Through Profession, Organizational Experience, and EHR Communication Quality.

PubMed

Barrett, Ashley K

2018-04-01

The American Recovery and Reinvestment Act passed by the U.S. government in 2009 mandates that all healthcare organizations adopt a certified electronic health record (EHR) system by 2015. Failure to comply will result in Medicare reimbursement penalties, which steadily increase with each year of delinquency. There are several repercussions of this seemingly top-down, rule-bound organizational change-one of which is employee resistance. Given the penalties for violating EHR meaningful use standards are ongoing, resistance to this mandate presents a serious issue for healthcare organizations. This study surveyed 345 employees in one healthcare organization that recently implemented an EHR. Analysis of variance results offer theoretical and pragmatic contributions by demonstrating physicians, nurses, and employees with more experience in their organization are the most resistant to EHR change. The job characteristics model is used to explain these findings. Hierarchical regression analyses also demonstrate the quality of communication surrounding EHR implementation-from both formal and informal sources-is negatively associated with EHR resistance and positively associated with perceived EHR implementation success and EHR's perceived relative advantage.

A reference architecture for integrated EHR in Colombia.

PubMed

de la Cruz, Edgar; Lopez, Diego M; Uribe, Gustavo; Gonzalez, Carolina; Blobel, Bernd

2011-01-01

The implementation of national EHR infrastructures has to start by a detailed definition of the overall structure and behavior of the EHR system (system architecture). Architectures have to be open, scalable, flexible, user accepted and user friendly, trustworthy, based on standards including terminologies and ontologies. The GCM provides an architectural framework created with the purpose of analyzing any kind of system, including EHR system´s architectures. The objective of this paper is to propose a reference architecture for the implementation of an integrated EHR in Colombia, based on the current state of system´s architectural models, and EHR standards. The proposed EHR architecture defines a set of services (elements) and their interfaces, to support the exchange of clinical documents, offering an open, scalable, flexible and semantically interoperable infrastructure. The architecture was tested in a pilot tele-consultation project in Colombia, where dental EHR are exchanged.

Understanding differences in electronic health record (EHR) use: linking individual physicians' perceptions of uncertainty and EHR use patterns in ambulatory care.

PubMed

Lanham, Holly Jordan; Sittig, Dean F; Leykum, Luci K; Parchman, Michael L; Pugh, Jacqueline A; McDaniel, Reuben R

2014-01-01

Electronic health records (EHR) hold great promise for managing patient information in ways that improve healthcare delivery. Physicians differ, however, in their use of this health information technology (IT), and these differences are not well understood. The authors study the differences in individual physicians' EHR use patterns and identify perceptions of uncertainty as an important new variable in understanding EHR use. Qualitative study using semi-structured interviews and direct observation of physicians (n=28) working in a multispecialty outpatient care organization. We identified physicians' perceptions of uncertainty as an important variable in understanding differences in EHR use patterns. Drawing on theories from the medical and organizational literatures, we identified three categories of perceptions of uncertainty: reduction, absorption, and hybrid. We used an existing model of EHR use to categorize physician EHR use patterns as high, medium, and low based on degree of feature use, level of EHR-enabled communication, and frequency that EHR use patterns change. Physicians' perceptions of uncertainty were distinctly associated with their EHR use patterns. Uncertainty reductionists tended to exhibit high levels of EHR use, uncertainty absorbers tended to exhibit low levels of EHR use, and physicians demonstrating both perspectives of uncertainty (hybrids) tended to exhibit medium levels of EHR use. We find evidence linking physicians' perceptions of uncertainty with EHR use patterns. Study findings have implications for health IT research, practice, and policy, particularly in terms of impacting health IT design and implementation efforts in ways that consider differences in physicians' perceptions of uncertainty.

The challenge of electronic health records (EHRs) design and implementation: responses of health workers to drawing a 'big and rich picture' of a future EHR programme using animated tools.

PubMed

Jenkings, K Neil; Wilson, Robert G

2007-01-01

To investigate the use of animation tools to aid visualisation of problems for discussion within focus groups, in the context of healthcare workers discussing electronic health records (EHRs). Ten healthcare staff focus groups, held in a range of organisational contexts. Each focus group was in four stages: baseline discussion, animator presentation, post-animator discussion and questionnaire. Audio recordings of the focus groups were transcribed and coded and the emergent analytic themes analysed for issues relating to EHR design and implementation. The data allowed a comparison of baseline and post-animator discussion. The animator facilitated discussion about EHR issues and these were thematically coded as: Workload; Sharing Information; Access to Information; Record Content; Confidentiality; Patient Consent; and Implementation. We illustrate that use of the animator in focus groups is one means to raise understanding about a proposed EHR development. The animator provided a visual 'probe' to support a more proactive and discursive localised approach to end-user concerns, which could be part of an effective stakeholder engagement and communication strategy crucial in any EHR or health informatics implementation programme. The results of the focus groups were to raise salient issues and concerns, many of which anticipated those that have emerged in the current NHS Connecting for Health Care Records programme in England. Potentially, animator-type technologies may facilitate the user ownership which other forms of dissemination appear to be failing to achieve.

A multi-site cognitive task analysis for biomedical query mediation.

PubMed

Hruby, Gregory W; Rasmussen, Luke V; Hanauer, David; Patel, Vimla L; Cimino, James J; Weng, Chunhua

2016-09-01

To apply cognitive task analyses of the Biomedical query mediation (BQM) processes for EHR data retrieval at multiple sites towards the development of a generic BQM process model. We conducted semi-structured interviews with eleven data analysts from five academic institutions and one government agency, and performed cognitive task analyses on their BQM processes. A coding schema was developed through iterative refinement and used to annotate the interview transcripts. The annotated dataset was used to reconstruct and verify each BQM process and to develop a harmonized BQM process model. A survey was conducted to evaluate the face and content validity of this harmonized model. The harmonized process model is hierarchical, encompassing tasks, activities, and steps. The face validity evaluation concluded the model to be representative of the BQM process. In the content validity evaluation, out of the 27 tasks for BQM, 19 meet the threshold for semi-valid, including 3 fully valid: "Identify potential index phenotype," "If needed, request EHR database access rights," and "Perform query and present output to medical researcher", and 8 are invalid. We aligned the goals of the tasks within the BQM model with the five components of the reference interview. The similarity between the process of BQM and the reference interview is promising and suggests the BQM tasks are powerful for eliciting implicit information needs. We contribute a BQM process model based on a multi-site study. This model promises to inform the standardization of the BQM process towards improved communication efficiency and accuracy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A Multi-Site Cognitive Task Analysis for Biomedical Query Mediation

PubMed Central

Hruby, Gregory W.; Rasmussen, Luke V.; Hanauer, David; Patel, Vimla; Cimino, James J.; Weng, Chunhua

2016-01-01

Objective To apply cognitive task analyses of the Biomedical query mediation (BQM) processes for EHR data retrieval at multiple sites towards the development of a generic BQM process model. Materials and Methods We conducted semi-structured interviews with eleven data analysts from five academic institutions and one government agency, and performed cognitive task analyses on their BQM processes. A coding schema was developed through iterative refinement and used to annotate the interview transcripts. The annotated dataset was used to reconstruct and verify each BQM process and to develop a harmonized BQM process model. A survey was conducted to evaluate the face and content validity of this harmonized model. Results The harmonized process model is hierarchical, encompassing tasks, activities, and steps. The face validity evaluation concluded the model to be representative of the BQM process. In the content validity evaluation, out of the 27 tasks for BQM, 19 meet the threshold for semi-valid, including 3 fully valid: “Identify potential index phenotype,” “If needed, request EHR database access rights,” and “Perform query and present output to medical researcher”, and 8 are invalid. Discussion We aligned the goals of the tasks within the BQM model with the five components of the reference interview. The similarity between the process of BQM and the reference interview is promising and suggests the BQM tasks are powerful for eliciting implicit information needs. Conclusions We contribute a BQM process model based on a multi-site study. This model promises to inform the standardization of the BQM process towards improved communication efficiency and accuracy. PMID:27435950

The Effect of a Learning Environment Using an Electronic Health Record (EHR) on Undergraduate Nursing Students' Behaviorial Intention to Use an EHR

ERIC Educational Resources Information Center

Foley, Shawn

2011-01-01

The purpose of this study was to explore the effect of a learning environment using an Electronic Health Record (EHR) on undergraduate nursing students' behavioral intention (BI) to use an EHR. BI is defined by Davis (1989) in the Technology Acceptance Model (TAM) as the degree to which a person has formulated conscious plans to perform or not…

Same organization, same electronic health records (EHRs) system, different use: exploring the linkage between practice member communication patterns and EHR use patterns in an ambulatory care setting

PubMed Central

Leykum, Luci K; McDaniel, Reuben R

2011-01-01

Objective Despite efforts made by ambulatory care organizations to standardize the use of electronic health records (EHRs), practices often incorporate these systems into their work differently from each other. One potential factor contributing to these differences is within-practice communication patterns. The authors explore the linkage between within-practice communication patterns and practice-level EHR use patterns. Design Qualitative study of six practices operating within the same multi-specialty ambulatory care organization using the same EHR system. Semistructured interviews and direct observation were conducted with all physicians, nurses, medical assistants, practice managers, and non-clinical staff from each practice. Measurements An existing model of practice relationships was used to analyze communication patterns within the practices. Practice-level EHR use was defined and analyzed as the ways in which a practice uses an EHR as a collective or a group—including the degree of feature use, level of EHR-enabled communication, and frequency that EHR use changes in a practice. Interview and observation data were analyzed for themes. Based on these themes, within-practice communication patterns were categorized as fragmented or cohesive, and practice-level EHR use patterns were categorized as heterogeneous or homogeneous. Practices where EHR use was uniformly high across all users were further categorized as having standardized EHR use. Communication patterns and EHR use patterns were compared across the six practices. Results Within-practice communication patterns were associated with practice-level EHR use patterns. In practices where communication patterns were fragmented, EHR use was heterogeneous. In practices where communication patterns were cohesive, EHR use was homogeneous. Additional analysis revealed that practices that had achieved standardized EHR use (uniformly high EHR use across all users) exhibited high levels of mindfulness and respectful interaction, whereas practices that were furthest from achieving standardized EHR use exhibited low levels of mindfulness and respectful interaction. Conclusion Within-practice communication patterns provide a unique perspective for exploring the issue of standardization in EHR use. A major fallacy of setting homogeneous EHR use as the goal for practice-level EHR use is that practices with uniformly low EHR use could be considered successful. Achieving uniformly high EHR use across all users in a practice is more consistent with the goals of current EHR adoption and use efforts. It was found that some communication patterns among practice members may enable more standardized EHR use than others. Understanding the linkage between communication patterns and EHR use can inform understanding of the human element in EHR use and may provide key lessons for the implementation of EHRs and other health information technologies. PMID:21846780

Same organization, same electronic health records (EHRs) system, different use: exploring the linkage between practice member communication patterns and EHR use patterns in an ambulatory care setting.

PubMed

Lanham, Holly Jordan; Leykum, Luci K; McDaniel, Reuben R

2012-01-01

Despite efforts made by ambulatory care organizations to standardize the use of electronic health records (EHRs), practices often incorporate these systems into their work differently from each other. One potential factor contributing to these differences is within-practice communication patterns. The authors explore the linkage between within-practice communication patterns and practice-level EHR use patterns. Qualitative study of six practices operating within the same multi-specialty ambulatory care organization using the same EHR system. Semistructured interviews and direct observation were conducted with all physicians, nurses, medical assistants, practice managers, and non-clinical staff from each practice. An existing model of practice relationships was used to analyze communication patterns within the practices. Practice-level EHR use was defined and analyzed as the ways in which a practice uses an EHR as a collective or a group-including the degree of feature use, level of EHR-enabled communication, and frequency that EHR use changes in a practice. Interview and observation data were analyzed for themes. Based on these themes, within-practice communication patterns were categorized as fragmented or cohesive, and practice-level EHR use patterns were categorized as heterogeneous or homogeneous. Practices where EHR use was uniformly high across all users were further categorized as having standardized EHR use. Communication patterns and EHR use patterns were compared across the six practices. Within-practice communication patterns were associated with practice-level EHR use patterns. In practices where communication patterns were fragmented, EHR use was heterogeneous. In practices where communication patterns were cohesive, EHR use was homogeneous. Additional analysis revealed that practices that had achieved standardized EHR use (uniformly high EHR use across all users) exhibited high levels of mindfulness and respectful interaction, whereas practices that were furthest from achieving standardized EHR use exhibited low levels of mindfulness and respectful interaction. Within-practice communication patterns provide a unique perspective for exploring the issue of standardization in EHR use. A major fallacy of setting homogeneous EHR use as the goal for practice-level EHR use is that practices with uniformly low EHR use could be considered successful. Achieving uniformly high EHR use across all users in a practice is more consistent with the goals of current EHR adoption and use efforts. It was found that some communication patterns among practice members may enable more standardized EHR use than others. Understanding the linkage between communication patterns and EHR use can inform understanding of the human element in EHR use and may provide key lessons for the implementation of EHRs and other health information technologies.

The Data Gap in the EHR for Clinical Research Eligibility Screening.

PubMed

Butler, Alex; Wei, Wei; Yuan, Chi; Kang, Tian; Si, Yuqi; Weng, Chunhua

2018-01-01

Much effort has been devoted to leverage EHR data for matching patients into clinical trials. However, EHRs may not contain all important data elements for clinical research eligibility screening. To better design research-friendly EHRs, an important step is to identify data elements frequently used for eligibility screening but not yet available in EHRs. This study fills this knowledge gap. Using the Alzheimer's disease domain as an example, we performed text mining on the eligibility criteria text in Clinicaltrials.gov to identify frequently used eligibility criteria concepts. We compared them to the EHR data elements of a cohort of Alzheimer's Disease patients to assess the data gap by usingthe OMOP Common Data Model to standardize the representations for both criteria concepts and EHR data elements. We identified the most common SNOMED CT concepts used in Alzheimer 's Disease trials, andfound 40% of common eligibility criteria concepts were not even defined in the concept space in the EHR dataset for a cohort of Alzheimer 'sDisease patients, indicating a significant data gap may impede EHR-based eligibility screening. The results of this study can be useful for designing targeted research data collection forms to help fill the data gap in the EHR.

Applying an Archetype-Based Approach to Electroencephalography/Event-Related Potential Experiments in the EEGBase Resource.

PubMed

Papež, Václav; Mouček, Roman

2017-01-01

The purpose of this study is to investigate the feasibility of applying openEHR (an archetype-based approach for electronic health records representation) to modeling data stored in EEGBase, a portal for experimental electroencephalography/event-related potential (EEG/ERP) data management. The study evaluates re-usage of existing openEHR archetypes and proposes a set of new archetypes together with the openEHR templates covering the domain. The main goals of the study are to (i) link existing EEGBase data/metadata and openEHR archetype structures and (ii) propose a new openEHR archetype set describing the EEG/ERP domain since this set of archetypes currently does not exist in public repositories. The main methodology is based on the determination of the concepts obtained from EEGBase experimental data and metadata that are expressible structurally by the openEHR reference model and semantically by openEHR archetypes. In addition, templates as the third openEHR resource allow us to define constraints over archetypes. Clinical Knowledge Manager (CKM), a public openEHR archetype repository, was searched for the archetypes matching the determined concepts. According to the search results, the archetypes already existing in CKM were applied and the archetypes not existing in the CKM were newly developed. openEHR archetypes support linkage to external terminologies. To increase semantic interoperability of the new archetypes, binding with the existing odML electrophysiological terminology was assured. Further, to increase structural interoperability, also other current solutions besides EEGBase were considered during the development phase. Finally, a set of templates using the selected archetypes was created to meet EEGBase requirements. A set of eleven archetypes that encompassed the domain of experimental EEG/ERP measurements were identified. Of these, six were reused without changes, one was extended, and four were newly created. All archetypes were arranged in the templates reflecting the EEGBase metadata structure. A mechanism of odML terminology referencing was proposed to assure semantic interoperability of the archetypes. The openEHR approach was found to be useful not only for clinical purposes but also for experimental data modeling.

The impact of electronic health record use on physician productivity.

PubMed

Adler-Milstein, Julia; Huckman, Robert S

2013-11-01

To examine the impact of the degree of electronic health record (EHR) use and delegation of EHR tasks on clinician productivity in ambulatory settings. We examined EHR use in primary care practices that implemented a web-based EHR from athenahealth (n = 42) over 3 years (695 practice-month observations). Practices were predominantly small and spread throughout the country. Data came from athenahealth practice management system and EHR task logs. We developed monthly measures of EHR use and delegation to support staff from task logs. Productivity was measured using work relative value units (RVUs). Using fixed effects models, we assessed the independent impacts on productivity of EHR use and delegation. We then explored the interaction between these 2 strategies and the role of practice size. Greater EHR use and greater delegation were independently associated with higher levels of productivity. An increase in EHR use of 1 standard deviation resulted in a 5.3% increase in RVUs per clinician workday; an increase in delegation of EHR tasks of 1 standard deviation resulted in an 11.0% increase in RVUs per clinician workday (P <.05 for both). Further, EHR use and delegation had a positive joint impact on productivity in large practices (coefficient, 0.058; P <.05), but a negative joint impact on productivity in small practices (coefficient, -0.142; P <.01). Clinicians in practices that increased EHR use and delegated EHR tasks were more productive, but practice size determined whether the 2 strategies were complements or substitutes.

Estimating Wisconsin Asthma Prevalence Using Clinical Electronic Health Records and Public Health Data

PubMed Central

Tomasallo, Carrie D.; Hanrahan, Lawrence P.; Tandias, Aman; Chang, Timothy S.; Cowan, Kelly J.

2014-01-01

Objectives. We compared a statewide telephone health survey with electronic health record (EHR) data from a large Wisconsin health system to estimate asthma prevalence in Wisconsin. Methods. We developed frequency tables and logistic regression models using Wisconsin Behavioral Risk Factor Surveillance System and University of Wisconsin primary care clinic data. We compared adjusted odds ratios (AORs) from each model. Results. Between 2007 and 2009, the EHR database contained 376 000 patients (30 000 with asthma), and 23 000 (1850 with asthma) responded to the Behavioral Risk Factor Surveillance System telephone survey. AORs for asthma were similar in magnitude and direction for the majority of covariates, including gender, age, and race/ethnicity, between survey and EHR models. The EHR data had greater statistical power to detect associations than did survey data, especially in pediatric and ethnic populations, because of larger sample sizes. Conclusions. EHRs can be used to estimate asthma prevalence in Wisconsin adults and children. EHR data may improve public health chronic disease surveillance using high-quality data at the local level to better identify areas of disparity and risk factors and guide education and health care interventions. PMID:24228643

Making Electronic Health Records (EHRs) Work: Informal Talk and Workarounds in Healthcare Organizations.

PubMed

Barrett, Ashley K; Stephens, Keri K

2017-08-01

A key provision of the American Recovery and Reinvestment Act of 2009 mandated that electronic health records (EHR) be adopted in US healthcare organizations by 2015. The purpose of this study is to examine the communicative processes involved as healthcare workers implement an EHR and make changes, known as workarounds. Guided by theories in social influence, and diffusion of innovations, we conducted a survey of healthcare professionals using an EHR system in an organization. Our structural equation modeling (SEM) and multiple regression results reveal coworker communication, in the form of informal social support and feedback, play an important role in whether people engage in workarounds. Understanding this relationship is important because our study also demonstrates that workarounds predict healthcare employees' overall satisfaction with the EHR system. Specifically, workarounds are associated with higher perceptions of the EHR's relative advantage, higher perceptions of EHR implementation success, and lower levels of resistance to EHR change. This study offers a health communication contribution to the growing research on EHR systems and demonstrates the persuasive effects that coworkers have on new technology use in healthcare organizations.

Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems

PubMed Central

Sittig, Dean F; Ash, Joan S; Feblowitz, Joshua; Meltzer, Seth; McMullen, Carmit; Guappone, Ken; Carpenter, Jim; Richardson, Joshua; Simonaitis, Linas; Evans, R Scott; Nichol, W Paul; Middleton, Blackford

2011-01-01

Background Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. Objective To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs. Study design and methods We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4). Results Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common. Conclusion We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content. PMID:21415065

Modelling of Operative Report Documents for Data Integration into an openEHR-Based Enterprise Data Warehouse.

PubMed

Haarbrandt, Birger; Wilschko, Andreas; Marschollek, Michael

2016-01-01

In order to integrate operative report documents from two operating room management systems into a data warehouse, we investigated the application of the two-level modelling approach of openEHR to create a shared data model. Based on the systems' analyses, a template consisting of 13 archetypes has been developed. Of these 13 archetypes, 3 have been obtained from the international archetype repository of the openEHR foundation. The remaining 10 archetypes have been newly created. The template was evaluated by an application system expert and through conducting a first test mapping of real-world data from one of the systems. The evaluation showed that by using the two-level modelling approach of openEHR, we succeeded to represent an integrated and shared information model for operative report documents. More research is needed to learn about the limitations of this approach in other data integration scenarios.

Comparison of EHR-based diagnosis documentation locations to a gold standard for risk stratification in patients with multiple chronic conditions.

PubMed

Martin, Shelby; Wagner, Jesse; Lupulescu-Mann, Nicoleta; Ramsey, Katrina; Cohen, Aaron; Graven, Peter; Weiskopf, Nicole G; Dorr, David A

2017-08-02

To measure variation among four different Electronic Health Record (EHR) system documentation locations versus 'gold standard' manual chart review for risk stratification in patients with multiple chronic illnesses. Adults seen in primary care with EHR evidence of at least one of 13 conditions were included. EHRs were manually reviewed to determine presence of active diagnoses, and risk scores were calculated using three different methodologies and five EHR documentation locations. Claims data were used to assess cost and utilization for the following year. Descriptive and diagnostic statistics were calculated for each EHR location. Criterion validity testing compared the gold standard verified diagnoses versus other EHR locations and risk scores in predicting future cost and utilization. Nine hundred patients had 2,179 probable diagnoses. About 70% of the diagnoses from the EHR were verified by gold standard. For a subset of patients having baseline and prediction year data (n=750), modeling showed that the gold standard was the best predictor of outcomes on average for a subset of patients that had these data. However, combining all data sources together had nearly equivalent performance for prediction as the gold standard. EHR data locations were inaccurate 30% of the time, leading to improvement in overall modeling from a gold standard from chart review for individual diagnoses. However, the impact on identification of the highest risk patients was minor, and combining data from different EHR locations was equivalent to gold standard performance. The reviewer's ability to identify a diagnosis as correct was influenced by a variety of factors, including completeness, temporality, and perceived accuracy of chart data.

Factors associated with adoption of health information technology: a conceptual model based on a systematic review.

PubMed

Kruse, Clemens Scott; DeShazo, Jonathan; Kim, Forest; Fulton, Lawrence

2014-05-23

The Health Information Technology for Economic and Clinical Health Act (HITECH) allocated $19.2 billion to incentivize adoption of the electronic health record (EHR). Since 2009, Meaningful Use Criteria have dominated information technology (IT) strategy. Health care organizations have struggled to meet expectations and avoid penalties to reimbursements from the Center for Medicare and Medicaid Services (CMS). Organizational theories attempt to explain factors that influence organizational change, and many theories address changes in organizational strategy. However, due to the complexities of the health care industry, existing organizational theories fall short of demonstrating association with significant health care IT implementations. There is no organizational theory for health care that identifies, groups, and analyzes both internal and external factors of influence for large health care IT implementations like adoption of the EHR. The purpose of this systematic review is to identify a full-spectrum of both internal organizational and external environmental factors associated with the adoption of health information technology (HIT), specifically the EHR. The result is a conceptual model that is commensurate with the complexity of with the health care sector. We performed a systematic literature search in PubMed (restricted to English), EBSCO Host, and Google Scholar for both empirical studies and theory-based writing from 1993-2013 that demonstrated association between influential factors and three modes of HIT: EHR, electronic medical record (EMR), and computerized provider order entry (CPOE). We also looked at published books on organizational theories. We made notes and noted trends on adoption factors. These factors were grouped as adoption factors associated with various versions of EHR adoption. The resulting conceptual model summarizes the diversity of independent variables (IVs) and dependent variables (DVs) used in articles, editorials, books, as well as quantitative and qualitative studies (n=83). As of 2009, only 16.30% (815/4999) of nonfederal, acute-care hospitals had adopted a fully interoperable EHR. From the 83 articles reviewed in this study, 16/83 (19%) identified internal organizational factors and 9/83 (11%) identified external environmental factors associated with adoption of the EHR, EMR, or CPOE. The conceptual model for EHR adoption associates each variable with the work that identified it. Commonalities exist in the literature for internal organizational and external environmental factors associated with the adoption of the EHR and/or CPOE. The conceptual model for EHR adoption associates internal and external factors, specific to the health care industry, associated with adoption of the EHR. It becomes apparent that these factors have some level of association, but the association is not consistently calculated individually or in combination. To better understand effective adoption strategies, empirical studies should be performed from this conceptual model to quantify the positive or negative effect of each factor.

Evaluation of a Hyperlinked Consumer Health Dictionary for reading EHR notes.

PubMed

Slaughter, Laura; Oyri, Karl; Fosse, Erik

2011-01-01

In this paper, we report on a pilot study conducted to test the usefulness and understandability of definitions in a Consumer Health Dictionary (IVS-CHD). Our two main goals for this study were to evaluate functionality of the dictionary when embedded in electronic health records (EHR) and determine the methodology for our larger-scale project to iteratively develop the IVS-CHD. The hyperlinked IVS-CHD was made available to thoracic surgery patients reading their own EHR. We asked patients to rate definitions on two 5-level Likert items measuring perceived usefulness and understandability. We also captured the terms that patients wanted defined, but that were not included in the IVS-CHD. Preliminary results indicate the types of problems that must be avoided when creating definitions, for example, that patients prefer detailed explanations that include medical outcomes, and that do not use "unfamiliar" terms they must also look up. We also have gained insight into the types of terms that patients want defined from their EHR notes, especially certain abbreviations. Patients further commented on the experience of reading EHR notes directly from the same system used by healthcare personnel and the help strategy of linking the contents to a hyperlinked dictionary.

Barriers and facilitators to electronic documentation in a rural hospital.

PubMed

Whittaker, Alice A; Aufdenkamp, Marilee; Tinley, Susan

2009-01-01

The purpose of the study was to explore nurses' perceptions of barriers and facilitators to adoption of an electronic health record (EHR) in a rural Midwestern hospital. This study was a qualitative, descriptive design. The Staggers and Parks Nurse-Computer Interaction Framework was used to guide directed content analysis. Eleven registered nurses from oncology and medical-surgical units were interviewed using three semistructured interview questions. Predetermined codes and operational definitions were developed from the Staggers and Parks framework. Narrative data were analyzed by each member of the research team and group consensus on coding was reached through group discussions. Participants were able to identify computer-related, nurse-related, and contextual barriers and facilitators to implementation of EHR. In addition, two distinct patterns of perceptions and acceptance were identified. The Staggers and Parks Nurse-Computer Interaction framework was found to be useful in identifying computer, nurse, and contextual characteristics that act as facilitators or barriers to adoption of an EHR system. Acceptance and use of an EHR are enhanced when barriers are managed and facilitators are supported. Understanding and management of facilitators and barriers to EHR adoption may impact nurses' ability to provide and document nursing care.

Comparison of methodologies for calculating quality measures based on administrative data versus clinical data from an electronic health record system: implications for performance measures.

PubMed

Tang, Paul C; Ralston, Mary; Arrigotti, Michelle Fernandez; Qureshi, Lubna; Graham, Justin

2007-01-01

New reimbursement policies and pay-for-performance programs to reward providers for producing better outcomes are proliferating. Although electronic health record (EHR) systems could provide essential clinical data upon which to base quality measures, most metrics in use were derived from administrative claims data. We compared commonly used quality measures calculated from administrative data to those derived from clinical data in an EHR based on a random sample of 125 charts of Medicare patients with diabetes. Using standard definitions based on administrative data (which require two visits with an encounter diagnosis of diabetes during the measurement period), only 75% of diabetics determined by manually reviewing the EHR (the gold standard) were identified. In contrast, 97% of diabetics were identified using coded information in the EHR. The discrepancies in identified patients resulted in statistically significant differences in the quality measures for frequency of HbA1c testing, control of blood pressure, frequency of testing for urine protein, and frequency of eye exams for diabetic patients. New development of standardized quality measures should shift from claims-based measures to clinically based measures that can be derived from coded information in an EHR. Using data from EHRs will also leverage their clinical content without adding burden to the care process.

Impacts of structuring the electronic health record: Results of a systematic literature review from the perspective of secondary use of patient data.

PubMed

Vuokko, Riikka; Mäkelä-Bengs, Päivi; Hyppönen, Hannele; Lindqvist, Minna; Doupi, Persephone

2017-01-01

To explore the impacts that structuring of electronic health records (EHRs) has had from the perspective of secondary use of patient data as reflected in currently published literature. This paper presents the results of a systematic literature review aimed at answering the following questions; (1) what are the common methods of structuring patient data to serve secondary use purposes; (2) what are the common methods of evaluating patient data structuring in the secondary use context, and (3) what impacts or outcomes of EHR structuring have been reported from the secondary use perspective. The reported study forms part of a wider systematic literature review on the impacts of EHR structuring methods and evaluations of their impact. The review was based on a 12-step systematic review protocol adapted from the Cochrane methodology. Original articles included in the study were divided into three groups for analysis and reporting based on their use focus: nursing documentation, medical use and secondary use (presented in this paper). The analysis from the perspective of secondary use of data includes 85 original articles from 1975 to 2010 retrieved from 15 bibliographic databases. The implementation of structured EHRs can be roughly divided into applications for documenting patient data at the point of care and application for retrieval of patient data (post hoc structuring). Two thirds of the secondary use articles concern EHR structuring methods which were still under development or in the testing phase. of structuring patient data such as codes, terminologies, reference information models, forms or templates and documentation standards were usually applied in combination. Most of the identified benefits of utilizing structured EHR data for secondary use purposes concentrated on information content and quality or on technical quality and reliability, particularly in the case of Natural Language Processing (NLP) studies. A few individual articles evaluated impacts on care processes, productivity and costs, patient safety, care quality or other health impacts. In most articles these endpoints were usually discussed as goals of secondary use and less as evidence-supported impacts, resulting from the use of structured EHR data for secondary purposes. Further studies and more sound evaluation methods are needed for evidence on how EHRs are utilized for secondary purposes, and how structured documentation methods can serve different users' needs, e.g. administration, statistics and research and development, in parallel to medical use purposes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A model-driven approach for representing clinical archetypes for Semantic Web environments.

PubMed

Martínez-Costa, Catalina; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás; Maldonado, José Alberto

2009-02-01

The life-long clinical information of any person supported by electronic means configures his Electronic Health Record (EHR). This information is usually distributed among several independent and heterogeneous systems that may be syntactically or semantically incompatible. There are currently different standards for representing and exchanging EHR information among different systems. In advanced EHR approaches, clinical information is represented by means of archetypes. Most of these approaches use the Archetype Definition Language (ADL) to specify archetypes. However, ADL has some drawbacks when attempting to perform semantic activities in Semantic Web environments. In this work, Semantic Web technologies are used to specify clinical archetypes for advanced EHR architectures. The advantages of using the Ontology Web Language (OWL) instead of ADL are described and discussed in this work. Moreover, a solution combining Semantic Web and Model-driven Engineering technologies is proposed to transform ADL into OWL for the CEN EN13606 EHR architecture.

Assessing the impact of electronic health records as an enabler of hospital quality and patient satisfaction.

PubMed

Jarvis, Benjamin; Johnson, Tricia; Butler, Peter; O'Shaughnessy, Kathryn; Fullam, Francis; Tran, Lac; Gupta, Richa

2013-10-01

To assess the impact of using an advanced electronic health record (EHR) on hospital quality and patient satisfaction. This retrospective, cross-sectional analysis was conducted in 2012 to evaluate the association between advanced EHR use (Healthcare Information Management Systems Society [HIMSS] Stage 6 or 7 as of December 2012) and estimated process and experience of care scores for hospitals under the Medicare Hospital Value-Based Purchasing Program, using data from the American Hospital Association for 2008 to 2010. Generalized linear regression models were fit to test the association between advanced EHR use with process of care and experience of care, controlling for hospital characteristics. In a second analysis, the models included variables to account for HIMSS stage of advanced EHR use. The study included 2,988 hospitals, with 248 (8.3%) classified as advanced EHR users (HIMSS Stage 6 or 7). After controlling for hospital characteristics, advanced EHR use was associated with a 4.2-point-higher process of care score (P < .001). Hospitals with Stage 7 EHRs had 11.7 points higher process of care scores, but Stage 6 users had scores that were not substantially different from those of nonadvanced users. There was no significant difference in estimated experience of care scores by level of advanced EHR use. This study evaluated the effectiveness of the U.S. federal government's investment in hospital information technology infrastructure. Results suggest that the most advanced EHRs have the greatest payoff in improving clinical process of care scores, without detrimentally impacting the patient experience.

Congruency between educators' teaching beliefs and an electronic health record teaching strategy.

PubMed

Bani-issa, Wegdan; Rempusheski, Veronica F

2014-06-01

Technology has changed healthcare institutions into automated settings with the potential to greatly enhance the quality of healthcare. Implementation of electronic health records (EHRs) to replace paper charting is one example of the influence of technology on healthcare worldwide. In the past decade nursing higher education has attempted to keep pace with technological changes by integrating EHRs into learning experiences. Little is known about educators' teaching beliefs and the use of EHRs as a teaching strategy. This study explores the composition of core teaching beliefs of nurse educators and their related teaching practices within the context of teaching with EHRs in the classroom. A collective case study and qualitative research approach was used to explore and describe teaching beliefs of seven nurse educators teaching with EHRs. Data collection included open-ended, audio-taped interviews and non-participant observation. Content analysis of transcribed interviews and observational field notes focused on identification of teaching belief themes and associated practices. Two contrasting collective case studies of teaching beliefs emerged. Constructivist beliefs were dominant, focused on experiential, student-centered, contextual and collaborative learning, and associated with expanded and a futuristic view of EHRs use. Objectivist beliefs focused on educators' control of the context of learning and were associated with a constrained, limited view of EHRs. Constructivist educators embrace technological change, an essential ingredient of educational reform. We encourage nurse educators to adopt a constructivist view to using technology in teaching in order to prepare nurses for a rapidly changing, technologically sophisticated practice. Copyright © 2014 Elsevier Ltd. All rights reserved.

EHR standards--A comparative study.

PubMed

Blobel, Bernd; Pharow, Peter

2006-01-01

For ensuring quality and efficiency of patient's care, the care paradigm moves from organization-centered over process-controlled towards personal care. Such health system paradigm change leads to new paradigms for analyzing, designing, implementing and deploying supporting health information systems including EHR systems as core application in a distributed eHealth environment. The paper defines the architectural paradigm for future-proof EHR systems. It compares advanced EHR architectures referencing them at the Generic Component Model. The paper introduces the evolving paradigm of autonomous computing for self-organizing health information systems.

Rapid Development of Specialty Population Registries and Quality Measures from Electronic Health Record Data*. An Agile Framework.

PubMed

Kannan, Vaishnavi; Fish, Jason S; Mutz, Jacqueline M; Carrington, Angela R; Lai, Ki; Davis, Lisa S; Youngblood, Josh E; Rauschuber, Mark R; Flores, Kathryn A; Sara, Evan J; Bhat, Deepa G; Willett, DuWayne L

2017-06-14

Creation of a new electronic health record (EHR)-based registry often can be a "one-off" complex endeavor: first developing new EHR data collection and clinical decision support tools, followed by developing registry-specific data extractions from the EHR for analysis. Each development phase typically has its own long development and testing time, leading to a prolonged overall cycle time for delivering one functioning registry with companion reporting into production. The next registry request then starts from scratch. Such an approach will not scale to meet the emerging demand for specialty registries to support population health and value-based care. To determine if the creation of EHR-based specialty registries could be markedly accelerated by employing (a) a finite core set of EHR data collection principles and methods, (b) concurrent engineering of data extraction and data warehouse design using a common dimensional data model for all registries, and (c) agile development methods commonly employed in new product development. We adopted as guiding principles to (a) capture data as a byproduct of care of the patient, (b) reinforce optimal EHR use by clinicians, (c) employ a finite but robust set of EHR data capture tool types, and (d) leverage our existing technology toolkit. Registries were defined by a shared condition (recorded on the Problem List) or a shared exposure to a procedure (recorded on the Surgical History) or to a medication (recorded on the Medication List). Any EHR fields needed - either to determine registry membership or to calculate a registry-associated clinical quality measure (CQM) - were included in the enterprise data warehouse (EDW) shared dimensional data model. Extract-transform-load (ETL) code was written to pull data at defined "grains" from the EHR into the EDW model. All calculated CQM values were stored in a single Fact table in the EDW crossing all registries. Registry-specific dashboards were created in the EHR to display both (a) real-time patient lists of registry patients and (b) EDW-generated CQM data. Agile project management methods were employed, including co-development, lightweight requirements documentation with User Stories and acceptance criteria, and time-boxed iterative development of EHR features in 2-week "sprints" for rapid-cycle feedback and refinement. Using this approach, in calendar year 2015 we developed a total of 43 specialty chronic disease registries, with 111 new EHR data collection and clinical decision support tools, 163 new clinical quality measures, and 30 clinic-specific dashboards reporting on both real-time patient care gaps and summarized and vetted CQM measure performance trends. This study suggests concurrent design of EHR data collection tools and reporting can quickly yield useful EHR structured data for chronic disease registries, and bodes well for efforts to migrate away from manual abstraction. This work also supports the view that in new EHR-based registry development, as in new product development, adopting agile principles and practices can help deliver valued, high-quality features early and often.

Rapid Development of Specialty Population Registries and Quality Measures from Electronic Health Record Data.

PubMed

Kannan, Vaishnavi; Fish, Jason S; Mutz, Jacqueline M; Carrington, Angela R; Lai, Ki; Davis, Lisa S; Youngblood, Josh E; Rauschuber, Mark R; Flores, Kathryn A; Sara, Evan J; Bhat, Deepa G; Willett, DuWayne L

2017-01-01

Creation of a new electronic health record (EHR)-based registry often can be a "one-off" complex endeavor: first developing new EHR data collection and clinical decision support tools, followed by developing registry-specific data extractions from the EHR for analysis. Each development phase typically has its own long development and testing time, leading to a prolonged overall cycle time for delivering one functioning registry with companion reporting into production. The next registry request then starts from scratch. Such an approach will not scale to meet the emerging demand for specialty registries to support population health and value-based care. To determine if the creation of EHR-based specialty registries could be markedly accelerated by employing (a) a finite core set of EHR data collection principles and methods, (b) concurrent engineering of data extraction and data warehouse design using a common dimensional data model for all registries, and (c) agile development methods commonly employed in new product development. We adopted as guiding principles to (a) capture data as a byproduct of care of the patient, (b) reinforce optimal EHR use by clinicians, (c) employ a finite but robust set of EHR data capture tool types, and (d) leverage our existing technology toolkit. Registries were defined by a shared condition (recorded on the Problem List) or a shared exposure to a procedure (recorded on the Surgical History) or to a medication (recorded on the Medication List). Any EHR fields needed - either to determine registry membership or to calculate a registry-associated clinical quality measure (CQM) - were included in the enterprise data warehouse (EDW) shared dimensional data model. Extract-transform-load (ETL) code was written to pull data at defined "grains" from the EHR into the EDW model. All calculated CQM values were stored in a single Fact table in the EDW crossing all registries. Registry-specific dashboards were created in the EHR to display both (a) real-time patient lists of registry patients and (b) EDW-gener-ated CQM data. Agile project management methods were employed, including co-development, lightweight requirements documentation with User Stories and acceptance criteria, and time-boxed iterative development of EHR features in 2-week "sprints" for rapid-cycle feedback and refinement. Using this approach, in calendar year 2015 we developed a total of 43 specialty chronic disease registries, with 111 new EHR data collection and clinical decision support tools, 163 new clinical quality measures, and 30 clinic-specific dashboards reporting on both real-time patient care gaps and summarized and vetted CQM measure performance trends. This study suggests concurrent design of EHR data collection tools and reporting can quickly yield useful EHR structured data for chronic disease registries, and bodes well for efforts to migrate away from manual abstraction. This work also supports the view that in new EHR-based registry development, as in new product development, adopting agile principles and practices can help deliver valued, high-quality features early and often. Schattauer GmbH.

Developing an Interface to Order and Document Health Education Videos in the Electronic Health Record.

PubMed

Wojcik, Lauren

2015-01-01

Transitioning to electronic health records (EHRs) provides an opportunity for health care systems to integrate educational content available on interactive patient systems (IPS) with the medical documentation system. This column discusses how one hospital simplified providers' workflow by making it easier to order educational videos and ensure that completed education is documented within the medical record. Integrating the EHR and IPS streamlined the provision of patient education, improved documentation, and supported the organization in meeting core requirements for Meaningful Use.

Building a reference functional model for EHR systems.

PubMed

Sumita, Yuki; Takata, Mami; Ishitsuka, Keiju; Tominaga, Yasuyuki; Ohe, Kazuhiko

2007-09-01

Our aim was to develop a reference functional model for electric health record systems (RFM). Such a RFM is built from functions using functional descriptive elements (FDEs) and represents the static relationships between them. This paper presents a new format for describing electric health record (EHR) system functions. Questionnaire and field interview survey was conducted in five hospitals in Japan and one in the USA, to collect data on EHR system functions. Based on survey results, a reference functional list (RFL) was created, in which each EHR system function was listed and divided into 13 FDE types. By analyzing the RFL, we built the meta-functional model and the functional model using UML class diagrams. The former defines language for expressing the functional model, while the latter represents functions, FDEs and their static relationships. A total of 385 functions were represented in the RFL. Six patterns were found for the relationships between functions. The meta-functional model was created as a new format for describing functions. Examples of the functional model, which included the six patterns in the relationships between functions and 11 verbs, were created. We present the meta-functional model, which is a new description format for the functional structure and relationships. Although a more detailed description is required to apply the RFM to the semiautomatic generation of functional specification documents, our RFM can visualize functional structures and functional relationships, classify functions using multiple axes and identify the similarities and differences between functions. The RFM will promote not only the standardization of EHR systems, but also communications between system developers and healthcare providers in the EHR system-design processes. 2006 Elsevier Ireland Ltd

Mapping a Nursing Terminology Subset to openEHR Archetypes. A Case Study of the International Classification for Nursing Practice.

PubMed

Nogueira, J R M; Cook, T W; Cavalini, L T

2015-01-01

Healthcare information technologies have the potential to transform nursing care. However, healthcare information systems based on conventional software architecture are not semantically interoperable and have high maintenance costs. Health informatics standards, such as controlled terminologies, have been proposed to improve healthcare information systems, but their implementation in conventional software has not been enough to overcome the current challenge. Such obstacles could be removed by adopting a multilevel model-driven approach, such as the openEHR specifications, in nursing information systems. To create an openEHR archetype model for the Functional Status concepts as published in Nursing Outcome Indicators Catalog of the International Classification for Nursing Practice (NOIC-ICNP). Four methodological steps were followed: 1) extraction of terms from the NOIC-ICNP terminology; 2) identification of previously published openEHR archetypes; 3) assessment of the adequacy of those openEHR archetypes to represent the terms; and 4) development of new openEHR archetypes when required. The "Barthel Index" archetype was retrieved and mapped to the 68 NOIC-ICNP Functional Status terms. There were 19 exact matches between a term and the correspondent archetype node and 23 archetype nodes that matched to one or more NOIC-INCP. No matches were found between the archetype and 14 of the NOIC-ICNP terms, and nine archetype nodes did not match any of the NOIC-ICNP terms. The openEHR model was sufficient to represent the semantics of the Functional Status concept according to the NOIC-ICNP, but there were differences in data granularity between the terminology and the archetype, thus producing a significantly complex mapping, which could be difficult to implement in real healthcare information systems. However, despite the technological complexity, the present study demonstrated the feasibility of mapping nursing terminologies to openEHR archetypes, which emphasizes the importance of adopting the multilevel model-driven approach for the achievement of semantic interoperability between healthcare information systems.

Practical Considerations for Implementing Genomic Information Resources

PubMed Central

Overby, Casey L.; Connolly, John; Chute, Christopher G.; Denny, Joshua C.; Freimuth, Robert R.; Hartzler, Andrea L.; Holm, Ingrid A.; Manzi, Shannon; Pathak, Jyotishman; Peissig, Peggy L.; Smith, Maureen; Williams, Marc S.; Shirts, Brian H.; Stoffel, Elena M.; Tarczy-Hornoch, Peter; Vitek, Carolyn R. Rohrer; Wolf, Wendy A.; Starren, Justin

2016-01-01

Summary Objectives To understand opinions and perceptions on the state of information resources specifically targeted to genomics, and approaches to delivery in clinical practice. Methods We conducted a survey of genomic content use and its clinical delivery from representatives across eight institutions in the electronic Medical Records and Genomics (eMERGE) network and two institutions in the Clinical Sequencing Exploratory Research (CSER) consortium in 2014. Results Eleven responses representing distinct projects across ten sites showed heterogeneity in how content is being delivered, with provider-facing content primarily delivered via the electronic health record (EHR) (n=10), and paper/pamphlets as the leading mode for patient-facing content (n=9). There was general agreement (91%) that new content is needed for patients and providers specific to genomics, and that while aspects of this content could be shared across institutions there remain site-specific needs (73% in agreement). Conclusion This work identifies a need for the improved access to and expansion of information resources to support genomic medicine, and opportunities for content developers and EHR vendors to partner with institutions to develop needed resources, and streamline their use – such as a central content site in multiple modalities while implementing approaches to allow for site-specific customization. PMID:27652374

Implementation of workflow engine technology to deliver basic clinical decision support functionality.

PubMed

Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

2011-04-10

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.

Development of a Hospital Outcome Measure Intended for Use With Electronic Health Records: 30-Day Risk-standardized Mortality After Acute Myocardial Infarction.

PubMed

McNamara, Robert L; Wang, Yongfei; Partovian, Chohreh; Montague, Julia; Mody, Purav; Eddy, Elizabeth; Krumholz, Harlan M; Bernheim, Susannah M

2015-09-01

Electronic health records (EHRs) offer the opportunity to transform quality improvement by using clinical data for comparing hospital performance without the burden of chart abstraction. However, current performance measures using EHRs are lacking. With support from the Centers for Medicare & Medicaid Services (CMS), we developed an outcome measure of hospital risk-standardized 30-day mortality rates for patients with acute myocardial infarction for use with EHR data. As no appropriate source of EHR data are currently available, we merged clinical registry data from the Action Registry-Get With The Guidelines with claims data from CMS to develop the risk model (2009 data for development, 2010 data for validation). We selected candidate variables that could be feasibly extracted from current EHRs and do not require changes to standard clinical practice or data collection. We used logistic regression with stepwise selection and bootstrapping simulation for model development. The final risk model included 5 variables available on presentation: age, heart rate, systolic blood pressure, troponin ratio, and creatinine level. The area under the receiver operating characteristic curve was 0.78. Hospital risk-standardized mortality rates ranged from 9.6% to 13.1%, with a median of 10.7%. The odds of mortality for a high-mortality hospital (+1 SD) were 1.37 times those for a low-mortality hospital (-1 SD). This measure represents the first outcome measure endorsed by the National Quality Forum for public reporting of hospital quality based on clinical data in the EHR. By being compatible with current clinical practice and existing EHR systems, this measure is a model for future quality improvement measures.

-Omic and Electronic Health Record Big Data Analytics for Precision Medicine.

PubMed

Wu, Po-Yen; Cheng, Chih-Wen; Kaddi, Chanchala D; Venugopalan, Janani; Hoffman, Ryan; Wang, May D

2017-02-01

Rapid advances of high-throughput technologies and wide adoption of electronic health records (EHRs) have led to fast accumulation of -omic and EHR data. These voluminous complex data contain abundant information for precision medicine, and big data analytics can extract such knowledge to improve the quality of healthcare. In this paper, we present -omic and EHR data characteristics, associated challenges, and data analytics including data preprocessing, mining, and modeling. To demonstrate how big data analytics enables precision medicine, we provide two case studies, including identifying disease biomarkers from multi-omic data and incorporating -omic information into EHR. Big data analytics is able to address -omic and EHR data challenges for paradigm shift toward precision medicine. Big data analytics makes sense of -omic and EHR data to improve healthcare outcome. It has long lasting societal impact.

Provider and patient satisfaction with the integration of ambulatory and hospital EHR systems.

PubMed

Meyerhoefer, Chad D; Sherer, Susan A; Deily, Mary E; Chou, Shin-Yi; Guo, Xiaohui; Chen, Jie; Sheinberg, Michael; Levick, Donald

2018-05-16

The installation of EHR systems can disrupt operations at clinical practice sites, but also lead to improvements in information availability. We examined how the installation of an ambulatory EHR at OB/GYN practices and its subsequent interface with an inpatient perinatal EHR affected providers' satisfaction with the transmission of clinical information and patients' ratings of their care experience. We collected data on provider satisfaction through 4 survey rounds during the phased implementation of the EHR. Data on patient satisfaction were drawn from Press Ganey surveys issued by the healthcare network through a standard process. Using multivariable models, we determined how provider satisfaction with information transmission and patient satisfaction with their care experience changed as the EHR system allowed greater information flow between OB/GYN practices and the hospital. Outpatient OB/GYN providers became more satisfied with their access to information from the inpatient perinatal triage unit once system capabilities included automatic data flow from triage back to the OB/GYN offices. Yet physicians were generally less satisfied with how the EHR affected their work processes than other clinical and non-clinical staff. Patient satisfaction dropped after initial EHR installation, and we find no evidence of increased satisfaction linked to system integration. Dissatisfaction of providers with an EHR system and difficulties incorporating EHR technology into patient care may negatively impact patient satisfaction. Care must be taken during EHR implementations to maintain good communication with patients while satisfying documentation requirements.

The business end of health information technology. Can a fully integrated electronic health record increase provider productivity in a large community practice?

PubMed

De Leon, Samantha; Connelly-Flores, Alison; Mostashari, Farzad; Shih, Sarah C

2010-01-01

Electronic health records (EHRs) are expected to transform and improve the way medicine is practiced. However, providers perceive many barriers toward implementing new health information technology. Specifically, they are most concerned about the potentially negative impact on their practice finances and productivity. This study compares the productivity of 75 providers at a large urban primary care practice from January 2005 to February 2009, before and after implementing an EHR system, using longitudinal mixed model analyses. While decreases in productivity were observed at the time the EHR system was implemented, most providers quickly recovered, showing increases in productivity per month shortly after EHR implementation. Overall, providers had significant productivity increases of 1.7% per month per provider from pre- to post-EHR adoption. The majority of the productivity gains occurred after the practice instituted a pay-for-performance program, enabled by the data capture of the EHRs. Coupled with pay-for-performance, EHRs can spur rapid gains in provider productivity.

Openness of patients' reporting with use of electronic records: psychiatric clinicians' views

PubMed Central

Blackford, Jennifer Urbano; Rosenbloom, S Trent; Seidel, Sandra; Clayton, Ellen Wright; Dilts, David M; Finder, Stuart G

2010-01-01

Objectives Improvements in electronic health record (EHR) system development will require an understanding of psychiatric clinicians' views on EHR system acceptability, including effects on psychotherapy communications, data-recording behaviors, data accessibility versus security and privacy, data quality and clarity, communications with medical colleagues, and stigma. Design Multidisciplinary development of a survey instrument targeting psychiatric clinicians who recently switched to EHR system use, focus group testing, data analysis, and data reliability testing. Measurements Survey of 120 university-based, outpatient mental health clinicians, with 56 (47%) responding, conducted 18 months after transition from a paper to an EHR system. Results Factor analysis gave nine item groupings that overlapped strongly with five a priori domains. Respondents both praised and criticized the EHR system. A strong majority (81%) felt that open therapeutic communications were preserved. Regarding data quality, content, and privacy, clinicians (63%) were less willing to record highly confidential information and disagreed (83%) with including their own psychiatric records among routinely accessed EHR systems. Limitations single time point; single academic medical center clinic setting; modest sample size; lack of prior instrument validation; survey conducted in 2005. Conclusions In an academic medical center clinic, the presence of electronic records was not seen as a dramatic impediment to therapeutic communications. Concerns regarding privacy and data security were significant, and may contribute to reluctances to adopt electronic records in other settings. Further study of clinicians' views and use patterns may be helpful in guiding development and deployment of electronic records systems. PMID:20064802

EHR Documentation: The Hype and the Hope for Improving Nursing Satisfaction and Quality Outcomes.

PubMed

OʼBrien, Ann; Weaver, Charlotte; Settergren, Theresa Tess; Hook, Mary L; Ivory, Catherine H

2015-01-01

The phenomenon of "data rich, information poor" in today's electronic health records (EHRs) is too often the reality for nursing. This article proposes the redesign of nursing documentation to leverage EHR data and clinical intelligence tools to support evidence-based, personalized nursing care across the continuum. The principles consider the need to optimize nurses' documentation efficiency while contributing to knowledge generation. The nursing process must be supported by EHRs through integration of best care practices: seamless workflows that display the right tools, evidence-based content, and information at the right time for optimal clinical decision making. Design of EHR documentation must attain a balance that ensures the capture of nursing's impact on safety, quality, highly reliable care, patient engagement, and satisfaction, yet minimizes "death by data entry." In 2014, a group of diverse informatics leaders from practice, academia, and the vendor community formed to address how best to transform electronic documentation to provide knowledge at the point of care and to deliver value to front line nurses and nurse leaders. As our health care system moves toward reimbursement on the basis of quality outcomes and prevention, the value of nursing data in this business proposition will become a key differentiator for health care organizations' economic success.

The International Classification of Functioning, Disability and Health (ICF) in Electronic Health Records. A Systematic Literature Review.

PubMed

Maritz, Roxanne; Aronsky, Dominik; Prodinger, Birgit

2017-09-20

The International Classification of Functioning, Disability and Health (ICF) is the World Health Organization's standard for describing health and health-related states. Examples of how the ICF has been used in Electronic Health Records (EHRs) have not been systematically summarized and described yet. To provide a systematic review of peer-reviewed literature about the ICF's use in EHRs, including related challenges and benefits. Peer-reviewed literature, published between January 2001 and July 2015 was retrieved from Medline ® , CINAHL ® , Scopus ® , and ProQuest ® Social Sciences using search terms related to ICF and EHR concepts. Publications were categorized according to three groups: Requirement specification, development and implementation. Information extraction was conducted according to a qualitative content analysis method, deductively informed by the evaluation framework for Health Information Systems: Human, Organization and Technology-fit (HOT-fit). Of 325 retrieved articles, 17 publications were included; 4 were categorized as requirement specification, 7 as development, and 6 as implementation publications. Information regarding the HOT-fit evaluation framework was summarized. Main benefits of using the ICF in EHRs were its unique comprehensive perspective on health and its interdisciplinary focus. Main challenges included the fact that the ICF is not structured as a formal terminology as well as the need for a reduced number of ICF codes for more feasible and practical use. Different approaches and technical solutions exist for integrating the ICF in EHRs, such as combining the ICF with other existing standards for EHR or selecting ICF codes with natural language processing. Though the use of the ICF in EHRs is beneficial as this review revealed, the ICF could profit from further improvements such as formalizing the knowledge representation in the ICF to support and enhance interoperability.

Rapid Development of Specialty Population Registries and Quality Measures from Electronic Health Record Data: An Agile Framework

PubMed Central

Kannan, V; Fish, JS; Mutz, JM; Carrington, AR; Lai, K; Davis, LS; Youngblood, JE; Rauschuber, MR; Flores, KA; Sara, EJ; Bhat, DG; Willett, DL

2017-01-01

Summary Background Creation of a new electronic health record (EHR)-based registry often can be a "one-off" complex endeavor: first developing new EHR data collection and clinical decision support tools, followed by developing registry-specific data extractions from the EHR for analysis. Each development phase typically has its own long development and testing time, leading to a prolonged overall cycle time for delivering one functioning registry with companion reporting into production. The next registry request then starts from scratch. Such an approach will not scale to meet the emerging demand for specialty registries to support population health and value-based care. Objective To determine if the creation of EHR-based specialty registries could be markedly accelerated by employing (a) a finite core set of EHR data collection principles and methods, (b) concurrent engineering of data extraction and data warehouse design using a common dimensional data model for all registries, and (c) agile development methods commonly employed in new product development. Methods We adopted as guiding principles to (a) capture data as a by product of care of the patient, (b) reinforce optimal EHR use by clinicians, (c) employ a finite but robust set of EHR data capture tool types, and (d) leverage our existing technology toolkit. Registries were defined by a shared condition (recorded on the Problem List) or a shared exposure to a procedure (recorded on the Surgical History) or to a medication (recorded on the Medication List). Any EHR fields needed—either to determine registry membership or to calculate a registry-associated clinical quality measure (CQM)—were included in the enterprise data warehouse (EDW) shared dimensional data model. Extract-transform-load (ETL) code was written to pull data at defined “grains” from the EHR into the EDW model. All calculated CQM values were stored in a single Fact table in the EDW crossing all registries. Registry-specific dashboards were created in the EHR to display both (a) real-time patient lists of registry patients and (b) EDW-generated CQM data. Agile project management methods were employed, including co-development, lightweight requirements documentation with User Stories and acceptance criteria, and time-boxed iterative development of EHR features in 2-week “sprints” for rapid-cycle feedback and refinement. Results Using this approach, in calendar year 2015 we developed a total of 43 specialty chronic disease registries, with 111 new EHR data collection and clinical decision support tools, 163 new clinical quality measures, and 30 clinic-specific dashboards reporting on both real-time patient care gaps and summarized and vetted CQM measure performance trends. Conclusions This study suggests concurrent design of EHR data collection tools and reporting can quickly yield useful EHR structured data for chronic disease registries, and bodes well for efforts to migrate away from manual abstraction. This work also supports the view that in new EHR-based registry development, as in new product development, adopting agile principles and practices can help deliver valued, high-quality features early and often. PMID:28930362

Querying Archetype-Based Electronic Health Records Using Hadoop and Dewey Encoding of openEHR Models.

PubMed

Sundvall, Erik; Wei-Kleiner, Fang; Freire, Sergio M; Lambrix, Patrick

2017-01-01

Archetype-based Electronic Health Record (EHR) systems using generic reference models from e.g. openEHR, ISO 13606 or CIMI should be easy to update and reconfigure with new types (or versions) of data models or entries, ideally with very limited programming or manual database tweaking. Exploratory research (e.g. epidemiology) leading to ad-hoc querying on a population-wide scale can be a challenge in such environments. This publication describes implementation and test of an archetype-aware Dewey encoding optimization that can be used to produce such systems in environments supporting relational operations, e.g. RDBMs and distributed map-reduce frameworks like Hadoop. Initial testing was done using a nine-node 2.2 GHz quad-core Hadoop cluster querying a dataset consisting of targeted extracts from 4+ million real patient EHRs, query results with sub-minute response time were obtained.

-Omic and Electronic Health Records Big Data Analytics for Precision Medicine

PubMed Central

Wu, Po-Yen; Cheng, Chih-Wen; Kaddi, Chanchala D.; Venugopalan, Janani; Hoffman, Ryan; Wang, May D.

2017-01-01

Objective Rapid advances of high-throughput technologies and wide adoption of electronic health records (EHRs) have led to fast accumulation of -omic and EHR data. These voluminous complex data contain abundant information for precision medicine, and big data analytics can extract such knowledge to improve the quality of health care. Methods In this article, we present -omic and EHR data characteristics, associated challenges, and data analytics including data pre-processing, mining, and modeling. Results To demonstrate how big data analytics enables precision medicine, we provide two case studies, including identifying disease biomarkers from multi-omic data and incorporating -omic information into EHR. Conclusion Big data analytics is able to address –omic and EHR data challenges for paradigm shift towards precision medicine. Significance Big data analytics makes sense of –omic and EHR data to improve healthcare outcome. It has long lasting societal impact. PMID:27740470

Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review.

PubMed

Xiao, Cao; Choi, Edward; Sun, Jimeng

2018-06-08

To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their target applications. We also highlight ongoing research and identify open challenges in building deep learning models of EHRs. We searched PubMed and Google Scholar for papers on deep learning studies using EHR data published between January 1, 2010, and January 31, 2018. We summarize them according to these axes: types of analytics tasks, types of deep learning model architectures, special challenges arising from health data and tasks and their potential solutions, as well as evaluation strategies. We surveyed and analyzed multiple aspects of the 98 articles we found and identified the following analytics tasks: disease detection/classification, sequential prediction of clinical events, concept embedding, data augmentation, and EHR data privacy. We then studied how deep architectures were applied to these tasks. We also discussed some special challenges arising from modeling EHR data and reviewed a few popular approaches. Finally, we summarized how performance evaluations were conducted for each task. Despite the early success in using deep learning for health analytics applications, there still exist a number of issues to be addressed. We discuss them in detail including data and label availability, the interpretability and transparency of the model, and ease of deployment.

Electronic Health Record Patient Portal Adoption by Health Care Consumers: An Acceptance Model and Survey.

PubMed

Tavares, Jorge; Oliveira, Tiago

2016-03-02

The future of health care delivery is becoming more citizen centered, as today's user is more active, better informed, and more demanding. Worldwide governments are promoting online health services, such as electronic health record (EHR) patient portals and, as a result, the deployment and use of these services. Overall, this makes the adoption of patient-accessible EHR portals an important field to study and understand. The aim of this study is to understand the factors that drive individuals to adopt EHR portals. We applied a new adoption model using, as a starting point, Ventkatesh's Unified Theory of Acceptance and Use of Technology in a consumer context (UTAUT2) by integrating a new construct specific to health care, a new moderator, and new relationships. To test the research model, we used the partial least squares (PLS) causal modelling approach. An online questionnaire was administrated. We collected 360 valid responses. The statistically significant drivers of behavioral intention are performance expectancy (beta=.200; t=3.619), effort expectancy (beta=.185; t=2.907), habit (beta=.388; t=7.320), and self-perception (beta=.098; t=2.285). The predictors of use behavior are habit (beta=0.206; t=2.752) and behavioral intention (beta=0.258; t=4.036). The model explained 49.7% of the variance in behavioral intention and 26.8% of the variance in use behavior. Our research helps to understand the desired technology characteristics of EHR portals. By testing an information technology acceptance model, we are able to determine what is more valued by patients when it comes to deciding whether to adopt EHR portals or not. The inclusion of specific constructs and relationships related to the health care consumer area also had a significant impact on understanding the adoption of EHR portals.

Relational machine learning for electronic health record-driven phenotyping.

PubMed

Peissig, Peggy L; Santos Costa, Vitor; Caldwell, Michael D; Rottscheit, Carla; Berg, Richard L; Mendonca, Eneida A; Page, David

2014-12-01

Electronic health records (EHR) offer medical and pharmacogenomics research unprecedented opportunities to identify and classify patients at risk. EHRs are collections of highly inter-dependent records that include biological, anatomical, physiological, and behavioral observations. They comprise a patient's clinical phenome, where each patient has thousands of date-stamped records distributed across many relational tables. Development of EHR computer-based phenotyping algorithms require time and medical insight from clinical experts, who most often can only review a small patient subset representative of the total EHR records, to identify phenotype features. In this research we evaluate whether relational machine learning (ML) using inductive logic programming (ILP) can contribute to addressing these issues as a viable approach for EHR-based phenotyping. Two relational learning ILP approaches and three well-known WEKA (Waikato Environment for Knowledge Analysis) implementations of non-relational approaches (PART, J48, and JRIP) were used to develop models for nine phenotypes. International Classification of Diseases, Ninth Revision (ICD-9) coded EHR data were used to select training cohorts for the development of each phenotypic model. Accuracy, precision, recall, F-Measure, and Area Under the Receiver Operating Characteristic (AUROC) curve statistics were measured for each phenotypic model based on independent manually verified test cohorts. A two-sided binomial distribution test (sign test) compared the five ML approaches across phenotypes for statistical significance. We developed an approach to automatically label training examples using ICD-9 diagnosis codes for the ML approaches being evaluated. Nine phenotypic models for each ML approach were evaluated, resulting in better overall model performance in AUROC using ILP when compared to PART (p=0.039), J48 (p=0.003) and JRIP (p=0.003). ILP has the potential to improve phenotyping by independently delivering clinically expert interpretable rules for phenotype definitions, or intuitive phenotypes to assist experts. Relational learning using ILP offers a viable approach to EHR-driven phenotyping. Copyright © 2014 Elsevier Inc. All rights reserved.

Agile Model Driven Development of Electronic Health Record-Based Specialty Population Registries.

PubMed

Kannan, Vaishnavi; Fish, Jason C; Willett, DuWayne L

2016-02-01

The transformation of the American healthcare payment system from fee-for-service to value-based care increasingly makes it valuable to develop patient registries for specialized populations, to better assess healthcare quality and costs. Recent widespread adoption of Electronic Health Records (EHRs) in the U.S. now makes possible construction of EHR-based specialty registry data collection tools and reports, previously unfeasible using manual chart abstraction. But the complexities of specialty registry EHR tools and measures, along with the variety of stakeholders involved, can result in misunderstood requirements and frequent product change requests, as users first experience the tools in their actual clinical workflows. Such requirements churn could easily stall progress in specialty registry rollout. Modeling a system's requirements and solution design can be a powerful way to remove ambiguities, facilitate shared understanding, and help evolve a design to meet newly-discovered needs. "Agile Modeling" retains these values while avoiding excessive unused up-front modeling in favor of iterative incremental modeling. Using Agile Modeling principles and practices, in calendar year 2015 one institution developed 58 EHR-based specialty registries, with 111 new data collection tools, supporting 134 clinical process and outcome measures, and enrolling over 16,000 patients. The subset of UML and non-UML models found most consistently useful in designing, building, and iteratively evolving EHR-based specialty registries included User Stories, Domain Models, Use Case Diagrams, Decision Trees, Graphical User Interface Storyboards, Use Case text descriptions, and Solution Class Diagrams.

Towards successful coordination of electronic health record based-referrals: a qualitative analysis.

PubMed

Hysong, Sylvia J; Esquivel, Adol; Sittig, Dean F; Paul, Lindsey A; Espadas, Donna; Singh, Simran; Singh, Hardeep

2011-07-27

Successful subspecialty referrals require considerable coordination and interactive communication among the primary care provider (PCP), the subspecialist, and the patient, which may be challenging in the outpatient setting. Even when referrals are facilitated by electronic health records (EHRs) (i.e., e-referrals), lapses in patient follow-up might occur. Although compelling reasons exist why referral coordination should be improved, little is known about which elements of the complex referral coordination process should be targeted for improvement. Using Okhuysen & Bechky's coordination framework, this paper aims to understand the barriers, facilitators, and suggestions for improving communication and coordination of EHR-based referrals in an integrated healthcare system. We conducted a qualitative study to understand coordination breakdowns related to e-referrals in an integrated healthcare system and examined work-system factors that affect the timely receipt of subspecialty care. We conducted interviews with seven subject matter experts and six focus groups with a total of 30 PCPs and subspecialists at two tertiary care Department of Veterans Affairs (VA) medical centers. Using techniques from grounded theory and content analysis, we identified organizational themes that affected the referral process. Four themes emerged: lack of an institutional referral policy, lack of standardization in certain referral procedures, ambiguity in roles and responsibilities, and inadequate resources to adapt and respond to referral requests effectively. Marked differences in PCPs' and subspecialists' communication styles and individual mental models of the referral processes likely precluded the development of a shared mental model to facilitate coordination and successful referral completion. Notably, very few barriers related to the EHR were reported. Despite facilitating information transfer between PCPs and subspecialists, e-referrals remain prone to coordination breakdowns. Clear referral policies, well-defined roles and responsibilities for key personnel, standardized procedures and communication protocols, and adequate human resources must be in place before implementing an EHR to facilitate referrals.

Towards successful coordination of electronic health record based-referrals: a qualitative analysis

PubMed Central

2011-01-01

Background Successful subspecialty referrals require considerable coordination and interactive communication among the primary care provider (PCP), the subspecialist, and the patient, which may be challenging in the outpatient setting. Even when referrals are facilitated by electronic health records (EHRs) (i.e., e-referrals), lapses in patient follow-up might occur. Although compelling reasons exist why referral coordination should be improved, little is known about which elements of the complex referral coordination process should be targeted for improvement. Using Okhuysen & Bechky's coordination framework, this paper aims to understand the barriers, facilitators, and suggestions for improving communication and coordination of EHR-based referrals in an integrated healthcare system. Methods We conducted a qualitative study to understand coordination breakdowns related to e-referrals in an integrated healthcare system and examined work-system factors that affect the timely receipt of subspecialty care. We conducted interviews with seven subject matter experts and six focus groups with a total of 30 PCPs and subspecialists at two tertiary care Department of Veterans Affairs (VA) medical centers. Using techniques from grounded theory and content analysis, we identified organizational themes that affected the referral process. Results Four themes emerged: lack of an institutional referral policy, lack of standardization in certain referral procedures, ambiguity in roles and responsibilities, and inadequate resources to adapt and respond to referral requests effectively. Marked differences in PCPs' and subspecialists' communication styles and individual mental models of the referral processes likely precluded the development of a shared mental model to facilitate coordination and successful referral completion. Notably, very few barriers related to the EHR were reported. Conclusions Despite facilitating information transfer between PCPs and subspecialists, e-referrals remain prone to coordination breakdowns. Clear referral policies, well-defined roles and responsibilities for key personnel, standardized procedures and communication protocols, and adequate human resources must be in place before implementing an EHR to facilitate referrals. PMID:21794109

The value of EHR-based assessment of physician competency: An investigative effort with internal medicine physicians.

PubMed

Venta, Kimberly; Baker, Erin; Fidopiastis, Cali; Stanney, Kay

2017-12-01

The purpose of this study was to investigate the potential of developing an EHR-based model of physician competency, named the Skill Deficiency Evaluation Toolkit for Eliminating Competency-loss Trends (Skill-DETECT), which presents the opportunity to use EHR-based models to inform selection of Continued Medical Education (CME) opportunities specifically targeted at maintaining proficiency. The IBM Explorys platform provided outpatient Electronic Health Records (EHRs) representing 76 physicians with over 5000 patients combined. These data were used to develop the Skill-DETECT model, a predictive hybrid model composed of a rule-based model, logistic regression model, and a thresholding model, which predicts cognitive clinical skill deficiencies in internal medicine physicians. A three-phase approach was then used to statistically validate the model performance. Subject Matter Expert (SME) panel reviews resulted in a 100% overall approval rate of the rule based model. Area under the receiver-operating characteristic curves calculated for each logistic regression curve resulted in values between 0.76 and 0.92, which indicated exceptional performance. Normality, skewness, and kurtosis were determined and confirmed that the distribution of values output from the thresholding model were unimodal and peaked, which confirmed effectiveness and generalizability. The validation has confirmed that the Skill-DETECT model has a strong ability to evaluate EHR data and support the identification of internal medicine cognitive clinical skills that are deficient or are of higher likelihood of becoming deficient and thus require remediation, which will allow both physician and medical organizations to fine tune training efforts. Copyright © 2017 Elsevier B.V. All rights reserved.

Contribution of Clinical Archetypes, and the Challenges, towards Achieving Semantic Interoperability for EHRs.

PubMed

Tapuria, Archana; Kalra, Dipak; Kobayashi, Shinji

2013-12-01

The objective is to introduce 'clinical archetype' which is a formal and agreed way of representing clinical information to ensure interoperability across and within Electronic Health Records (EHRs). The paper also aims at presenting the challenges building quality labeled clinical archetypes and the challenges towards achieving semantic interoperability between EHRs. Twenty years of international research, various European healthcare informatics projects and the pioneering work of the openEHR Foundation have led to the following results. The requirements for EHR information architectures have been consolidated within ISO 18308 and adopted within the ISO 13606 EHR interoperability standard. However, a generic EHR architecture cannot ensure that the clinical meaning of information from heterogeneous sources can be reliably interpreted by receiving systems and services. Therefore, clinical models called 'clinical archetypes' are required to formalize the representation of clinical information within the EHR. Part 2 of ISO 13606 defines how archetypes should be formally represented. The current challenge is to grow clinical communities to build a library of clinical archetypes and to identify how evidence of best practice and multi-professional clinical consensus should best be combined to define archetypes at the optimal level of granularity and specificity and quality label them for wide adoption. Standardizing clinical terms within EHRs using clinical terminology like Systematized Nomenclature of Medicine Clinical Terms is also a challenge. Clinical archetypes would play an important role in achieving semantic interoperability within EHRs. Attempts are being made in exploring the design and adoption challenges for clinical archetypes.

Attending Physician Remote Access of the Electronic Health Record and Implications for Resident Supervision: A Mixed Methods Study.

PubMed

Martin, Shannon K; Tulla, Kiara; Meltzer, David O; Arora, Vineet M; Farnan, Jeanne M

2017-12-01

Advances in information technology have increased remote access to the electronic health record (EHR). Concurrently, standards defining appropriate resident supervision have evolved. How often and under what circumstances inpatient attending physicians remotely access the EHR for resident supervision is unknown. We described a model of attending remote EHR use for resident supervision, and quantified the frequency and magnitude of use. Using a mixed methods approach, general medicine inpatient attendings were surveyed and interviewed about their remote EHR use. Frequency of use and supervisory actions were quantitatively examined via survey. Transcripts from semistructured interviews were analyzed using grounded theory to identify codes and themes. A total of 83% (59 of 71) of attendings participated. Fifty-seven (97%) reported using the EHR remotely, with 54 (92%) reporting they discovered new clinical information not relayed by residents via remote EHR use. A majority (93%, 55 of 59) reported that this resulted in management changes, and 54% (32 of 59) reported making immediate changes by contacting cross-covering teams. Six major factors around remote EHR use emerged: resident, clinical, educational, personal, technical, and administrative. Attendings described resident and clinical factors as facilitating "backstage" supervision via remote EHR use. In our study to assess attending remote EHR use for resident supervision, attendings reported frequent remote use with resulting supervisory actions, describing a previously uncharacterized form of "backstage" oversight supervision. Future work should explore best practices in remote EHR use to provide effective supervision and ultimately improve patient safety.

The Evaluation of SEPAS National Project Based on Electronic Health Record System (EHRS) Coordinates in Iran.

PubMed

Asadi, Farkhondeh; Moghaddasi, Hamid; Rabiei, Reza; Rahimi, Forough; Mirshekarlou, Soheila Jahangiri

2015-12-01

Electronic Health Records (EHRs) are secure private lifetime records that can be shared by using interoperability standards between different organizations and units. These records are created by the productive system that is called EHR system. Implementing EHR systems has a number of advantages such as facilitating access to medical records, supporting patient care, and improving the quality of care and health care decisions. The project of electronic health record system in Iran, which is the goal of this study, is called SEPAS. With respect to the importance of EHR and EHR systems the researchers investigated the project from two perspectives: determining the coordinates of the project and how it evolved, and incorporating the coordinates of EHR system in this project. In this study two evaluation tools, a checklist and a questionnaire, were developed based on texts and reliable documentation. The questionnaire and the checklist were validated using content validity by receiving the experts' comments and the questionnaire's reliability was estimated through Test-retest(r =87%). Data were collected through study, observation, and interviews with experts and specialists of SEPAS project. This research showed that SEPAS project, like any other project, could be evaluated. It has some aims; steps, operational phases and certain start and end time, but all the resources and required facilities for the project have not been considered. Therefore it could not satisfy its specified objective and the useful and unique changes which are the other characteristics of any project have not been achieved. In addition, the findings of EHR system coordinates can be determined in 4 categories as Standards and rules, Telecommunication-Communication facilities, Computer equipment and facilities and Stakeholders. The findings indicated that SEPAS has the ability to use all standards of medical terminology and health classification systems in the case of Maksa approval (The reference health coding of Iran). ISO13606 was used as the main standard in this project. Regarding the telecommunication-communication facilities of the project, the findings showed that its link is restricted to health care centers which does not cover other institutions and organizations involved in public health. The final result showed that SEPAS is in the early stages of execution. And the full implementation of EHR needs the provision of the infrastructure of the National Health Information Network that is the same as EHR system.

Agile Model Driven Development of Electronic Health Record-Based Specialty Population Registries

PubMed Central

Kannan, Vaishnavi; Fish, Jason C.; Willett, DuWayne L.

2018-01-01

The transformation of the American healthcare payment system from fee-for-service to value-based care increasingly makes it valuable to develop patient registries for specialized populations, to better assess healthcare quality and costs. Recent widespread adoption of Electronic Health Records (EHRs) in the U.S. now makes possible construction of EHR-based specialty registry data collection tools and reports, previously unfeasible using manual chart abstraction. But the complexities of specialty registry EHR tools and measures, along with the variety of stakeholders involved, can result in misunderstood requirements and frequent product change requests, as users first experience the tools in their actual clinical workflows. Such requirements churn could easily stall progress in specialty registry rollout. Modeling a system’s requirements and solution design can be a powerful way to remove ambiguities, facilitate shared understanding, and help evolve a design to meet newly-discovered needs. “Agile Modeling” retains these values while avoiding excessive unused up-front modeling in favor of iterative incremental modeling. Using Agile Modeling principles and practices, in calendar year 2015 one institution developed 58 EHR-based specialty registries, with 111 new data collection tools, supporting 134 clinical process and outcome measures, and enrolling over 16,000 patients. The subset of UML and non-UML models found most consistently useful in designing, building, and iteratively evolving EHR-based specialty registries included User Stories, Domain Models, Use Case Diagrams, Decision Trees, Graphical User Interface Storyboards, Use Case text descriptions, and Solution Class Diagrams. PMID:29750222

Advanced and secure architectural EHR approaches.

PubMed

Blobel, Bernd

2006-01-01

Electronic Health Records (EHRs) provided as a lifelong patient record advance towards core applications of distributed and co-operating health information systems and health networks. For meeting the challenge of scalable, flexible, portable, secure EHR systems, the underlying EHR architecture must be based on the component paradigm and model driven, separating platform-independent and platform-specific models. Allowing manageable models, real systems must be decomposed and simplified. The resulting modelling approach has to follow the ISO Reference Model - Open Distributing Processing (RM-ODP). The ISO RM-ODP describes any system component from different perspectives. Platform-independent perspectives contain the enterprise view (business process, policies, scenarios, use cases), the information view (classes and associations) and the computational view (composition and decomposition), whereas platform-specific perspectives concern the engineering view (physical distribution and realisation) and the technology view (implementation details from protocols up to education and training) on system components. Those views have to be established for components reflecting aspects of all domains involved in healthcare environments including administrative, legal, medical, technical, etc. Thus, security-related component models reflecting all view mentioned have to be established for enabling both application and communication security services as integral part of the system's architecture. Beside decomposition and simplification of system regarding the different viewpoint on their components, different levels of systems' granularity can be defined hiding internals or focusing on properties of basic components to form a more complex structure. The resulting models describe both structure and behaviour of component-based systems. The described approach has been deployed in different projects defining EHR systems and their underlying architectural principles. In that context, the Australian GEHR project, the openEHR initiative, the revision of CEN ENV 13606 "Electronic Health Record communication", all based on Archetypes, but also the HL7 version 3 activities are discussed in some detail. The latter include the HL7 RIM, the HL7 Development Framework, the HL7's clinical document architecture (CDA) as well as the set of models from use cases, activity diagrams, sequence diagrams up to Domain Information Models (DMIMs) and their building blocks Common Message Element Types (CMET) Constraining Models to their underlying concepts. The future-proof EHR architecture as open, user-centric, user-friendly, flexible, scalable, portable core application in health information systems and health networks has to follow advanced architectural paradigms.

Evaluation of software maintain ability with open EHR - a comparison of architectures.

PubMed

Atalag, Koray; Yang, Hong Yul; Tempero, Ewan; Warren, James R

2014-11-01

To assess whether it is easier to maintain a clinical information system developed using open EHR model driven development versus mainstream methods. A new open source application (GastrOS) has been developed following open EHR's multi-level modelling approach using .Net/C# based on the same requirements of an existing clinically used application developed using Microsoft Visual Basic and Access database. Almost all the domain knowledge was embedded into the software code and data model in the latter. The same domain knowledge has been expressed as a set of open EHR Archetypes in GastrOS. We then introduced eight real-world change requests that had accumulated during live clinical usage, and implemented these in both systems while measuring time for various development tasks and change in software size for each change request. Overall it took half the time to implement changes in GastrOS. However it was the more difficult application to modify for one change request, suggesting the nature of change is also important. It was not possible to implement changes by modelling only. Comparison of relative measures of time and software size change within each application highlights how architectural differences affected maintain ability across change requests. The use of open EHR model driven development can result in better software maintain ability. The degree to which open EHR affects software maintain ability depends on the extent and nature of domain knowledge involved in changes. Although we used relative measures for time and software size, confounding factors could not be totally excluded as a controlled study design was not feasible. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A partnership model for implementing electronic health records in resource-limited primary care settings: experiences from two nurse-managed health centers

PubMed Central

Dennehy, Patricia; White, Mary P; Hamilton, Andrew; Pohl, Joanne M; Tanner, Clare; Onifade, Tiffiani J

2011-01-01

Objective To present a partnership-based and community-oriented approach designed to ease provider anxiety and facilitate the implementation of electronic health records (EHR) in resource-limited primary care settings. Materials and Methods The approach, referred to as partnership model, was developed and iteratively refined through the research team's previous work on implementing health information technology (HIT) in over 30 safety net practices. This paper uses two case studies to illustrate how the model was applied to help two nurse-managed health centers (NMHC), a particularly vulnerable primary care setting, implement EHR and get prepared to meet the meaningful use criteria. Results The strong focus of the model on continuous quality improvement led to eventual implementation success at both sites, despite difficulties encountered during the initial stages of the project. Discussion There has been a lack of research, particularly in resource-limited primary care settings, on strategies for abating provider anxiety and preparing them to manage complex changes associated with EHR uptake. The partnership model described in this paper may provide useful insights into the work shepherded by HIT regional extension centers dedicated to supporting resource-limited communities disproportionally affected by EHR adoption barriers. Conclusion NMHC, similar to other primary care settings, are often poorly resourced, understaffed, and lack the necessary expertise to deploy EHR and integrate its use into their day-to-day practice. This study demonstrates that implementation of EHR, a prerequisite to meaningful use, can be successfully achieved in this setting, and partnership efforts extending far beyond the initial software deployment stage may be the key. PMID:21828225

Analysis and evaluation of the Electronic Health Record standard in China: a comparison with the American national standard ASTM E 1384.

PubMed

Xu, Wei; Guan, Zhiyu; Cao, Hongxin; Zhang, Haiyan; Lu, Min; Li, Tiejun

2011-08-01

To analyze and evaluate the newly issued Electronic Health Record (EHR) Architecture and Data Standard of China (Chinese EHR Standard) and identify areas of improvement for future revisions. We compared the Chinese EHR Standard with the standard of the American Society for Testing and Materials Standard Practice for Content and Structure of Electronic Health Records in the United States (ASTM E 1384 Standard). The comparison comprised two steps: (1) comparing the conformance of the two standards to the international standard: Health Informatics-Requirements for an Electronic Health Record Architecture (ISO/TS 18308), and showing how the architectures of the two standards satisfy or deviate from the ISO requirements and (2) comparing the detailed data structures between the two standards. Of the 124 requirement items in ISO/TS 18308, the Chinese EHR Standard and the ASTM E 1384 Standard conformed to 77 (62.1%) and 111 (89.5%), respectively. The Chinese EHR Standard conformed to 34 of 50 Structure requirements (68.0%), 22 of 24 Process requirements (91.7%), and 21 of 50 Other requirements (42.0%). The ASTM E 1384 Standard conformed to 49 of 50 Structure requirements (98.0%), 23 of 24 Process requirements (95.8%), and 39 of 40 Other requirements (78.0%). Further development of the Chinese EHR Standard should focus on supporting privacy and security mechanism, diverse data types, more generic and extensible lower level data structures, and relational attributes for data elements. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Area-level factors associated with electronic health record adoption and meaningful use in the Regional Extension Center Program.

PubMed

Samuel, Cleo A

2014-01-01

To identify area-level correlates of electronic health record (EHR) adoption and meaningful use (MU) among primary care providers (PCPs) enrolled in the Regional Extension Center (REC) Program. County-level data on 2013 EHR adoption and MU among REC-enrolled PCPs were obtained from the Office of the National Coordinator for Health Information Technology and linked with other county-level data sources including the Area Resource File, American Community Survey, and Federal Communications Commission's broadband availability database. Hierarchical models with random intercepts for RECs were employed to assess associations between a broad set of area-level factors and county-level rates of EHR adoption and MU. Among the 2715 counties examined, the average county-level EHR adoption and MU rates for REC-enrolled PCPs were 87.5% and 54.2%, respectively. Community health center presence and Medicaid enrollment concentration were positively associated with EHR adoption, while metropolitan status and Medicare Advantage enrollment concentration were positively associated with MU. Health professional shortage area status and minority concentration were negatively associated with EHR adoption and MU. Increased financial incentives in areas with greater concentrations of Medicaid and Medicare enrollees may be encouraging EHR adoption and MU among REC-enrolled PCPs. Disparities in EHR adoption and MU in some low-resource and underserved areas remain a concern. Federal efforts to spur EHR adoption and MU have demonstrated some early success; however, some geographic variations in EHR diffusion indicate that greater attention needs to be paid to ensuring equitable uptake and use of EHRs throughout the US. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Area-level factors associated with electronic health record adoption and meaningful use in the Regional Extension Center Program

PubMed Central

Samuel, Cleo A

2014-01-01

Objective To identify area-level correlates of electronic health record (EHR) adoption and meaningful use (MU) among primary care providers (PCPs) enrolled in the Regional Extension Center (REC) Program. Materials and methods County-level data on 2013 EHR adoption and MU among REC-enrolled PCPs were obtained from the Office of the National Coordinator for Health Information Technology and linked with other county-level data sources including the Area Resource File, American Community Survey, and Federal Communications Commission's broadband availability database. Hierarchical models with random intercepts for RECs were employed to assess associations between a broad set of area-level factors and county-level rates of EHR adoption and MU. Results Among the 2715 counties examined, the average county-level EHR adoption and MU rates for REC-enrolled PCPs were 87.5% and 54.2%, respectively. Community health center presence and Medicaid enrollment concentration were positively associated with EHR adoption, while metropolitan status and Medicare Advantage enrollment concentration were positively associated with MU. Health professional shortage area status and minority concentration were negatively associated with EHR adoption and MU. Discussion Increased financial incentives in areas with greater concentrations of Medicaid and Medicare enrollees may be encouraging EHR adoption and MU among REC-enrolled PCPs. Disparities in EHR adoption and MU in some low-resource and underserved areas remain a concern. Conclusions Federal efforts to spur EHR adoption and MU have demonstrated some early success; however, some geographic variations in EHR diffusion indicate that greater attention needs to be paid to ensuring equitable uptake and use of EHRs throughout the US. PMID:24798687

Electronic health records and patient safety: co-occurrence of early EHR implementation with patient safety practices in primary care settings.

PubMed

Tanner, C; Gans, D; White, J; Nath, R; Pohl, J

2015-01-01

The role of electronic health records (EHR) in enhancing patient safety, while substantiated in many studies, is still debated. This paper examines early EHR adopters in primary care to understand the extent to which EHR implementation is associated with the workflows, policies and practices that promote patient safety, as compared to practices with paper records. Early adoption is defined as those who were using EHR prior to implementation of the Meaningful Use program. We utilized the Physician Practice Patient Safety Assessment (PPPSA) to compare primary care practices with fully implemented EHR to those utilizing paper records. The PPPSA measures the extent of adoption of patient safety practices in the domains: medication management, handoffs and transition, personnel qualifications and competencies, practice management and culture, and patient communication. Data from 209 primary care practices responding between 2006-2010 were included in the analysis: 117 practices used paper medical records and 92 used an EHR. Results showed that, within all domains, EHR settings showed significantly higher rates of having workflows, policies and practices that promote patient safety than paper record settings. While these results were expected in the area of medication management, EHR use was also associated with adoption of patient safety practices in areas in which the researchers had no a priori expectations of association. Sociotechnical models of EHR use point to complex interactions between technology and other aspects of the environment related to human resources, workflow, policy, culture, among others. This study identifies that among primary care practices in the national PPPSA database, having an EHR was strongly empirically associated with the workflow, policy, communication and cultural practices recommended for safe patient care in ambulatory settings.

Does adoption of electronic health records improve the quality of care management in France? Results from the French e-SI (PREPS-SIPS) study.

PubMed

Plantier, Morgane; Havet, Nathalie; Durand, Thierry; Caquot, Nicolas; Amaz, Camille; Biron, Pierre; Philip, Irène; Perrier, Lionel

2017-06-01

Electronic health records (EHR) are increasingly being adopted by healthcare systems worldwide. In France, the "Hôpital numérique 2012-2017" program was implemented as part of a strategic plan to modernize health information technology (HIT), including the promotion of widespread EHR use. With significant upfront investment costs as well as ongoing operational expenses, it is important to assess this system in terms of its ability to result in improvements in hospital performances. The aim of this study was to evaluate the impact of EHR use on the quality of care management in acute care hospitals throughout France. This retrospective study was based on data derived from three national databases for the year 2011: IPAQSS (indicators of improvement in the quality and the management of healthcare, "IPAQSS"), Hospi-Diag (French hospital performance indicators), and the national accreditation database. Several multivariate models were used to examine the association between the use of EHRs and specific EHR features with four quality indicators: the quality of patient record, the delay in sending information at hospital discharge, the pain status evaluation, and the nutritional status evaluation, while also adjusting for hospital characteristics. The models revealed a significant positive impact of EHR use on the four quality indicators. Additionally, they showed a differential impact according to the functionality of the element of the health record that was computerized. All four quality indicators were also impacted by the type of hospital, the geographical region, and the severity of the pathology. These results suggest that, to improve the quality of care management in hospitals, EHR adoption represents an important lever. They complete previous work dealing with EHR and the organizational performance of hospital surgical units. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

PubMed Central

Miotto, Riccardo; Li, Li; Kidd, Brian A.; Dudley, Joel T.

2016-01-01

Secondary use of electronic health records (EHRs) promises to advance clinical research and better inform clinical decision making. Challenges in summarizing and representing patient data prevent widespread practice of predictive modeling using EHRs. Here we present a novel unsupervised deep feature learning method to derive a general-purpose patient representation from EHR data that facilitates clinical predictive modeling. In particular, a three-layer stack of denoising autoencoders was used to capture hierarchical regularities and dependencies in the aggregated EHRs of about 700,000 patients from the Mount Sinai data warehouse. The result is a representation we name “deep patient”. We evaluated this representation as broadly predictive of health states by assessing the probability of patients to develop various diseases. We performed evaluation using 76,214 test patients comprising 78 diseases from diverse clinical domains and temporal windows. Our results significantly outperformed those achieved using representations based on raw EHR data and alternative feature learning strategies. Prediction performance for severe diabetes, schizophrenia, and various cancers were among the top performing. These findings indicate that deep learning applied to EHRs can derive patient representations that offer improved clinical predictions, and could provide a machine learning framework for augmenting clinical decision systems. PMID:27185194

Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

NASA Astrophysics Data System (ADS)

Miotto, Riccardo; Li, Li; Kidd, Brian A.; Dudley, Joel T.

2016-05-01

Secondary use of electronic health records (EHRs) promises to advance clinical research and better inform clinical decision making. Challenges in summarizing and representing patient data prevent widespread practice of predictive modeling using EHRs. Here we present a novel unsupervised deep feature learning method to derive a general-purpose patient representation from EHR data that facilitates clinical predictive modeling. In particular, a three-layer stack of denoising autoencoders was used to capture hierarchical regularities and dependencies in the aggregated EHRs of about 700,000 patients from the Mount Sinai data warehouse. The result is a representation we name “deep patient”. We evaluated this representation as broadly predictive of health states by assessing the probability of patients to develop various diseases. We performed evaluation using 76,214 test patients comprising 78 diseases from diverse clinical domains and temporal windows. Our results significantly outperformed those achieved using representations based on raw EHR data and alternative feature learning strategies. Prediction performance for severe diabetes, schizophrenia, and various cancers were among the top performing. These findings indicate that deep learning applied to EHRs can derive patient representations that offer improved clinical predictions, and could provide a machine learning framework for augmenting clinical decision systems.

Perceived usefulness and perceived ease of use of electronic health records among nurses: Application of Technology Acceptance Model.

PubMed

Tubaishat, Ahmad

2017-09-18

Electronic health records (EHRs) are increasingly being implemented in healthcare organizations but little attention has been paid to the degree to which nurses as end-users will accept these systems and subsequently use them. To explore nurses' perceptions of usefulness and ease-of-use of EHRs. The relationship between these constructs was examined, and its predictors were studied. A national exploratory study was conducted with 1539 nurses from 15 randomly selected hospitals, representative of different regions and healthcare sectors in Jordan. Data were collected using a self-administered questionnaire, which was based on the Technology Acceptance Model. Correlations and linear multiple regression were utilized to analyze the data. Jordanian nurses demonstrated a positive perception of the usefulness and ease-of-use of EHRs, and subsequently accepted the technology. Significant positive correlations were found between these two constructs. The variables that predict usefulness were the gender, professional rank, EHR experience, and computer skills of the nurses. The perceived ease-of-use was affected by nursing and EHR experience, and computers skills. This study adds to the growing body of knowledge on issues related to the acceptance of technology in the health informatics field, focusing on nurses' acceptance of EHRs.

Model Development for EHR Interdisciplinary Information Exchange of ICU Common Goals

PubMed Central

Collins, Sarah A.; Bakken, Suzanne; Vawdrey, David K.; Coiera, Enrico; Currie, Leanne

2010-01-01

Purpose Effective interdisciplinary exchange of patient information is an essential component of safe, efficient, and patient–centered care in the intensive care unit (ICU). Frequent handoffs of patient care, high acuity of patient illness, and the increasing amount of available data complicate information exchange. Verbal communication can be affected by interruptions and time limitations. To supplement verbal communication, many ICUs rely on documentation in electronic health records (EHRs) to reduce errors of omission and information loss. The purpose of this study was to develop a model of EHR interdisciplinary information exchange of ICU common goals. Methods The theoretical frameworks of distributed cognition and the clinical communication space were integrated and a previously published categorization of verbal information exchange was used. 59.5 hours of interdisciplinary rounds in a Neurovascular ICU were observed and five interviews and one focus group with ICU nurses and physicians were conducted. Results Current documentation tools in the ICU were not sufficient to capture the nurses' and physicians' collaborative decision-making and verbal communication of goal-directed actions and interactions. Clinicians perceived the EHR to be inefficient for information retrieval, leading to a further reliance on verbal information exchange. Conclusion The model suggests that EHRs should support: 1) Information tools for the explicit documentation of goals, interventions, and assessments with synthesized and summarized information outputs of events and updates; and 2) Messaging tools that support collaborative decision-making and patient safety double checks that currently occur between nurses and physicians in the absence of EHR support. PMID:20974549

Assessing and comparing the usability of Chinese EHRs used in two Peking University hospitals to EHRs used in the US: A method of RUA.

PubMed

Xu, Lufei; Wen, Dong; Zhang, Xingting; Lei, Jianbo

2016-05-01

The objective of this study was to investigate the usability level of Chinese hospital Electronic Health Records (EHRs) by assessing the completion times of EHRs for seven "meaningful use (MU)" relevant tasks conducted at two Chinese tertiary hospitals and comparing the results to those of relevant research conducted in US EHRs. Using Rapid Usability Assessment (RUA) developed by the National Center for Cognitive Informatics and Decision Making (NCCD), the usability of EHRs from two Peking University hospitals was assessed using a three-step Keystroke Level Model (KLM) in a laboratory environment. (1) The total EHR task completion time for 7 MU relevant test tasks showed no significant differences between the two Chinese EHRs and their US counterparts, in which the time for thinking was relatively large and comprised 35.6% of the total time. The time for the electronic physician order was the largest. (2) For specific tasks, the mean completion times of the 2 hospital EHR systems spent on recording, modifying and searching (RMS) the medication orders were similar to those for the RMS radioactive tests; the mean time spent on the RMS laboratory test orders were much less. (3) There were 85 usability problems identified in the 2 hospital EHR systems. In Chinese EHRs, a substantial amount of time is required to complete tasks relevant to MU targets and many preventable usability problems can be discovered. The task completion time of the 2 Chinese EHR systems was a little shorter than in the 5 reported US EHR systems, while the differences in smoking status and CPOE tasks were obvious; one main reason for these differences was the use of structured data entry. The efficiency of Chinese and US EHRs was not significantly different. The key to improving the efficiency of both systems lies in expediting the Computerized physician order entry (CPOE) task. Many usability problems can be identified using heuristic assessments and improved by corresponding actions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Automated population of an i2b2 clinical data warehouse from an openEHR-based data repository.

PubMed

Haarbrandt, Birger; Tute, Erik; Marschollek, Michael

2016-10-01

Detailed Clinical Model (DCM) approaches have recently seen wider adoption. More specifically, openEHR-based application systems are now used in production in several countries, serving diverse fields of application such as health information exchange, clinical registries and electronic medical record systems. However, approaches to efficiently provide openEHR data to researchers for secondary use have not yet been investigated or established. We developed an approach to automatically load openEHR data instances into the open source clinical data warehouse i2b2. We evaluated query capabilities and the performance of this approach in the context of the Hanover Medical School Translational Research Framework (HaMSTR), an openEHR-based data repository. Automated creation of i2b2 ontologies from archetypes and templates and the integration of openEHR data instances from 903 patients of a paediatric intensive care unit has been achieved. In total, it took an average of ∼2527s to create 2.311.624 facts from 141.917 XML documents. Using the imported data, we conducted sample queries to compare the performance with two openEHR systems and to investigate if this representation of data is feasible to support cohort identification and record level data extraction. We found the automated population of an i2b2 clinical data warehouse to be a feasible approach to make openEHR data instances available for secondary use. Such an approach can facilitate timely provision of clinical data to researchers. It complements analytics based on the Archetype Query Language by allowing querying on both, legacy clinical data sources and openEHR data instances at the same time and by providing an easy-to-use query interface. However, due to different levels of expressiveness in the data models, not all semantics could be preserved during the ETL process. Copyright © 2016 Elsevier Inc. All rights reserved.

Cost-benefit assessment of using electronic health records data for clinical research versus current practices: Contribution of the Electronic Health Records for Clinical Research (EHR4CR) European Project.

PubMed

Beresniak, Ariel; Schmidt, Andreas; Proeve, Johann; Bolanos, Elena; Patel, Neelam; Ammour, Nadir; Sundgren, Mats; Ericson, Mats; Karakoyun, Töresin; Coorevits, Pascal; Kalra, Dipak; De Moor, Georges; Dupont, Danielle

2016-01-01

The widespread adoption of electronic health records (EHR) provides a new opportunity to improve the efficiency of clinical research. The European EHR4CR (Electronic Health Records for Clinical Research) 4-year project has developed an innovative technological platform to enable the re-use of EHR data for clinical research. The objective of this cost-benefit assessment (CBA) is to assess the value of EHR4CR solutions compared to current practices, from the perspective of sponsors of clinical trials. A CBA model was developed using an advanced modeling approach. The costs of performing three clinical research scenarios (S) applied to a hypothetical Phase II or III oncology clinical trial workflow (reference case) were estimated under current and EHR4CR conditions, namely protocol feasibility assessment (S1), patient identification for recruitment (S2), and clinical study execution (S3). The potential benefits were calculated considering that the estimated reduction in actual person-time and costs for performing EHR4CR S1, S2, and S3 would accelerate time to market (TTM). Probabilistic sensitivity analyses using Monte Carlo simulations were conducted to manage uncertainty. Should the estimated efficiency gains achieved with the EHR4CR platform translate into faster TTM, the expected benefits for the global pharmaceutical oncology sector were estimated at €161.5m (S1), €45.7m (S2), €204.5m (S1+S2), €1906m (S3), and up to €2121.8m (S1+S2+S3) when the scenarios were used sequentially. The results suggest that optimizing clinical trial design and execution with the EHR4CR platform would generate substantial added value for pharmaceutical industry, as main sponsors of clinical trials in Europe, and beyond. Copyright © 2015 Elsevier Inc. All rights reserved.

Contribution of Clinical Archetypes, and the Challenges, towards Achieving Semantic Interoperability for EHRs

PubMed Central

Kalra, Dipak; Kobayashi, Shinji

2013-01-01

Objectives The objective is to introduce 'clinical archetype' which is a formal and agreed way of representing clinical information to ensure interoperability across and within Electronic Health Records (EHRs). The paper also aims at presenting the challenges building quality labeled clinical archetypes and the challenges towards achieving semantic interoperability between EHRs. Methods Twenty years of international research, various European healthcare informatics projects and the pioneering work of the openEHR Foundation have led to the following results. Results The requirements for EHR information architectures have been consolidated within ISO 18308 and adopted within the ISO 13606 EHR interoperability standard. However, a generic EHR architecture cannot ensure that the clinical meaning of information from heterogeneous sources can be reliably interpreted by receiving systems and services. Therefore, clinical models called 'clinical archetypes' are required to formalize the representation of clinical information within the EHR. Part 2 of ISO 13606 defines how archetypes should be formally represented. The current challenge is to grow clinical communities to build a library of clinical archetypes and to identify how evidence of best practice and multi-professional clinical consensus should best be combined to define archetypes at the optimal level of granularity and specificity and quality label them for wide adoption. Standardizing clinical terms within EHRs using clinical terminology like Systematized Nomenclature of Medicine Clinical Terms is also a challenge. Conclusions Clinical archetypes would play an important role in achieving semantic interoperability within EHRs. Attempts are being made in exploring the design and adoption challenges for clinical archetypes. PMID:24523993

Quality and Certification of Electronic Health Records

PubMed Central

Hoerbst, A.; Ammenwerth, E.

2010-01-01

Background Numerous projects, initiatives, and programs are dedicated to the development of Electronic Health Records (EHR) worldwide. Increasingly more of these plans have recently been brought from a scientific environment to real life applications. In this context, quality is a crucial factor with regard to the acceptance and utility of Electronic Health Records. However, the dissemination of the existing quality approaches is often rather limited. Objectives The present paper aims at the description and comparison of the current major quality certification approaches to EHRs. Methods A literature analysis was carried out in order to identify the relevant publications with regard to EHR quality certification. PubMed, ACM Digital Library, IEEExplore, CiteSeer, and Google (Scholar) were used to collect relevant sources. The documents that were obtained were analyzed using techniques of qualitative content analysis. Results The analysis discusses and compares the quality approaches of CCHIT, EuroRec, IHE, openEHR, and EN13606. These approaches differ with regard to their focus, support of service-oriented EHRs, process of (re-)certification and testing, number of systems certified and tested, supporting organizations, and regional relevance. Discussion The analyzed approaches show differences with regard to their structure and processes. System vendors can exploit these approaches in order to improve and certify their information systems. Health care organizations can use these approaches to support selection processes or to assess the quality of their own information systems. PMID:23616834

EHR implementation in South Africa: how do we get it right?

PubMed

Yogeswaran, Parimalaranie; Wright, Graham

2010-01-01

In an environment of expanding demand on the health care system to provide equitable, accessible and safe health care, usage of information communication technology is one of the strategies identified to fulfil such expectations. Electronic Health Record (EHR) is an important tool towards achieving better health care using such technology, although, across the world EHR implementation has experienced a high failure rate. Nevertheless South Africa has made a strategic decision to implement EHR system in the public health sector. An evaluation toolkit was developed, to measure the state of readiness of health institutions in South Africa in implementing EHR based on Kaplan and Norton's work on Balanced Score Card (BSC), and the subsequent variant model developed by Protti. A Critical Success Factor (CSF) scorecard to assess the state of readiness and a Balanced Score Card matrix to be used as a strategic framework was developed. These tools were validated using critiques by a panel of experts. The toolkit developed has the potential to assist the organization towards a better EHR implementation path.

Electronic health record adoption in US hospitals: the emergence of a digital "advanced use" divide.

PubMed

Adler-Milstein, Julia; Holmgren, A Jay; Kralovec, Peter; Worzala, Chantal; Searcy, Talisha; Patel, Vaishali

2017-11-01

While most hospitals have adopted electronic health records (EHRs), we know little about whether hospitals use EHRs in advanced ways that are critical to improving outcomes, and whether hospitals with fewer resources - small, rural, safety-net - are keeping up. Using 2008-2015 American Hospital Association Information Technology Supplement survey data, we measured "basic" and "comprehensive" EHR adoption among hospitals to provide the latest national numbers. We then used new supplement questions to assess advanced use of EHRs and EHR data for performance measurement and patient engagement functions. To assess a digital "advanced use" divide, we ran logistic regression models to identify hospital characteristics associated with high adoption in each advanced use domain. We found that 80.5% of hospitals adopted at least a basic EHR system, a 5.3 percentage point increase from 2014. Only 37.5% of hospitals adopted at least 8 (of 10) EHR data for performance measurement functions, and 41.7% of hospitals adopted at least 8 (of 10) patient engagement functions. Critical access hospitals were less likely to have adopted at least 8 performance measurement functions (odds ratio [OR] = 0.58; P < .001) and at least 8 patient engagement functions (OR = 0.68; P = 0.02). While the Health Information Technology for Economic and Clinical Health Act resulted in widespread hospital EHR adoption, use of advanced EHR functions lags and a digital divide appears to be emerging, with critical-access hospitals in particular lagging behind. This is concerning, because EHR-enabled performance measurement and patient engagement are key contributors to improving hospital performance. Hospital EHR adoption is widespread and many hospitals are using EHRs to support performance measurement and patient engagement. However, this is not happening across all hospitals. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Prediction and Informative Risk Factor Selection of Bone Diseases.

PubMed

Li, Hui; Li, Xiaoyi; Ramanathan, Murali; Zhang, Aidong

2015-01-01

With the booming of healthcare industry and the overwhelming amount of electronic health records (EHRs) shared by healthcare institutions and practitioners, we take advantage of EHR data to develop an effective disease risk management model that not only models the progression of the disease, but also predicts the risk of the disease for early disease control or prevention. Existing models for answering these questions usually fall into two categories: the expert knowledge based model or the handcrafted feature set based model. To fully utilize the whole EHR data, we will build a framework to construct an integrated representation of features from all available risk factors in the EHR data and use these integrated features to effectively predict osteoporosis and bone fractures. We will also develop a framework for informative risk factor selection of bone diseases. A pair of models for two contrast cohorts (e.g., diseased patients versus non-diseased patients) will be established to discriminate their characteristics and find the most informative risk factors. Several empirical results on a real bone disease data set show that the proposed framework can successfully predict bone diseases and select informative risk factors that are beneficial and useful to guide clinical decisions.

Using a generalised identity reference model with archetypes to support interoperability of demographics information in electronic health record systems.

PubMed

Xu Chen; Berry, Damon; Stephens, Gaye

2015-01-01

Computerised identity management is in general encountered as a low-level mechanism that enables users in a particular system or region to securely access resources. In the Electronic Health Record (EHR), the identifying information of both the healthcare professionals who access the EHR and the patients whose EHR is accessed, are subject to change. Demographics services have been developed to manage federated patient and healthcare professional identities and to support challenging healthcare-specific use cases in the presence of diverse and sometimes conflicting demographic identities. Demographics services are not the only use for identities in healthcare. Nevertheless, contemporary EHR specifications limit the types of entities that can be the actor or subject of a record to health professionals and patients, thus limiting the use of two level models in other healthcare information systems. Demographics are ubiquitous in healthcare, so for a general identity model to be usable, it should be capable of managing demographic information. In this paper, we introduce a generalised identity reference model (GIRM) based on key characteristics of five surveyed demographic models. We evaluate the GIRM by using it to express the EN13606 demographics model in an extensible way at the metadata level and show how two-level modelling can support the exchange of instances of demographic identities. This use of the GIRM to express demographics information shows its application for standards-compliant two-level modelling alongside heterogeneous demographics models. We advocate this approach to facilitate the interoperability of identities between two-level model-based EHR systems and show the validity and the extensibility of using GIRM for the expression of other health-related identities.

For Developers

MedlinePlus

... health IT providers to link patient portals and electronic health record (EHR) systems to content from MedlinePlus.gov. MedlinePlus ... updates Subscribe to RSS Follow us Disclaimers Copyright Privacy Accessibility Quality Guidelines Viewers & Players MedlinePlus Connect for ...

The Impact of a Primary Care Education Program Regarding Cancer Survivorship Care Plans: Results from an Engineering, Primary Care, and Oncology Collaborative for Survivorship Health.

PubMed

Donohue, SarahMaria; Haine, James E; Li, Zhanhai; Trowbridge, Elizabeth R; Kamnetz, Sandra A; Feldstein, David A; Sosman, James M; Wilke, Lee G; Sesto, Mary E; Tevaarwerk, Amye J

2017-09-20

Survivorship care plans (SCPs) have been recommended as tools to improve care coordination and outcomes for cancer survivors. SCPs are increasingly being provided to survivors and their primary care providers. However, most primary care providers remain unaware of SCPs, limiting their potential benefit. Best practices for educating primary care providers regarding SCP existence and content are needed. We developed an education program to inform primary care providers of the existence, content, and potential uses for SCPs. The education program consisted of a 15-min presentation highlighting SCP basics presented at mandatory primary care faculty meetings. An anonymous survey was electronically administered via email (n = 287 addresses) to evaluate experience with and basic knowledge of SCPs pre- and post-education. A total of 101 primary care advanced practice providers (APPs) and physicians (35% response rate) completed the baseline survey with only 23% reporting prior receipt of a SCP. Only 9% could identify the SCP location within the electronic health record (EHR). Following the education program, primary care physicians and APPs demonstrated a significant improvement in SCP knowledge, including improvement in their ability to locate one within the EHR (9 vs 59%, p < 0.0001). A brief educational program containing information about SCP existence, content, and location in the EHR increased primary care physician and APP knowledge in these areas, which are prerequisites for using SCP in clinical practice.

Clinical Knowledge Governance Framework for Nationwide Data Infrastructure Projects.

PubMed

Wulff, Antje; Haarbrandt, Birger; Marschollek, Michael

2018-01-01

The availability of semantically-enriched and interoperable clinical information models is crucial for reusing once collected data across institutions like aspired in the German HiGHmed project. Funded by the Federal Ministry of Education and Research, this nationwide data infrastructure project adopts the openEHR approach for semantic modelling. Here, strong governance is required to define high-quality and reusable models. Design of a clinical knowledge governance framework for openEHR modelling in cross-institutional settings like HiGHmed. Analysis of successful practices from international projects, published ideas on archetype governance and own modelling experiences as well as modelling of BPMN processes. We designed a framework by presenting archetype variations, roles and responsibilities, IT support and modelling workflows. Our framework has great potential to make the openEHR modelling efforts manageable. Because practical experiences are rare, prospectively our work will be predestinated to evaluate the benefits of such structured governance approaches.

Modeling and executing electronic health records driven phenotyping algorithms using the NQF Quality Data Model and JBoss® Drools Engine.

PubMed

Li, Dingcheng; Endle, Cory M; Murthy, Sahana; Stancl, Craig; Suesse, Dale; Sottara, Davide; Huff, Stanley M; Chute, Christopher G; Pathak, Jyotishman

2012-01-01

With increasing adoption of electronic health records (EHRs), the need for formal representations for EHR-driven phenotyping algorithms has been recognized for some time. The recently proposed Quality Data Model from the National Quality Forum (NQF) provides an information model and a grammar that is intended to represent data collected during routine clinical care in EHRs as well as the basic logic required to represent the algorithmic criteria for phenotype definitions. The QDM is further aligned with Meaningful Use standards to ensure that the clinical data and algorithmic criteria are represented in a consistent, unambiguous and reproducible manner. However, phenotype definitions represented in QDM, while structured, cannot be executed readily on existing EHRs. Rather, human interpretation, and subsequent implementation is a required step for this process. To address this need, the current study investigates open-source JBoss® Drools rules engine for automatic translation of QDM criteria into rules for execution over EHR data. In particular, using Apache Foundation's Unstructured Information Management Architecture (UIMA) platform, we developed a translator tool for converting QDM defined phenotyping algorithm criteria into executable Drools rules scripts, and demonstrated their execution on real patient data from Mayo Clinic to identify cases for Coronary Artery Disease and Diabetes. To the best of our knowledge, this is the first study illustrating a framework and an approach for executing phenotyping criteria modeled in QDM using the Drools business rules management system.

Modeling and Executing Electronic Health Records Driven Phenotyping Algorithms using the NQF Quality Data Model and JBoss® Drools Engine

PubMed Central

Li, Dingcheng; Endle, Cory M; Murthy, Sahana; Stancl, Craig; Suesse, Dale; Sottara, Davide; Huff, Stanley M.; Chute, Christopher G.; Pathak, Jyotishman

2012-01-01

With increasing adoption of electronic health records (EHRs), the need for formal representations for EHR-driven phenotyping algorithms has been recognized for some time. The recently proposed Quality Data Model from the National Quality Forum (NQF) provides an information model and a grammar that is intended to represent data collected during routine clinical care in EHRs as well as the basic logic required to represent the algorithmic criteria for phenotype definitions. The QDM is further aligned with Meaningful Use standards to ensure that the clinical data and algorithmic criteria are represented in a consistent, unambiguous and reproducible manner. However, phenotype definitions represented in QDM, while structured, cannot be executed readily on existing EHRs. Rather, human interpretation, and subsequent implementation is a required step for this process. To address this need, the current study investigates open-source JBoss® Drools rules engine for automatic translation of QDM criteria into rules for execution over EHR data. In particular, using Apache Foundation’s Unstructured Information Management Architecture (UIMA) platform, we developed a translator tool for converting QDM defined phenotyping algorithm criteria into executable Drools rules scripts, and demonstrated their execution on real patient data from Mayo Clinic to identify cases for Coronary Artery Disease and Diabetes. To the best of our knowledge, this is the first study illustrating a framework and an approach for executing phenotyping criteria modeled in QDM using the Drools business rules management system. PMID:23304325

Implementation of workflow engine technology to deliver basic clinical decision support functionality

PubMed Central

2011-01-01

Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform. PMID:21477364

Electronic Health Record Patient Portal Adoption by Health Care Consumers: An Acceptance Model and Survey

PubMed Central

2016-01-01

Background The future of health care delivery is becoming more citizen centered, as today’s user is more active, better informed, and more demanding. Worldwide governments are promoting online health services, such as electronic health record (EHR) patient portals and, as a result, the deployment and use of these services. Overall, this makes the adoption of patient-accessible EHR portals an important field to study and understand. Objective The aim of this study is to understand the factors that drive individuals to adopt EHR portals. Methods We applied a new adoption model using, as a starting point, Ventkatesh's Unified Theory of Acceptance and Use of Technology in a consumer context (UTAUT2) by integrating a new construct specific to health care, a new moderator, and new relationships. To test the research model, we used the partial least squares (PLS) causal modelling approach. An online questionnaire was administrated. We collected 360 valid responses. Results The statistically significant drivers of behavioral intention are performance expectancy (beta=.200; t=3.619), effort expectancy (beta=.185; t=2.907), habit (beta=.388; t=7.320), and self-perception (beta=.098; t=2.285). The predictors of use behavior are habit (beta=0.206; t=2.752) and behavioral intention (beta=0.258; t=4.036). The model explained 49.7% of the variance in behavioral intention and 26.8% of the variance in use behavior. Conclusions Our research helps to understand the desired technology characteristics of EHR portals. By testing an information technology acceptance model, we are able to determine what is more valued by patients when it comes to deciding whether to adopt EHR portals or not. The inclusion of specific constructs and relationships related to the health care consumer area also had a significant impact on understanding the adoption of EHR portals. PMID:26935646

An approach for the semantic interoperability of ISO EN 13606 and OpenEHR archetypes.

PubMed

Martínez-Costa, Catalina; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2010-10-01

The communication between health information systems of hospitals and primary care organizations is currently an important challenge to improve the quality of clinical practice and patient safety. However, clinical information is usually distributed among several independent systems that may be syntactically or semantically incompatible. This fact prevents healthcare professionals from accessing clinical information of patients in an understandable and normalized way. In this work, we address the semantic interoperability of two EHR standards: OpenEHR and ISO EN 13606. Both standards follow the dual model approach which distinguishes information and knowledge, this being represented through archetypes. The solution presented here is capable of transforming OpenEHR archetypes into ISO EN 13606 and vice versa by combining Semantic Web and Model-driven Engineering technologies. The resulting software implementation has been tested using publicly available collections of archetypes for both standards.

The Impact of Electronic Health Records on Risk Management of Information Systems in Australian Residential Aged Care Homes.

PubMed

Jiang, Tao; Yu, Ping; Hailey, David; Ma, Jun; Yang, Jie

2016-09-01

To obtain indications of the influence of electronic health records (EHR) in managing risks and meeting information system accreditation standard in Australian residential aged care (RAC) homes. The hypothesis to be tested is that the RAC homes using EHR have better performance in meeting information system standards in aged care accreditation than their counterparts only using paper records for information management. Content analysis of aged care accreditation reports from the Aged Care Standards and Accreditation Agency produced between April 2011 and December 2013. Items identified included types of information systems, compliance with accreditation standards, and indicators of failure to meet an expected outcome for information systems. The Chi-square test was used to identify difference between the RAC homes that used EHR systems and those that used paper records in not meeting aged care accreditation standards. 1,031 (37.4%) of 2,754 RAC homes had adopted EHR systems. Although the proportion of homes that met all accreditation standards was significantly higher for those with EHR than for homes with paper records, only 13 RAC homes did not meet one or more expected outcomes. 12 used paper records and nine of these failed the expected outcome for information systems. The overall contribution of EHR to meeting aged care accreditation standard in Australia was very small. Risk indicators for not meeting information system standard were no access to accurate and appropriate information, failure in monitoring mechanisms, not reporting clinical incidents, insufficient recording of residents' clinical changes, not providing accurate care plans, and communication processes failure. The study has provided indications that use of EHR provides small, yet significant advantages for RAC homes in Australia in managing risks for information management and in meeting accreditation requirements. The implication of the study for introducing technology innovation in RAC in Australia is discussed.

Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence

PubMed Central

2013-01-01

Background Computerized clinical trial recruitment support is one promising field for the application of routine care data for clinical research. The primary task here is to compare the eligibility criteria defined in trial protocols with patient data contained in the electronic health record (EHR). To avoid the implementation of different patient definitions in multi-site trials, all participating research sites should use similar patient data from the EHR. Knowledge of the EHR data elements which are commonly available from most EHRs is required to be able to define a common set of criteria. The objective of this research is to determine for five tertiary care providers the extent of available data compared with the eligibility criteria of randomly selected clinical trials. Methods Each participating study site selected three clinical trials at random. All eligibility criteria sentences were broken up into independent patient characteristics, which were then assigned to one of the 27 semantic categories for eligibility criteria developed by Luo et al. We report on the fraction of patient characteristics with corresponding structured data elements in the EHR and on the fraction of patients with available data for these elements. The completeness of EHR data for the purpose of patient recruitment is calculated for each semantic group. Results 351 eligibility criteria from 15 clinical trials contained 706 patient characteristics. In average, 55% of these characteristics could be documented in the EHR. Clinical data was available for 64% of all patients, if corresponding data elements were available. The total completeness of EHR data for recruitment purposes is 35%. The best performing semantic groups were ‘age’ (89%), ‘gender’ (89%), ‘addictive behaviour’ (74%), ‘disease, symptom and sign’ (64%) and ‘organ or tissue status’ (61%). No data was available for 6 semantic groups. Conclusions There exists a significant gap in structure and content between data documented during patient care and data required for patient eligibility assessment. Nevertheless, EHR data on age and gender of the patient, as well as selected information on his disease can be complete enough to allow for an effective support of the manual screening process with an intelligent preselection of patients and patient data. PMID:23514203

Electronic Health Record Effects on Work-Life Balance and Burnout Within the I3 Population Collaborative.

PubMed

Robertson, Sandy L; Robinson, Mark D; Reid, Alfred

2017-08-01

Physician burnout is a problem that often is attributed to the use of the electronic health record (EHR). To estimate the prevalence of burnout and work-life balance satisfaction in primary care residents and teaching physicians, and to examine the relationship between these outcomes, EHR use, and other practice and individual factors. Residents and faculty in 19 primary care programs were anonymously surveyed about burnout, work-life balance satisfaction, and EHR use. Additional items included practice size, specialty, EHR characteristics, and demographics. A logistic regression model identified independent factors associated with burnout and work-life balance satisfaction. In total, 585 of 866 surveys (68%) were completed, and 216 (37%) respondents indicated 1 or more symptoms of burnout, with 162 (75%) attributing burnout to the EHR. A total of 310 of 585 (53%) reported dissatisfaction with work-life balance, and 497 (85%) indicated that use of the EHR affected their work-life balance. Respondents who spent more than 6 hours weekly after hours in EHR work were 2.9 times (95% confidence interval [CI] 1.9-4.4) more likely to report burnout and 3.9 times (95% CI 1.9-8.2) more likely to attribute burnout to the EHR. They were 0.33 times (95% CI 0.22-0.49) as likely to report work-life balance satisfaction, and 3.7 times (95% CI 2.1-6.7) more likely to attribute their work-life balance satisfaction to the EHR. More after-hours time spent on the EHR was associated with burnout and less work-life satisfaction in primary care residents and faculty.

Development of a tripolar model of technology acceptance: Hospital-based physicians' perspective on EHR.

PubMed

Beglaryan, Mher; Petrosyan, Varduhi; Bunker, Edward

2017-06-01

In health care, information technologies (IT) hold a promise to harness an ever-increasing flow of health related information and bring significant benefits including improved quality of care, efficiency, and cost containment. One of the main tools for collecting and utilizing health data is the Electronic Health Record (EHR). EHRs implementation can face numerous barriers to acceptance including attitudes and perceptions of potential users, required effort attributed to their implementation and usage, and resistance to change. Various theories explicate different aspects of technology deployment, implementation, and acceptance. One of the common theories is the Technology Acceptance Model (TAM), which helps to study the implementation of different healthcare IT applications. The objectives of this study are: to understand the barriers of EHR implementation from the perspective of physicians; to identify major determinants of physicians' acceptance of technology; and develop a model that explains better how EHRs (and technologies in general) are accepted by physicians. The proposed model derives from a cross-sectional survey of physicians selected through multi-stage cluster sampling from the hospitals of Yerevan, Armenia. The study team designed the survey instrument based on a literature review on barriers of EHR implementation. The analysis employed exploratory structural equation modeling (ESEM) with a robust weighted least squares (WLSMV) estimator for categorical indicators. The analysis progressed in two steps: appraisal of the measurement model and testing of the structural model. The derived model identifies the following factors as direct determinants of behavioral intention to use a novel technology: projected collective usefulness; personal innovativeness; patient influence; and resistance to change. Other factors (e.g., organizational change, professional relationships, administrative monitoring, organizational support and computer anxiety) exert their effects through projected collective usefulness, perceived usefulness, and perceived ease of use. The model reconciles individual-oriented and environment-oriented theoretical approaches and proposes a Tripolar Model of Technology Acceptance (TMTA), bringing together three key pillars of the healthcare: patients, practitioners, and provider organizations. The proposed TMTA explains 85% of variance of behavioral intention to use technology. The current study draws from the barriers of EHR implementation and identifies major determinants of technology acceptance among physicians. The study proposes TMTA as affording stronger explanative and predictive abilities for the health care system. TMTA paves a long overlooked gap in TAM and its descendants, which, in organizational settings, might distort construal of technology acceptance. It also explicates with greater depth the interdependence of different participants of the healthcare and complex interactions between healthcare and technologies. Copyright © 2017 Elsevier B.V. All rights reserved.

Developing EHR-driven heart failure risk prediction models using CPXR(Log) with the probabilistic loss function.

PubMed

Taslimitehrani, Vahid; Dong, Guozhu; Pereira, Naveen L; Panahiazar, Maryam; Pathak, Jyotishman

2016-04-01

Computerized survival prediction in healthcare identifying the risk of disease mortality, helps healthcare providers to effectively manage their patients by providing appropriate treatment options. In this study, we propose to apply a classification algorithm, Contrast Pattern Aided Logistic Regression (CPXR(Log)) with the probabilistic loss function, to develop and validate prognostic risk models to predict 1, 2, and 5year survival in heart failure (HF) using data from electronic health records (EHRs) at Mayo Clinic. The CPXR(Log) constructs a pattern aided logistic regression model defined by several patterns and corresponding local logistic regression models. One of the models generated by CPXR(Log) achieved an AUC and accuracy of 0.94 and 0.91, respectively, and significantly outperformed prognostic models reported in prior studies. Data extracted from EHRs allowed incorporation of patient co-morbidities into our models which helped improve the performance of the CPXR(Log) models (15.9% AUC improvement), although did not improve the accuracy of the models built by other classifiers. We also propose a probabilistic loss function to determine the large error and small error instances. The new loss function used in the algorithm outperforms other functions used in the previous studies by 1% improvement in the AUC. This study revealed that using EHR data to build prediction models can be very challenging using existing classification methods due to the high dimensionality and complexity of EHR data. The risk models developed by CPXR(Log) also reveal that HF is a highly heterogeneous disease, i.e., different subgroups of HF patients require different types of considerations with their diagnosis and treatment. Our risk models provided two valuable insights for application of predictive modeling techniques in biomedicine: Logistic risk models often make systematic prediction errors, and it is prudent to use subgroup based prediction models such as those given by CPXR(Log) when investigating heterogeneous diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

Market effects on electronic health record adoption by physicians.

PubMed

Abdolrasulnia, Maziar; Menachemi, Nir; Shewchuk, Richard M; Ginter, Peter M; Duncan, W Jack; Brooks, Robert G

2008-01-01

Despite the advantages of electronic health record (EHR) systems, the adoption of these systems has been slow among community-based physicians. Current studies have examined organizational and personal barriers to adoption; however, the influence of market characteristics has not been studied. The purpose of this study was to measure the effects of market characteristics on EHR adoption by physicians. Generalized hierarchal linear modeling was used to analyze EHR survey data from Florida which were combined with data from the Area Resource File and the Florida Office of Insurance Regulation. The main outcome variable was self-reported use of EHR by physicians. A total of 2,926 physicians from practice sizes of 20 or less were included in the sample. Twenty-one percent (n = 613) indicated that they personally and routinely use an EHR system in their practice. Physicians located in counties with higher physician concentration were found to be more likely to adopt EHRs. For every one-unit increase in nonfederal physicians per 10,000 in the county, there was a 2.0% increase in likelihood of EHR adoption by physicians (odds ratio = 1.02, confidence interval = 1.00-1.03). Health maintenance organization penetration rate and poverty level were not found to be significantly related to EHR adoption. However, practice size, years in practice, Medicare payer mix, and measures of technology readiness were found to independently influence physician adoption. Market factors play an important role in the diffusion of EHRs in small medical practices. Policy makers interested in furthering the adoption of EHRs must consider strategies that would enhance the confidence of users as well as provide financial support in areas with the highest concentration of small medical practices and Medicare beneficiaries. Health care leaders should be cognizant of the market forces that enable or constrain the adoption of EHR among their practices and those of their competitors.

Using the landmark method for creating prediction models in large datasets derived from electronic health records.

PubMed

Wells, Brian J; Chagin, Kevin M; Li, Liang; Hu, Bo; Yu, Changhong; Kattan, Michael W

2015-03-01

With the integration of electronic health records (EHRs), health data has become easily accessible and abounded. The EHR has the potential to provide important healthcare information to researchers by creating study cohorts. However, accessing this information comes with three major issues: 1) Predictor variables often change over time, 2) Patients have various lengths of follow up within the EHR, and 3) the size of the EHR data can be computationally challenging. Landmark analyses provide a perfect complement to EHR data and help to alleviate these three issues. We present two examples that utilize patient birthdays as landmark times for creating dynamic datasets for predicting clinical outcomes. The use of landmark times help to solve these three issues by incorporating information that changes over time, by creating unbiased reference points that are not related to a patient's exposure within the EHR, and reducing the size of a dataset compared to true time-varying analysis. These techniques are shown using two example cohort studies from the Cleveland Clinic that utilized 4.5 million and 17,787 unique patients, respectively.

Big Data, Predictive Analytics, and Quality Improvement in Kidney Transplantation: A Proof of Concept.

PubMed

Srinivas, T R; Taber, D J; Su, Z; Zhang, J; Mour, G; Northrup, D; Tripathi, A; Marsden, J E; Moran, W P; Mauldin, P D

2017-03-01

We sought proof of concept of a Big Data Solution incorporating longitudinal structured and unstructured patient-level data from electronic health records (EHR) to predict graft loss (GL) and mortality. For a quality improvement initiative, GL and mortality prediction models were constructed using baseline and follow-up data (0-90 days posttransplant; structured and unstructured for 1-year models; data up to 1 year for 3-year models) on adult solitary kidney transplant recipients transplanted during 2007-2015 as follows: Model 1: United Network for Organ Sharing (UNOS) data; Model 2: UNOS & Transplant Database (Tx Database) data; Model 3: UNOS, Tx Database & EHR comorbidity data; and Model 4: UNOS, Tx Database, EHR data, Posttransplant trajectory data, and unstructured data. A 10% 3-year GL rate was observed among 891 patients (2007-2015). Layering of data sources improved model performance; Model 1: area under the curve (AUC), 0.66; (95% confidence interval [CI]: 0.60, 0.72); Model 2: AUC, 0.68; (95% CI: 0.61-0.74); Model 3: AUC, 0.72; (95% CI: 0.66-077); Model 4: AUC, 0.84, (95 % CI: 0.79-0.89). One-year GL (AUC, 0.87; Model 4) and 3-year mortality (AUC, 0.84; Model 4) models performed similarly. A Big Data approach significantly adds efficacy to GL and mortality prediction models and is EHR deployable to optimize outcomes. © 2016 The American Society of Transplantation and the American Society of Transplant Surgeons.

Electronic health records. A systematic review on quality requirements.

PubMed

Hoerbst, A; Ammenwerth, E

2010-01-01

Since the first concepts for electronic health records (EHRs) in the 1990s, the content, structure, and technology of such records were frequently changed and adapted. The basic idea to support and enhance health care stayed the same over time. To reach these goals, it is crucial that EHRs themselves adhere to rigid quality requirements. The present review aims at describing the currently available, mainly non-functional, quality requirements with regard to electronic health records. A combined approach - systematic literature analysis and expert interviews - was used. The literature analysis as well as the expert interviews included sources/experts from different domains such as standards and norms, scientific literature and guidelines, and best practice. The expert interviews were performed by using problem-centric qualitative computer-assisted telephone interviews (CATIs) or face-to-face interviews. All of the data that was obtained was analyzed using qualitative content analysis techniques. In total, more than 1200 requirements were identified of which 203 requirements were also mentioned during the expert interviews. The requirements are organized according to the ISO 9126 and the eEurope 2002 criteria. Categories with the highest number of requirements found include global requirements, (general) functional requirements and data security. The number of non-functional requirements found is by contrast lower. The manuscript gives comprehensive insight into the currently available, primarily non-functional, EHR requirements. To our knowledge, there are no other publications that have holistically reported on this topic. The requirements identified can be used in different ways, e.g. the conceptual design, the development of EHR systems, as a starting point for further refinement or as a basis for the development of specific sets of requirements.

Nursing constraint models for electronic health records: a vision for domain knowledge governance.

PubMed

Hovenga, Evelyn; Garde, Sebastian; Heard, Sam

2005-12-01

Various forms of electronic health records (EHRs) are currently being introduced in several countries. Nurses are primary stakeholders and need to ensure that their information and knowledge needs are being met by such systems information sharing between health care providers to enable them to improve the quality and efficiency of health care service delivery for all subjects of care. The latest international EHR standards have adopted the openEHR approach of two-level modelling. The first level is a stable information model determining structure, while the second level consists of constraint models or 'archetypes' that reflect the specifications or clinician rules for how clinical information needs to be represented to enable unambiguous data sharing. The current state of play in terms of international health informatics standards development activities is providing the nursing profession with a unique opportunity and challenge. Much work has been undertaken internationally in the area of nursing terminologies and evidence-based practice. This paper argues that to make the most of these emerging technologies and EHRs we must now concentrate on developing a process to identify, document, implement, manage and govern our nursing domain knowledge as well as contribute to the development of relevant international standards. It is argued that one comprehensive nursing terminology, such as the ICNP or SNOMED CT is simply too complex and too difficult to maintain. As the openEHR archetype approach does not rely heavily on big standardised terminologies, it offers more flexibility during standardisation of clinical concepts and it ensures open, future-proof electronic health records. We conclude that it is highly desirable for the nursing profession to adopt this openEHR approach as a means of documenting and governing the nursing profession's domain knowledge. It is essential for the nursing profession to develop its domain knowledge constraint models (archetypes) collaboratively in an international context.

Evidence-based management of ambulatory electronic health record system implementation: an assessment of conceptual support and qualitative evidence.

PubMed

McAlearney, Ann Scheck; Hefner, Jennifer L; Sieck, Cynthia; Rizer, Milisa; Huerta, Timothy R

2014-07-01

While electronic health record (EHR) systems have potential to drive improvements in healthcare, a majority of EHR implementations fall short of expectations. Shortcomings in implementations are often due to organizational issues around the implementation process rather than technological problems. Evidence from both the information technology and healthcare management literature can be applied to improve the likelihood of implementation success, but the translation of this evidence into practice has not been widespread. Our objective was to comprehensively study and synthesize best practices for managing ambulatory EHR system implementation in healthcare organizations, highlighting applicable management theories and successful strategies. We held 45 interviews with key informants in six U.S. healthcare organizations purposively selected based on reported success with ambulatory EHR implementation. We also conducted six focus groups comprised of 37 physicians. Interview and focus group transcripts were analyzed using both deductive and inductive methods to answer research questions and explore emergent themes. We suggest that successful management of ambulatory EHR implementation can be guided by the Plan-Do-Study-Act (PDSA) quality improvement (QI) model. While participants did not acknowledge nor emphasize use of this model, we found evidence that successful implementation practices could be framed using the PDSA model. Additionally, successful sites had three strategies in common: 1) use of evidence from published health information technology (HIT) literature emphasizing implementation facilitators; 2) focusing on workflow; and 3) incorporating critical management factors that facilitate implementation. Organizations seeking to improve ambulatory EHR implementation processes can use frameworks such as the PDSA QI model to guide efforts and provide a means to formally accommodate new evidence over time. Implementing formal management strategies and incorporating new evidence through the PDSA model is a key element of evidence-based management and a crucial way for organizations to position themselves to proactively address implementation and use challenges before they are exacerbated. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

An Enterprise Architecture Perspective to Electronic Health Record Based Care Governance.

PubMed

Motoc, Bogdan

2017-01-01

This paper proposes an Enterprise Architecture viewpoint of Electronic Health Record (EHR) based care governance. The improvements expected are derived from the collaboration framework and the clinical health model proposed as foundation for the concept of EHR.

A Distributed Ensemble Approach for Mining Healthcare Data under Privacy Constraints

PubMed Central

Li, Yan; Bai, Changxin; Reddy, Chandan K.

2015-01-01

In recent years, electronic health records (EHRs) have been widely adapted at many healthcare facilities in an attempt to improve the quality of patient care and increase the productivity and efficiency of healthcare delivery. These EHRs can accurately diagnose diseases if utilized appropriately. While the EHRs can potentially resolve many of the existing problems associated with disease diagnosis, one of the main obstacles in effectively using them is the patient privacy and sensitivity of the medical information available in the EHR. Due to these concerns, even if the EHRs are available for storage and retrieval purposes, sharing of the patient records between different healthcare facilities has become a major concern and has hampered some of the effective advantages of using EHRs. Due to this lack of data sharing, most of the facilities aim at building clinical decision support systems using limited amount of patient data from their own EHR systems to provide important diagnosis related decisions. It becomes quite infeasible for a newly established healthcare facility to build a robust decision making system due to the lack of sufficient patient records. However, to make effective decisions from clinical data, it is indispensable to have large amounts of data to train the decision models. In this regard, there are conflicting objectives of preserving patient privacy and having sufficient data for modeling and decision making. To handle such disparate goals, we develop two adaptive distributed privacy-preserving algorithms based on a distributed ensemble strategy. The basic idea of our approach is to build an elegant model for each participating facility to accurately learn the data distribution, and then can transfer the useful healthcare knowledge acquired on their data from these participators in the form of their own decision models without revealing and sharing the patient-level sensitive data, thus protecting patient privacy. We demonstrate that our approach can successfully build accurate and robust prediction models, under privacy constraints, using the healthcare data collected from different geographical locations. We demonstrate the performance of our method using the Type-2 diabetes EHRs accumulated from multiple sources from all fifty states in the U.S. Our method was evaluated on diagnosing diabetes in the presence of insufficient number of patient records from certain regions without revealing the actual patient data from other regions. Using the proposed approach, we also discovered the important biomarkers, both universal and region-specific, and validated the selected biomarkers using the biomedical literature. PMID:26681811

A Distributed Ensemble Approach for Mining Healthcare Data under Privacy Constraints.

PubMed

Li, Yan; Bai, Changxin; Reddy, Chandan K

2016-02-10

In recent years, electronic health records (EHRs) have been widely adapted at many healthcare facilities in an attempt to improve the quality of patient care and increase the productivity and efficiency of healthcare delivery. These EHRs can accurately diagnose diseases if utilized appropriately. While the EHRs can potentially resolve many of the existing problems associated with disease diagnosis, one of the main obstacles in effectively using them is the patient privacy and sensitivity of the medical information available in the EHR. Due to these concerns, even if the EHRs are available for storage and retrieval purposes, sharing of the patient records between different healthcare facilities has become a major concern and has hampered some of the effective advantages of using EHRs. Due to this lack of data sharing, most of the facilities aim at building clinical decision support systems using limited amount of patient data from their own EHR systems to provide important diagnosis related decisions. It becomes quite infeasible for a newly established healthcare facility to build a robust decision making system due to the lack of sufficient patient records. However, to make effective decisions from clinical data, it is indispensable to have large amounts of data to train the decision models. In this regard, there are conflicting objectives of preserving patient privacy and having sufficient data for modeling and decision making. To handle such disparate goals, we develop two adaptive distributed privacy-preserving algorithms based on a distributed ensemble strategy. The basic idea of our approach is to build an elegant model for each participating facility to accurately learn the data distribution, and then can transfer the useful healthcare knowledge acquired on their data from these participators in the form of their own decision models without revealing and sharing the patient-level sensitive data, thus protecting patient privacy. We demonstrate that our approach can successfully build accurate and robust prediction models, under privacy constraints, using the healthcare data collected from different geographical locations. We demonstrate the performance of our method using the Type-2 diabetes EHRs accumulated from multiple sources from all fifty states in the U.S. Our method was evaluated on diagnosing diabetes in the presence of insufficient number of patient records from certain regions without revealing the actual patient data from other regions. Using the proposed approach, we also discovered the important biomarkers, both universal and region-specific, and validated the selected biomarkers using the biomedical literature.

Archetype modeling methodology.

PubMed

Moner, David; Maldonado, José Alberto; Robles, Montserrat

2018-03-01

Clinical Information Models (CIMs) expressed as archetypes play an essential role in the design and development of current Electronic Health Record (EHR) information structures. Although there exist many experiences about using archetypes in the literature, a comprehensive and formal methodology for archetype modeling does not exist. Having a modeling methodology is essential to develop quality archetypes, in order to guide the development of EHR systems and to allow the semantic interoperability of health data. In this work, an archetype modeling methodology is proposed. This paper describes its phases, the inputs and outputs of each phase, and the involved participants and tools. It also includes the description of the possible strategies to organize the modeling process. The proposed methodology is inspired by existing best practices of CIMs, software and ontology development. The methodology has been applied and evaluated in regional and national EHR projects. The application of the methodology provided useful feedback and improvements, and confirmed its advantages. The conclusion of this work is that having a formal methodology for archetype development facilitates the definition and adoption of interoperable archetypes, improves their quality, and facilitates their reuse among different information systems and EHR projects. Moreover, the proposed methodology can be also a reference for CIMs development using any other formalism. Copyright © 2018 Elsevier Inc. All rights reserved.

The Journey through Grief: Insights from a Qualitative Study of Electronic Health Record Implementation

PubMed Central

McAlearney, Ann Scheck; Hefner, Jennifer L; Sieck, Cynthia J; Huerta, Timothy R

2015-01-01

Objective To improve understanding of facilitators of EHR system implementation, paying particular attention to opportunities to maximize physician adoption and effective deployment. Data Sources/Study Setting Primary data collected from 47 physician and 35 administrative key informants from six U.S. health care organizations identified because of purported success with EHR implementation. Study Design We conducted interviews and focus groups in an extensive qualitative study. Data Collection/Extraction Methods Verbatim transcripts were analyzed both deductively and inductively using the constant comparative method. Principal Findings Conceptualizing EHR adoption as loss through the lens of Kübler-Ross's five stages of grief model may help individuals and organizations more effectively orient to the challenge of change. Coupled with Kotter's eight-step change management framework, we offer a structure to facilitate organizations' movement through the EHR implementation journey. Combining insights from these frameworks, we identify 10 EHR strategies that can help address EHR implementation barriers. Conclusions Loss is one part of change often overlooked. Addressing it directly and compassionately can potentially facilitate the EHR implementation journey. We offer a summarized list of deployment strategies that are sensitive to these issues to support physician transition to new technologies that will bring value to clinical practice. PMID:25219627

Quantifying predictive capability of electronic health records for the most harmful breast cancer

NASA Astrophysics Data System (ADS)

Wu, Yirong; Fan, Jun; Peissig, Peggy; Berg, Richard; Tafti, Ahmad Pahlavan; Yin, Jie; Yuan, Ming; Page, David; Cox, Jennifer; Burnside, Elizabeth S.

2018-03-01

Improved prediction of the "most harmful" breast cancers that cause the most substantive morbidity and mortality would enable physicians to target more intense screening and preventive measures at those women who have the highest risk; however, such prediction models for the "most harmful" breast cancers have rarely been developed. Electronic health records (EHRs) represent an underused data source that has great research and clinical potential. Our goal was to quantify the value of EHR variables in the "most harmful" breast cancer risk prediction. We identified 794 subjects who had breast cancer with primary non-benign tumors with their earliest diagnosis on or after 1/1/2004 from an existing personalized medicine data repository, including 395 "most harmful" breast cancer cases and 399 "least harmful" breast cancer cases. For these subjects, we collected EHR data comprised of 6 components: demographics, diagnoses, symptoms, procedures, medications, and laboratory results. We developed two regularized prediction models, Ridge Logistic Regression (Ridge-LR) and Lasso Logistic Regression (Lasso-LR), to predict the "most harmful" breast cancer one year in advance. The area under the ROC curve (AUC) was used to assess model performance. We observed that the AUCs of Ridge-LR and Lasso-LR models were 0.818 and 0.839 respectively. For both the Ridge-LR and LassoLR models, the predictive performance of the whole EHR variables was significantly higher than that of each individual component (p<0.001). In conclusion, EHR variables can be used to predict the "most harmful" breast cancer, providing the possibility to personalize care for those women at the highest risk in clinical practice.

Quantifying predictive capability of electronic health records for the most harmful breast cancer.

PubMed

Wu, Yirong; Fan, Jun; Peissig, Peggy; Berg, Richard; Tafti, Ahmad Pahlavan; Yin, Jie; Yuan, Ming; Page, David; Cox, Jennifer; Burnside, Elizabeth S

2018-02-01

Improved prediction of the "most harmful" breast cancers that cause the most substantive morbidity and mortality would enable physicians to target more intense screening and preventive measures at those women who have the highest risk; however, such prediction models for the "most harmful" breast cancers have rarely been developed. Electronic health records (EHRs) represent an underused data source that has great research and clinical potential. Our goal was to quantify the value of EHR variables in the "most harmful" breast cancer risk prediction. We identified 794 subjects who had breast cancer with primary non-benign tumors with their earliest diagnosis on or after 1/1/2004 from an existing personalized medicine data repository, including 395 "most harmful" breast cancer cases and 399 "least harmful" breast cancer cases. For these subjects, we collected EHR data comprised of 6 components: demographics, diagnoses, symptoms, procedures, medications, and laboratory results. We developed two regularized prediction models, Ridge Logistic Regression (Ridge-LR) and Lasso Logistic Regression (Lasso-LR), to predict the "most harmful" breast cancer one year in advance. The area under the ROC curve (AUC) was used to assess model performance. We observed that the AUCs of Ridge-LR and Lasso-LR models were 0.818 and 0.839 respectively. For both the Ridge-LR and Lasso-LR models, the predictive performance of the whole EHR variables was significantly higher than that of each individual component (p<0.001). In conclusion, EHR variables can be used to predict the "most harmful" breast cancer, providing the possibility to personalize care for those women at the highest risk in clinical practice.

Impact of the HITECH financial incentives on EHR adoption in small, physician-owned practices.

PubMed

Cohen, Martin F

2016-10-01

Physicians in small physician-owned practices in the United States have been slower to adopt EHRs than physicians in large practices or practices owned by large organizations. The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 included provisions intended to address many of the potential barriers to EHR adoption cited in the literature, including a financial incentives program that has paid physicians and other professionals $13 billion through December 2015. Given the range of factors that may be influencing physicians' decisions on whether to adopt an EHR, and given the level of HITECH expenditures to date, there is significant policy value in assessing whether the HITECH incentives have actually had an impact on EHR adoption decisions among U.S. physicians in small, physician-owned practices. This study addresses this question by analyzing physicians' own views on the influence of the HITECH incentives as well as other potential considerations in their decision-making on whether to adopt an EHR. Using data from a national survey of physicians, five composite scales were created from groups of survey items to reflect physician views on different potential facilitators and barriers for EHR adoption as of 2011, after the launch of the HITECH incentives program. Multinomial and binary logistic regression models were specified to test which of these physician-reported considerations have a significant relationship with EHR adoption status among 1043 physicians working in physician-owned practices with no more than 10 physicians. Physicians' views on the importance of the HITECH financial incentives are strongly associated with EHR adoption during the first three years of the HITECH period (2010-2012). In the study's primary model, a one-point increase on a three-point scale for physician-reported influence of the HITECH financial incentives increases the relative risk of being in the process of adoption in 2011, compared to the risk of remaining a non-adopter, by a factor of 4.02 (p<0.001, 95% CI of 2.06-7.85). In a second model which excludes pre-HITECH adopters from the data, a one-point increase on the incentives scale increases the relative risk of having become a new EHR user in 2010 or 2011, compared to the risk of remaining a non-adopter, by a factor of 3.98 (p<0.01, 95% CI of 1.48-10.68) and also increases the relative risk of being in the process of adoption in 2011 by a factor of 5.73 (p<0.001, 95% CI of 2.57-12.76), compared to the risk of remaining a non-adopter in 2011. In contrast, a composite scale that reflects whether physicians viewed choosing a specific EHR vendor as challenging is not associated with adoption status. This study's principal finding is that the HITECH financial incentives were influential in accelerating EHR adoption among small, physician-owned practices in the United States. A second finding is that physician decision-making on EHR adoption in the United States has not matched what would be predicted by the literature on network effects. The market's failure to converge on a dominant design in the absence of interoperability means it will be difficult to achieve widespread exchange of patients' clinical information among different health care provider organizations. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Developing the First Generally-Available openEHR Archetypes and Templates for Physiotherapy: An Example of Building Clinical Models and Modelling Capacity via Student-Led Academic-Industrial Collaboration.

PubMed

Chihab, Jamila; Franke, Hildegard; McNicoll, Ian; Darlison, Matthew W

2017-01-01

We present the first public openEHR archetypes and templates for physiotherapy, and the context of multidisciplinary academic-industry partnership that has enabled their production by a team led by a clinically trained student on the UCL health informatics MSc programme.

LinkEHR-Ed: a multi-reference model archetype editor based on formal semantics.

PubMed

Maldonado, José A; Moner, David; Boscá, Diego; Fernández-Breis, Jesualdo T; Angulo, Carlos; Robles, Montserrat

2009-08-01

To develop a powerful archetype editing framework capable of handling multiple reference models and oriented towards the semantic description and standardization of legacy data. The main prerequisite for implementing tools providing enhanced support for archetypes is the clear specification of archetype semantics. We propose a formalization of the definition section of archetypes based on types over tree-structured data. It covers the specialization of archetypes, the relationship between reference models and archetypes and conformance of data instances to archetypes. LinkEHR-Ed, a visual archetype editor based on the former formalization with advanced processing capabilities that supports multiple reference models, the editing and semantic validation of archetypes, the specification of mappings to data sources, and the automatic generation of data transformation scripts, is developed. LinkEHR-Ed is a useful tool for building, processing and validating archetypes based on any reference model.

Impact of the HITECH Act on physicians' adoption of electronic health records.

PubMed

Mennemeyer, Stephen T; Menachemi, Nir; Rahurkar, Saurabh; Ford, Eric W

2016-03-01

The Health Information Technology for Economic and Clinical Health (HITECH) Act has distributed billions of dollars to physicians as incentives for adopting certified electronic health records (EHRs) through the meaningful use (MU) program ultimately aimed at improving healthcare outcomes. The authors examine the extent to which the MU program impacted the EHR adoption curve that existed prior to the Act. Bass and Gamma Shifted Gompertz (G/SG) diffusion models of the adoption of "Any" and "Basic" EHR systems in physicians' offices using consistent data series covering 2001-2013 and 2006-2013, respectively, are estimated to determine if adoption was stimulated during either a PrePay (2009-2010) period of subsidy anticipation or a PostPay (2011-2013) period when payments were actually made. Adoption of Any EHR system may have increased by as much as 7 percentage points above the level predicted in the absence of the MU subsidies. This estimate, however, lacks statistical significance and becomes smaller or negative under alternative model specifications. No substantial effects are found for Basic systems. The models suggest that adoption was largely driven by "imitation" effects (q-coefficient) as physicians mimic their peers' technology use or respond to mandates. Small and often insignificant "innovation" effects (p-coefficient) are found suggesting little enthusiasm by physicians who are leaders in technology adoption. The authors find weak evidence of the impact of the MU program on EHR uptake. This is consistent with reports that many current EHR systems reduce physician productivity, lack data sharing capabilities, and need to incorporate other key interoperability features (e.g., application program interfaces). © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Personalized-detailed clinical model for data interoperability among clinical standards.

PubMed

Khan, Wajahat Ali; Hussain, Maqbool; Afzal, Muhammad; Amin, Muhammad Bilal; Saleem, Muhammad Aamir; Lee, Sungyoung

2013-08-01

Data interoperability among health information exchange (HIE) systems is a major concern for healthcare practitioners to enable provisioning of telemedicine-related services. Heterogeneity exists in these systems not only at the data level but also among different heterogeneous healthcare standards with which these are compliant. The relationship between healthcare organization data and different heterogeneous standards is necessary to achieve the goal of data level interoperability. We propose a personalized-detailed clinical model (P-DCM) approach for the generation of customized mappings that creates the necessary linkage between organization-conformed healthcare standards concepts and clinical model concepts to ensure data interoperability among HIE systems. We consider electronic health record (EHR) standards, openEHR, and HL7 CDA instances transformation using P-DCM. P-DCM concepts associated with openEHR and HL7 CDA help in transformation of instances among these standards. We investigated two datasets: (1) data of 100 diabetic patients, including 50 each of type 1 and type 2, from a local hospital in Korea and (2) data of a single Alzheimer's disease patient. P-DCMs were created for both scenarios, which provided the basis for deriving instances for HL7 CDA and openEHR standards. For proof of concept, we present case studies of encounter information for type 2 diabetes mellitus patients and monitoring of daily routine activities of an Alzheimer's disease patient. These reflect P-DCM-based customized mappings generation with openEHR and HL7 CDA standards. Customized mappings are generated based on the relationship of P-DCM concepts with CDA and openEHR concepts. The objective of this work is to achieve semantic data interoperability among heterogeneous standards. This would lead to effective utilization of resources and allow timely information exchange among healthcare systems.

Personalized-Detailed Clinical Model for Data Interoperability Among Clinical Standards

PubMed Central

Khan, Wajahat Ali; Hussain, Maqbool; Afzal, Muhammad; Amin, Muhammad Bilal; Saleem, Muhammad Aamir

2013-01-01

Abstract Objective: Data interoperability among health information exchange (HIE) systems is a major concern for healthcare practitioners to enable provisioning of telemedicine-related services. Heterogeneity exists in these systems not only at the data level but also among different heterogeneous healthcare standards with which these are compliant. The relationship between healthcare organization data and different heterogeneous standards is necessary to achieve the goal of data level interoperability. We propose a personalized-detailed clinical model (P-DCM) approach for the generation of customized mappings that creates the necessary linkage between organization-conformed healthcare standards concepts and clinical model concepts to ensure data interoperability among HIE systems. Materials and Methods: We consider electronic health record (EHR) standards, openEHR, and HL7 CDA instances transformation using P-DCM. P-DCM concepts associated with openEHR and HL7 CDA help in transformation of instances among these standards. We investigated two datasets: (1) data of 100 diabetic patients, including 50 each of type 1 and type 2, from a local hospital in Korea and (2) data of a single Alzheimer's disease patient. P-DCMs were created for both scenarios, which provided the basis for deriving instances for HL7 CDA and openEHR standards. Results: For proof of concept, we present case studies of encounter information for type 2 diabetes mellitus patients and monitoring of daily routine activities of an Alzheimer's disease patient. These reflect P-DCM-based customized mappings generation with openEHR and HL7 CDA standards. Customized mappings are generated based on the relationship of P-DCM concepts with CDA and openEHR concepts. Conclusions: The objective of this work is to achieve semantic data interoperability among heterogeneous standards. This would lead to effective utilization of resources and allow timely information exchange among healthcare systems. PMID:23875730

Model driven development of clinical information sytems using openEHR.

PubMed

Atalag, Koray; Yang, Hong Yul; Tempero, Ewan; Warren, Jim

2011-01-01

openEHR and the recent international standard (ISO 13606) defined a model driven software development methodology for health information systems. However there is little evidence in the literature describing implementation; especially for desktop clinical applications. This paper presents an implementation pathway using .Net/C# technology for Microsoft Windows desktop platforms. An endoscopy reporting application driven by openEHR Archetypes and Templates has been developed. A set of novel GUI directives has been defined and presented which guides the automatic graphical user interface generator to render widgets properly. We also reveal the development steps and important design decisions; from modelling to the final software product. This might provide guidance for other developers and form evidence required for the adoption of these standards for vendors and national programs alike.

Enabling locally-developed content for access through the infobutton by means of automated concept annotation.

PubMed

Hulse, Nathan C; Long, Jie; Xu, Xiaomin; Tao, Cui

2014-01-01

Infobuttons have proven to be an increasingly important resource in providing a standardized approach to integrating useful educational materials at the point of care in electronic health records (EHRs). They provide a simple, uniform pathway for both patients and providers to receive pertinent education materials in a quick fashion from within EHRs and Personalized Health Records (PHRs). In recent years, the international standards organization Health Level Seven has balloted and approved a standards-based pathway for requesting and receiving data for infobuttons, simplifying some of the barriers for their adoption in electronic medical records and amongst content providers. Local content, developed by the hosting organization themselves, still needs to be indexed and annotated with appropriate metadata and terminologies in order to be fully accessible via the infobutton. In this manuscript we present an approach for automating the annotation of internally-developed patient education sheets with standardized terminologies and compare and contrast the approach with manual approaches used previously. We anticipate that a combination of system-generated and human reviewed annotations will provide the most comprehensive and effective indexing strategy, thereby allowing best access to internally-created content via the infobutton.

Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts

PubMed Central

Fernández-Breis, Jesualdo Tomás; Maldonado, José Alberto; Marcos, Mar; Legaz-García, María del Carmen; Moner, David; Torres-Sospedra, Joaquín; Esteban-Gil, Angel; Martínez-Salvador, Begoña; Robles, Montserrat

2013-01-01

Background The secondary use of electronic healthcare records (EHRs) often requires the identification of patient cohorts. In this context, an important problem is the heterogeneity of clinical data sources, which can be overcome with the combined use of standardized information models, virtual health records, and semantic technologies, since each of them contributes to solving aspects related to the semantic interoperability of EHR data. Objective To develop methods allowing for a direct use of EHR data for the identification of patient cohorts leveraging current EHR standards and semantic web technologies. Materials and methods We propose to take advantage of the best features of working with EHR standards and ontologies. Our proposal is based on our previous results and experience working with both technological infrastructures. Our main principle is to perform each activity at the abstraction level with the most appropriate technology available. This means that part of the processing will be performed using archetypes (ie, data level) and the rest using ontologies (ie, knowledge level). Our approach will start working with EHR data in proprietary format, which will be first normalized and elaborated using EHR standards and then transformed into a semantic representation, which will be exploited by automated reasoning. Results We have applied our approach to protocols for colorectal cancer screening. The results comprise the archetypes, ontologies, and datasets developed for the standardization and semantic analysis of EHR data. Anonymized real data have been used and the patients have been successfully classified by the risk of developing colorectal cancer. Conclusions This work provides new insights in how archetypes and ontologies can be effectively combined for EHR-driven phenotyping. The methodological approach can be applied to other problems provided that suitable archetypes, ontologies, and classification rules can be designed. PMID:23934950

Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: the SHARPn project.

PubMed

Rea, Susan; Pathak, Jyotishman; Savova, Guergana; Oniki, Thomas A; Westberg, Les; Beebe, Calvin E; Tao, Cui; Parker, Craig G; Haug, Peter J; Huff, Stanley M; Chute, Christopher G

2012-08-01

The Strategic Health IT Advanced Research Projects (SHARP) Program, established by the Office of the National Coordinator for Health Information Technology in 2010 supports research findings that remove barriers for increased adoption of health IT. The improvements envisioned by the SHARP Area 4 Consortium (SHARPn) will enable the use of the electronic health record (EHR) for secondary purposes, such as care process and outcomes improvement, biomedical research and epidemiologic monitoring of the nation's health. One of the primary informatics problem areas in this endeavor is the standardization of disparate health data from the nation's many health care organizations and providers. The SHARPn team is developing open source services and components to support the ubiquitous exchange, sharing and reuse or 'liquidity' of operational clinical data stored in electronic health records. One year into the design and development of the SHARPn framework, we demonstrated end to end data flow and a prototype SHARPn platform, using thousands of patient electronic records sourced from two large healthcare organizations: Mayo Clinic and Intermountain Healthcare. The platform was deployed to (1) receive source EHR data in several formats, (2) generate structured data from EHR narrative text, and (3) normalize the EHR data using common detailed clinical models and Consolidated Health Informatics standard terminologies, which were (4) accessed by a phenotyping service using normalized data specifications. The architecture of this prototype SHARPn platform is presented. The EHR data throughput demonstration showed success in normalizing native EHR data, both structured and narrative, from two independent organizations and EHR systems. Based on the demonstration, observed challenges for standardization of EHR data for interoperable secondary use are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: The SHARPn project

PubMed Central

Rea, Susan; Pathak, Jyotishman; Savova, Guergana; Oniki, Thomas A.; Westberg, Les; Beebe, Calvin E.; Tao, Cui; Parker, Craig G.; Haug, Peter J.; Huff, Stanley M.; Chute, Christopher G.

2016-01-01

The Strategic Health IT Advanced Research Projects (SHARP) Program, established by the Office of the National Coordinator for Health Information Technology in 2010 supports research findings that remove barriers for increased adoption of health IT. The improvements envisioned by the SHARP Area 4 Consortium (SHARPn) will enable the use of the electronic health record (EHR) for secondary purposes, such as care process and outcomes improvement, biomedical research and epidemiologic monitoring of the nation’s health. One of the primary informatics problem areas in this endeavor is the standardization of disparate health data from the nation’s many health care organizations and providers. The SHARPn team is developing open source services and components to support the ubiquitous exchange, sharing and reuse or ‘liquidity’ of operational clinical data stored in electronic health records. One year into the design and development of the SHARPn framework, we demonstrated end to end data flow and a prototype SHARPn platform, using thousands of patient electronic records sourced from two large healthcare organizations: Mayo Clinic and Intermountain Healthcare. The platform was deployed to (1) receive source EHR data in several formats, (2) generate structured data from EHR narrative text, and (3) normalize the EHR data using common detailed clinical models and Consolidated Health Informatics standard terminologies, which were (4) accessed by a phenotyping service using normalized data specifications. The architecture of this prototype SHARPn platform is presented. The EHR data throughput demonstration showed success in normalizing native EHR data, both structured and narrative, from two independent organizations and EHR systems. Based on the demonstration, observed challenges for standardization of EHR data for interoperable secondary use are discussed. PMID:22326800

Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts.

PubMed

Fernández-Breis, Jesualdo Tomás; Maldonado, José Alberto; Marcos, Mar; Legaz-García, María del Carmen; Moner, David; Torres-Sospedra, Joaquín; Esteban-Gil, Angel; Martínez-Salvador, Begoña; Robles, Montserrat

2013-12-01

The secondary use of electronic healthcare records (EHRs) often requires the identification of patient cohorts. In this context, an important problem is the heterogeneity of clinical data sources, which can be overcome with the combined use of standardized information models, virtual health records, and semantic technologies, since each of them contributes to solving aspects related to the semantic interoperability of EHR data. To develop methods allowing for a direct use of EHR data for the identification of patient cohorts leveraging current EHR standards and semantic web technologies. We propose to take advantage of the best features of working with EHR standards and ontologies. Our proposal is based on our previous results and experience working with both technological infrastructures. Our main principle is to perform each activity at the abstraction level with the most appropriate technology available. This means that part of the processing will be performed using archetypes (ie, data level) and the rest using ontologies (ie, knowledge level). Our approach will start working with EHR data in proprietary format, which will be first normalized and elaborated using EHR standards and then transformed into a semantic representation, which will be exploited by automated reasoning. We have applied our approach to protocols for colorectal cancer screening. The results comprise the archetypes, ontologies, and datasets developed for the standardization and semantic analysis of EHR data. Anonymized real data have been used and the patients have been successfully classified by the risk of developing colorectal cancer. This work provides new insights in how archetypes and ontologies can be effectively combined for EHR-driven phenotyping. The methodological approach can be applied to other problems provided that suitable archetypes, ontologies, and classification rules can be designed.

Melinda – A custom search engine that provides access to locally-developed content using the HL7 Infobutton standard

PubMed Central

Wan, Yik-Ki J.; Staes, Catherine J.

2016-01-01

Healthcare organizations use care pathways to standardize care, but once developed, adoption rates often remain low. One challenge for usage concerns clinicians’ difficulty in accessing guidance when it is most needed. Although the HL7 ‘Infobutton Standard’ allows clinicians easier access to external references, access to locally-developed resources often requires clinicians to deviate from their normal electronic health record (EHR) workflow to use another application. To address this gap between internal and external resources, we reviewed the literature and existing practices at the University of Utah Health Care. We identify the requirements to meet the needs of a healthcare enterprise and clinicians, describe the design and development of a prototype to aggregate both internal and external resources from within or outside the EHR, and evaluated strengths and limitations of the prototype. The system is functional but not implemented in a live EHR environment. We suggest next steps and enhancements. PMID:28269964

A Standards-Based Architecture Proposal for Integrating Patient mHealth Apps to Electronic Health Record Systems.

PubMed

Marceglia, S; Fontelo, P; Rossi, E; Ackerman, M J

2015-01-01

Mobile health Applications (mHealth Apps) are opening the way to patients' responsible and active involvement with their own healthcare management. However, apart from Apps allowing patient's access to their electronic health records (EHRs), mHealth Apps are currently developed as dedicated "island systems". Although much work has been done on patient's access to EHRs, transfer of information from mHealth Apps to EHR systems is still low. This study proposes a standards-based architecture that can be adopted by mHealth Apps to exchange information with EHRs to support better quality of care. Following the definition of requirements for the EHR/mHealth App information exchange recently proposed, and after reviewing current standards, we designed the architecture for EHR/mHealth App integration. Then, as a case study, we modeled a system based on the proposed architecture aimed to support home monitoring for congestive heart failure patients. We simulated such process using, on the EHR side, OpenMRS, an open source longitudinal EHR and, on the mHealth App side, the iOS platform. The integration architecture was based on the bi-directional exchange of standard documents (clinical document architecture rel2 - CDA2). In the process, the clinician "prescribes" the home monitoring procedures by creating a CDA2 prescription in the EHR that is sent, encrypted and de-identified, to the mHealth App to create the monitoring calendar. At the scheduled time, the App alerts the patient to start the monitoring. After the measurements are done, the App generates a structured CDA2-compliant monitoring report and sends it to the EHR, thus avoiding local storage. The proposed architecture, even if validated only in a simulation environment, represents a step forward in the integration of personal mHealth Apps into the larger health-IT ecosystem, allowing the bi-directional data exchange between patients and healthcare professionals, supporting the patient's engagement in self-management and self-care.

The Effect of Electronic Health Record Use and Patient-Centered Communication on Cancer Screening Behavior: An Analysis of the Health Information National Trends Survey.

PubMed

Totzkay, Daniel; Silk, Kami J; Sheff, Sarah E

2017-07-01

The present study used the 2013 Health Information National Trends Survey (N = 3185) to examine the effects of patient-centered communication (PCC) and the use of electronic health records (EHRs) on the likelihood of patients receiving a recommended screening for cancer (i.e., mammogram, PSA test). Self-determination theory, a framework of self-initiated extrinsic behaviors, was applied to test mediation models of PCC and EHR use, respectively, through patient activation. The results demonstrated that PCC and EHR use predicted cancer screening (mediated through patient activation), but only for women recommended for biannual mammograms. The aforementioned relationship was not found for men who are recommended for prostate cancer screening. PCC and EHRs do appear to facilitate a patient's ability to take care of their own health, but only under certain circumstances. It was additionally found that men were more likely to report higher degrees of physician PCC when their physicians maintained an EHR, whereas women reported no difference. Future research should examine more nuanced personality factors that affect the perception of PCC in the presence of EHRs and the relationship between men's activation and likelihood of receiving a cancer screen.

A generative tool for building health applications driven by ISO 13606 archetypes.

PubMed

Menárguez-Tortosa, Marcos; Martínez-Costa, Catalina; Fernández-Breis, Jesualdo Tomás

2012-10-01

The use of Electronic Healthcare Records (EHR) standards in the development of healthcare applications is crucial for achieving the semantic interoperability of clinical information. Advanced EHR standards make use of the dual model architecture, which provides a solution for clinical interoperability based on the separation of the information and knowledge. However, the impact of such standards is biased by the limited availability of tools that facilitate their usage and practical implementation. In this paper, we present an approach for the automatic generation of clinical applications for the ISO 13606 EHR standard, which is based on the dual model architecture. This generator has been generically designed, so it can be easily adapted to other dual model standards and can generate applications for multiple technological platforms. Such good properties are based on the combination of standards for the representation of generic user interfaces and model-driven engineering techniques.

Progress along developmental tracks for electronic health records implementation in the United States

PubMed Central

Hollar, David W

2009-01-01

The development and implementation of electronic health records (EHR) have occurred slowly in the United States. To date, these approaches have, for the most part, followed four developmental tracks: (a) Enhancement of immunization registries and linkage with other health records to produce Child Health Profiles (CHP), (b) Regional Health Information Organization (RHIO) demonstration projects to link together patient medical records, (c) Insurance company projects linked to ICD-9 codes and patient records for cost-benefit assessments, and (d) Consortia of EHR developers collaborating to model systems requirements and standards for data linkage. Until recently, these separate efforts have been conducted in the very silos that they had intended to eliminate, and there is still considerable debate concerning health professionals access to as well as commitment to using EHR if these systems are provided. This paper will describe these four developmental tracks, patient rights and the legal environment for EHR, international comparisons, and future projections for EHR expansion across health networks in the United States. PMID:19291284

Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services

PubMed Central

Daniel, Christel; Ouagne, David; Sadou, Eric; Forsberg, Kerstin; Gilchrist, Mark Mc; Zapletal, Eric; Paris, Nicolas; Hussain, Sajjad; Jaulent, Marie-Christine; MD, Dipka Kalra

2016-01-01

With the development of platforms enabling the use of routinely collected clinical data in the context of international clinical research, scalable solutions for cross border semantic interoperability need to be developed. Within the context of the IMI EHR4CR project, we first defined the requirements and evaluation criteria of the EHR4CR semantic interoperability platform and then developed the semantic resources and supportive services and tooling to assist hospital sites in standardizing their data for allowing the execution of the project use cases. The experience gained from the evaluation of the EHR4CR platform accessing to semantically equivalent data elements across 11 European participating EHR systems from 5 countries demonstrated how far the mediation model and mapping efforts met the expected requirements of the project. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data. PMID:27570649

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature.

PubMed

Perez-Rey, David; Jimenez-Castellanos, Ana; Garcia-Remesal, Miguel; Crespo, Jose; Maojo, Victor

2012-04-05

Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset of HL7-CDA documents, returning significantly fewer citations since queries are focused on characteristics identified within the EHR. For instance, compared with more than 200,000 citations retrieved by breast neoplasm, fewer than ten citations were retrieved when ten patient features were added using CDAPubMed. This is an open source tool that can be freely used for non-profit purposes and integrated with other existing systems.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

PubMed Central

2012-01-01

Background Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. Results We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. Conclusions CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset of HL7-CDA documents, returning significantly fewer citations since queries are focused on characteristics identified within the EHR. For instance, compared with more than 200,000 citations retrieved by breast neoplasm, fewer than ten citations were retrieved when ten patient features were added using CDAPubMed. This is an open source tool that can be freely used for non-profit purposes and integrated with other existing systems. PMID:22480327

Design and Hospital-Wide Implementation of a Standardized Discharge Summary in an Electronic Health Record

PubMed Central

Dean, Shannon M; Gilmore-Bykovskyi, Andrea; Buchanan, Joel; Ehlenfeldt, Brad; Kind, Amy JH

2016-01-01

Background The hospital discharge summary is the primary method used to communicate a patient's plan of care to the next provider(s). Despite the existence of regulations and guidelines outlining the optimal content for the discharge summary and its importance in facilitating an effective transition to post-hospital care, incomplete discharge summaries remain a common problem that may contribute to poor post-hospital outcomes. Electronic health records (EHRs) are regularly used as a platform upon which standardization of content and format can be implemented. Objective We describe here the design and hospital-wide implementation of a standardized discharge summary using an EHR. Methods We employed the evidence-based Replicating Effective Programs implementation strategy to guide the development and implementation during this large-scale project. Results Within 18 months, 90% of all hospital discharge summaries were written using the standardized format. Hospital providers found the template helpful and easy to use, and recipient providers perceived an improvement in the quality of discharge summaries compared to those sent from our hospital previously. Conclusions Discharge summaries can be standardized and implemented hospital-wide with both author and recipient provider satisfaction, especially if evidence-based implementation strategies are employed. The use of EHR tools to guide clinicians in writing comprehensive discharge summaries holds promise in improving the existing deficits in communication at transitions of care. PMID:28334559

MDA-based EHR application security services.

PubMed

Blobel, Bernd; Pharow, Peter

2004-01-01

Component-oriented, distributed, virtual EHR systems have to meet enhanced security and privacy requirements. In the context of advanced architectural paradigms such as component-orientation, model-driven, and knowledge-based, standardised security services needed have to be specified and implemented in an integrated way following the same paradigm. This concerns the deployment of formal models, meta-languages, reference models such as the ISO RM-ODP, and development as well as implementation tools. International projects' results presented proceed on that streamline.

Assessing the relationship between patient safety culture and EHR strategy.

PubMed

Ford, Eric W; Silvera, Geoffrey A; Kazley, Abby S; Diana, Mark L; Huerta, Timothy R

2016-07-11

Purpose - The purpose of this paper is to explore the relationship between hospitals' electronic health record (EHR) adoption characteristics and their patient safety cultures. The "Meaningful Use" (MU) program is designed to increase hospitals' adoption of EHR, which will lead to better care quality, reduce medical errors, avoid unnecessary cost, and promote a patient safety culture. To reduce medical errors, hospital leaders have been encouraged to promote safety cultures common to high-reliability organizations. Expecting a positive relationship between EHR adoption and improved patient safety cultures appears sound in theory, but it has yet to be empirically demonstrated. Design/methodology/approach - Providers' perceptions of patient safety culture and counts of patient safety incidents are explored in relationship to hospital EHR adoption patterns. Multi-level modeling is employed to data drawn from the Agency for Healthcare Research and Quality's surveys on patient safety culture (level 1) and the American Hospital Association's survey and healthcare information technology supplement (level 2). Findings - The findings suggest that the early adoption of EHR capabilities hold a negative association to the number of patient safety events reported. However, this relationship was not present in providers' perceptions of overall patient safety cultures. These mixed results suggest that the understanding of the EHR-patient safety culture relationship needs further research. Originality/value - Relating EHR MU and providers' care quality attitudes is an important leading indicator for improved patient safety cultures. For healthcare facility managers and providers, the ability to effectively quantify the impact of new technologies on efforts to change organizational cultures is important for pinpointing clinical areas for process improvements.

Impact of a Web-Based Electronic Health Record on Behavioral Health Service Delivery for Children and Adolescents: Randomized Controlled Trial.

PubMed

Bruns, Eric J; Hook, Alyssa N; Parker, Elizabeth M; Esposito, Isabella; Sather, April; Parigoris, Ryan M; Lyon, Aaron R; Hyde, Kelly L

2018-06-14

Electronic health records (EHRs) have been widely proposed as a mechanism for improving health care quality. However, rigorous research on the impact of EHR systems on behavioral health service delivery is scant, especially for children and adolescents. The current study evaluated the usability of an EHR developed to support the implementation of the Wraparound care coordination model for children and youth with complex behavioral health needs, and impact of the EHR on service processes, fidelity, and proximal outcomes. Thirty-four Wraparound facilitators working in two programs in two states were randomized to either use the new EHR (19/34, 56%) or to continue to implement Wraparound services as usual (SAU) using paper-based documentation (15/34, 44%). Key functions of the EHR included standard fields such as youth and family information, diagnoses, assessment data, and progress notes. In addition, there was the maintenance of a coordinated plan of care, progress measurement on strategies and services, communication among team members, and reporting on services, expenditures, and outcomes. All children and youth referred to services for eight months (N=211) were eligible for the study. After excluding those who were ineligible (69/211, 33%) and who declined to participate (59/211, 28%), a total of 83/211 (39%) children and youth were enrolled in the study with 49/211 (23%) in the EHR condition and 34/211 (16%) in the SAU condition. Facilitators serving these youth and families and their supervisors completed measures of EHR usability and appropriateness, supervision processes and activities, work satisfaction, and use of and attitudes toward standardized assessments. Data from facilitators were collected by web survey and, where necessary, by phone interviews. Parents and caregivers completed measures via phone interviews. Related to fidelity and quality of behavioral health care, including Wraparound team climate, working alliance with providers, fidelity to the Wraparound model, and satisfaction with services. EHR-assigned facilitators from both sites demonstrated the robust use of the system. Facilitators in the EHR group reported spending significantly more time reviewing client progress (P=.03) in supervision, and less time overall sending reminders to youth/families (P=.04). A trend toward less time on administrative tasks (P=.098) in supervision was also found. Facilitators in both groups reported significantly increased use of measurement-based care strategies overall, which may reflect cross-group contamination (given that randomization of staff to the EHR occurred within agencies and supervisors supervised both types of staff). Although not significant at P<.05, there was a trend (P=.10) toward caregivers in the EHR group reporting poorer shared agreement on tasks on the measure of working alliance with providers. No other significant between-group differences were found. Results support the proposal that use of EHR systems can promote the use of client progress data and promote efficiency; however, there was little evidence of any impact (positive or negative) on overall service quality, fidelity, or client satisfaction. The field of children's behavioral health services would benefit from additional research on EHR systems using designs that include larger sample sizes and longer follow-up periods. ClinicalTrials.gov NCT02421874; https://clinicaltrials.gov/ct2/show/NCT02421874 (Archived by WebCite at http://www.webcitation.org/6yyGPJ3NA). ©Eric J Bruns, Alyssa N Hook, Elizabeth M Parker, Isabella Esposito, April Sather, Ryan M Parigoris, Aaron R Lyon, Kelly L Hyde. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 14.06.2018.

Patient and public attitudes towards informed consent models and levels of awareness of Electronic Health Records in the UK

PubMed Central

Riordan, Fiona; Papoutsi, Chrysanthi; Reed, Julie E.; Marston, Cicely; Bell, Derek; Majeed, Azeem

2015-01-01

Background The development of Electronic Health Records (EHRs) forms an integral part of the information strategy for the National Health Service (NHS) in the UK, with the aim of facilitating health information exchange for patient care and secondary use, including research and healthcare planning. Implementing EHR systems requires an understanding of patient expectations for consent mechanisms and consideration of public awareness towards information sharing as might be made possible through integrated EHRs across primary and secondary health providers. Objectives To explore levels of public awareness about EHRs and to examine attitudes towards different consent models with respect to sharing identifiable and de-identified records for healthcare provision, research and planning. Methods A cross-sectional questionnaire survey was administered to adult patients and members of the public in primary and secondary care clinics in West London, UK in 2011. In total, 5331 individuals participated in the survey, and 3157 were included in the final analysis. Results The majority (91%) of respondents expected to be explicitly asked for consent for their identifiable records to be accessed for health provision, research or planning. Half the respondents (49%) did not expect to be asked for consent before their de-identified records were accessed. Compared with White British respondents, those from all other ethnic groups were more likely to anticipate their permission would be obtained before their de-identified records were used. Of the study population, 59% reported already being aware of EHRs before the survey. Older respondents and individuals with complex patterns of interaction with healthcare services were more likely to report prior awareness of EHRs. Individuals self-identifying as belonging to ethnic groups other than White British, and those with lower educational qualifications were less likely to report being aware of EHRs than White British respondents and respondents with degree-level education, respectively. Those who reported being aware of EHRs were less likely to say they expected explicit consent to be sought before use of their de-identified record. Conclusions A large number of patients remain unaware of EHRs, while preference for implicit consent is stronger among those who report previous awareness. Differences in awareness levels and consent expectations between groups with different socio-demographic characteristics suggest that public education and information campaigns should target specific groups to increase public awareness and ensure meaningful informed consent mechanisms. PMID:25649841

Hospital financial position and the adoption of electronic health records.

PubMed

Ginn, Gregory O; Shen, Jay J; Moseley, Charles B

2011-01-01

The objective of this study was to examine the relationship between financial position and adoption of electronic health records (EHRs) in 2442 acute care hospitals. The study was cross-sectional and utilized a general linear mixed model with the multinomial distribution specification for data analysis. We verified the results by also running a multinomial logistic regression model. To measure our variables, we used data from (1) the 2007 American Hospital Association (AHA) electronic health record implementation survey, (2) the 2006 Centers for Medicare and Medicaid Cost Reports, and (3) the 2006 AHA Annual Survey containing organizational and operational data. Our dependent variable was an ordinal variable with three levels used to indicate the extent of EHR adoption by hospitals. Our independent variables were five financial ratios: (1) net days revenue in accounts receivable, (2) total margin, (3) the equity multiplier, (4) total asset turnover, and (5) the ratio of total payroll to total expenses. For control variables, we used (1) bed size, (2) ownership type, (3) teaching affiliation, (4) system membership, (5) network participation, (6) fulltime equivalent nurses per adjusted average daily census, (7) average daily census per staffed bed, (8) Medicare patients percentage, (9) Medicaid patients percentage, (10) capitation-based reimbursement, and (11) nonconcentrated market. Only liquidity was significant and positively associated with EHR adoption. Asset turnover ratio was significant but, unexpectedly, was negatively associated with EHR adoption. However, many control variables, most notably bed size, showed significant positive associations with EHR adoption. Thus, it seems that hospitals adopt EHRs as a strategic move to better align themselves with their environment.

Possibilities and Implications of Using the ICF and Other Vocabulary Standards in Electronic Health Records.

PubMed

Vreeman, Daniel J; Richoz, Christophe

2015-12-01

There is now widespread recognition of the powerful potential of electronic health record (EHR) systems to improve the health-care delivery system. The benefits of EHRs grow even larger when the health data within their purview are seamlessly shared, aggregated and processed across different providers, settings and institutions. Yet, the plethora of idiosyncratic conventions for identifying the same clinical content in different information systems is a fundamental barrier to fully leveraging the potential of EHRs. Only by adopting vocabulary standards that provide the lingua franca across these local dialects can computers efficiently move, aggregate and use health data for decision support, outcomes management, quality reporting, research and many other purposes. In this regard, the International Classification of Functioning, Disability, and Health (ICF) is an important standard for physiotherapists because it provides a framework and standard language for describing health and health-related states. However, physiotherapists and other health-care professionals capture a wide range of data such as patient histories, clinical findings, tests and measurements, procedures, and so on, for which other vocabulary standards such as Logical Observation Identifiers Names and Codes and Systematized Nomenclature Of Medicine Clinical Terms are crucial for interoperable communication between different electronic systems. In this paper, we describe how the ICF and other internationally accepted vocabulary standards could advance physiotherapy practise and research by enabling data sharing and reuse by EHRs. We highlight how these different vocabulary standards fit together within a comprehensive record system, and how EHRs can make use of them, with a particular focus on enhancing decision-making. By incorporating the ICF and other internationally accepted vocabulary standards into our clinical information systems, physiotherapists will be able to leverage the potent capabilities of EHRs and contribute our unique clinical perspective to other health-care providers within the emerging electronic health information infrastructure. Copyright © 2013 John Wiley & Sons, Ltd.

DEVELOPMENT AND PERFORMANCE OF TEXT-MINING ALGORITHMS TO EXTRACT SOCIOECONOMIC STATUS FROM DE-IDENTIFIED ELECTRONIC HEALTH RECORDS.

PubMed

Hollister, Brittany M; Restrepo, Nicole A; Farber-Eger, Eric; Crawford, Dana C; Aldrich, Melinda C; Non, Amy

2017-01-01

Socioeconomic status (SES) is a fundamental contributor to health, and a key factor underlying racial disparities in disease. However, SES data are rarely included in genetic studies due in part to the difficultly of collecting these data when studies were not originally designed for that purpose. The emergence of large clinic-based biobanks linked to electronic health records (EHRs) provides research access to large patient populations with longitudinal phenotype data captured in structured fields as billing codes, procedure codes, and prescriptions. SES data however, are often not explicitly recorded in structured fields, but rather recorded in the free text of clinical notes and communications. The content and completeness of these data vary widely by practitioner. To enable gene-environment studies that consider SES as an exposure, we sought to extract SES variables from racial/ethnic minority adult patients (n=9,977) in BioVU, the Vanderbilt University Medical Center biorepository linked to de-identified EHRs. We developed several measures of SES using information available within the de-identified EHR, including broad categories of occupation, education, insurance status, and homelessness. Two hundred patients were randomly selected for manual review to develop a set of seven algorithms for extracting SES information from de-identified EHRs. The algorithms consist of 15 categories of information, with 830 unique search terms. SES data extracted from manual review of 50 randomly selected records were compared to data produced by the algorithm, resulting in positive predictive values of 80.0% (education), 85.4% (occupation), 87.5% (unemployment), 63.6% (retirement), 23.1% (uninsured), 81.8% (Medicaid), and 33.3% (homelessness), suggesting some categories of SES data are easier to extract in this EHR than others. The SES data extraction approach developed here will enable future EHR-based genetic studies to integrate SES information into statistical analyses. Ultimately, incorporation of measures of SES into genetic studies will help elucidate the impact of the social environment on disease risk and outcomes.

Care episode retrieval: distributional semantic models for information retrieval in the clinical domain.

PubMed

Moen, Hans; Ginter, Filip; Marsi, Erwin; Peltonen, Laura-Maria; Salakoski, Tapio; Salanterä, Sanna

2015-01-01

Patients' health related information is stored in electronic health records (EHRs) by health service providers. These records include sequential documentation of care episodes in the form of clinical notes. EHRs are used throughout the health care sector by professionals, administrators and patients, primarily for clinical purposes, but also for secondary purposes such as decision support and research. The vast amounts of information in EHR systems complicate information management and increase the risk of information overload. Therefore, clinicians and researchers need new tools to manage the information stored in the EHRs. A common use case is, given a--possibly unfinished--care episode, to retrieve the most similar care episodes among the records. This paper presents several methods for information retrieval, focusing on care episode retrieval, based on textual similarity, where similarity is measured through domain-specific modelling of the distributional semantics of words. Models include variants of random indexing and the semantic neural network model word2vec. Two novel methods are introduced that utilize the ICD-10 codes attached to care episodes to better induce domain-specificity in the semantic model. We report on experimental evaluation of care episode retrieval that circumvents the lack of human judgements regarding episode relevance. Results suggest that several of the methods proposed outperform a state-of-the art search engine (Lucene) on the retrieval task.

Care episode retrieval: distributional semantic models for information retrieval in the clinical domain

PubMed Central

2015-01-01

Patients' health related information is stored in electronic health records (EHRs) by health service providers. These records include sequential documentation of care episodes in the form of clinical notes. EHRs are used throughout the health care sector by professionals, administrators and patients, primarily for clinical purposes, but also for secondary purposes such as decision support and research. The vast amounts of information in EHR systems complicate information management and increase the risk of information overload. Therefore, clinicians and researchers need new tools to manage the information stored in the EHRs. A common use case is, given a - possibly unfinished - care episode, to retrieve the most similar care episodes among the records. This paper presents several methods for information retrieval, focusing on care episode retrieval, based on textual similarity, where similarity is measured through domain-specific modelling of the distributional semantics of words. Models include variants of random indexing and the semantic neural network model word2vec. Two novel methods are introduced that utilize the ICD-10 codes attached to care episodes to better induce domain-specificity in the semantic model. We report on experimental evaluation of care episode retrieval that circumvents the lack of human judgements regarding episode relevance. Results suggest that several of the methods proposed outperform a state-of-the art search engine (Lucene) on the retrieval task. PMID:26099735

Automatic generation of computable implementation guides from clinical information models.

PubMed

Boscá, Diego; Maldonado, José Alberto; Moner, David; Robles, Montserrat

2015-06-01

Clinical information models are increasingly used to describe the contents of Electronic Health Records. Implementation guides are a common specification mechanism used to define such models. They contain, among other reference materials, all the constraints and rules that clinical information must obey. However, these implementation guides typically are oriented to human-readability, and thus cannot be processed by computers. As a consequence, they must be reinterpreted and transformed manually into an executable language such as Schematron or Object Constraint Language (OCL). This task can be difficult and error prone due to the big gap between both representations. The challenge is to develop a methodology for the specification of implementation guides in such a way that humans can read and understand easily and at the same time can be processed by computers. In this paper, we propose and describe a novel methodology that uses archetypes as basis for generation of implementation guides. We use archetypes to generate formal rules expressed in Natural Rule Language (NRL) and other reference materials usually included in implementation guides such as sample XML instances. We also generate Schematron rules from NRL rules to be used for the validation of data instances. We have implemented these methods in LinkEHR, an archetype editing platform, and exemplify our approach by generating NRL rules and implementation guides from EN ISO 13606, openEHR, and HL7 CDA archetypes. Copyright © 2015 Elsevier Inc. All rights reserved.

Does adoption of electronic health records improve organizational performances of hospital surgical units? Results from the French e-SI (PREPS-SIPS) study.

PubMed

Plantier, Morgane; Havet, Nathalie; Durand, Thierry; Caquot, Nicolas; Amaz, Camille; Philip, Irène; Biron, Pierre; Perrier, Lionel

2017-02-01

Electronic health records (EHR) are increasingly being adopted by healthcare systems worldwide. In France, the "Hôpital numérique 2012-2017" program was implemented as part of a strategic plan to modernize health information technology (HIT), including promotion of widespread EHR use. With significant upfront investment costs as well as ongoing operational expenses, it is important to assess this system in terms of its ability to result in improvements in hospital performances. The aim of this study was to evaluate the impact of EHR use on the organizational performances of acute care hospital surgical units throughout France. This retrospective study was based on data derived from three national databases for year the 2012: IPAQSS (Indicators of improvement in the quality and the management of healthcare, "IPAQSS"), Hospi-Diag (French hospital performance indicators), and the national accreditation database. National data and methodological support were provided by the French Ministry of Health (DGOS) and the French National Authority for Health (HAS). Multivariate linear models were used to assess four organizational performance indicators: the occupancy rate of surgical inpatient beds, operating room utilization, the activity per surgeon, and the activity per both nurse anesthetist and anesthesiologist which were dependent variables. Several independent variables were taken into account, including the degree of EHR use. The models revealed a significant positive impact of EHR use on operating room utilization and bed occupancy rates for surgical inpatient units. No significant association was found between the activity per surgeon or the activity per nurse anesthetist and anesthesiologist with EHR use. All four organizational performance indicators were impacted by the type of hospital, the geographical region, and the severity of the pathologies. We were able to verify the purported potential benefits of EHR use on the organizational performances of surgical units in French hospitals. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Using OpenEHR in SICTI an electronic health record system for critical medicine

NASA Astrophysics Data System (ADS)

Filgueira, R.; Odriazola, A.; Simini, F.

2007-11-01

SICTI is a software tool for registering health records in critical medicine environments. Version 1.0 has been in use since 2003. The Biomedical Engineering Group (Núcleo de Ingeniería Biomédica), with support from the Technological Development Programme (Programa de Desarrollo Tecnológico), decided to develop a new version, to provide an aid for more critical medicine processes, based on a framework which would make the application domain change oriented. The team analyzed three alternatives: to develop an original product based on new research, to base the development on OpenEHR framework, or to use HL7 RIM as the reference model for SICTI. The team opted for OpenEHR. This work describes the use of OpenEHR, its strong and weak points, and states future work perspectives.

Bridging data models and terminologies to support adverse drug event reporting using EHR data.

PubMed

Declerck, G; Hussain, S; Daniel, C; Yuksel, M; Laleci, G B; Twagirumukiza, M; Jaulent, M-C

2015-01-01

This article is part of the Focus Theme of METHODs of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". SALUS project aims at building an interoperability platform and a dedicated toolkit to enable secondary use of electronic health records (EHR) data for post marketing drug surveillance. An important component of this toolkit is a drug-related adverse events (AE) reporting system designed to facilitate and accelerate the reporting process using automatic prepopulation mechanisms. To demonstrate SALUS approach for establishing syntactic and semantic interoperability for AE reporting. Standard (e.g. HL7 CDA-CCD) and proprietary EHR data models are mapped to the E2B(R2) data model via SALUS Common Information Model. Terminology mapping and terminology reasoning services are designed to ensure the automatic conversion of source EHR terminologies (e.g. ICD-9-CM, ICD-10, LOINC or SNOMED-CT) to the target terminology MedDRA which is expected in AE reporting forms. A validated set of terminology mappings is used to ensure the reliability of the reasoning mechanisms. The percentage of data elements of a standard E2B report that can be completed automatically has been estimated for two pilot sites. In the best scenario (i.e. the available fields in the EHR have actually been filled), only 36% (pilot site 1) and 38% (pilot site 2) of E2B data elements remain to be filled manually. In addition, most of these data elements shall not be filled in each report. SALUS platform's interoperability solutions enable partial automation of the AE reporting process, which could contribute to improve current spontaneous reporting practices and reduce under-reporting, which is currently one major obstacle in the process of acquisition of pharmacovigilance data.

Predicting neutropenia risk in patients with cancer using electronic data.

PubMed

Pawloski, Pamala A; Thomas, Avis J; Kane, Sheryl; Vazquez-Benitez, Gabriela; Shapiro, Gary R; Lyman, Gary H

2017-04-01

Clinical guidelines recommending the use of myeloid growth factors are largely based on the prescribed chemotherapy regimen. The guidelines suggest that oncologists consider patient-specific characteristics when prescribing granulocyte-colony stimulating factor (G-CSF) prophylaxis; however, a mechanism to quantify individual patient risk is lacking. Readily available electronic health record (EHR) data can provide patient-specific information needed for individualized neutropenia risk estimation. An evidence-based, individualized neutropenia risk estimation algorithm has been developed. This study evaluated the automated extraction of EHR chemotherapy treatment data and externally validated the neutropenia risk prediction model. A retrospective cohort of adult patients with newly diagnosed breast, colorectal, lung, lymphoid, or ovarian cancer who received the first cycle of a cytotoxic chemotherapy regimen from 2008 to 2013 were recruited from a single cancer clinic. Electronically extracted EHR chemotherapy treatment data were validated by chart review. Neutropenia risk stratification was conducted and risk model performance was assessed using calibration and discrimination. Chemotherapy treatment data electronically extracted from the EHR were verified by chart review. The neutropenia risk prediction tool classified 126 patients (57%) as being low risk for febrile neutropenia, 44 (20%) as intermediate risk, and 51 (23%) as high risk. The model was well calibrated (Hosmer-Lemeshow goodness-of-fit test = 0.24). Discrimination was adequate and slightly less than in the original internal validation (c-statistic 0.75 vs 0.81). Chemotherapy treatment data were electronically extracted from the EHR successfully. The individualized neutropenia risk prediction model performed well in our retrospective external cohort. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Implementing electronic health records (EHRs): health care provider perceptions before and after transition from a local basic EHR to a commercial comprehensive EHR.

PubMed

Krousel-Wood, Marie; McCoy, Allison B; Ahia, Chad; Holt, Elizabeth W; Trapani, Donnalee N; Luo, Qingyang; Price-Haywood, Eboni G; Thomas, Eric J; Sittig, Dean F; Milani, Richard V

2018-06-01

We assessed changes in the percentage of providers with positive perceptions of electronic health record (EHR) benefit before and after transition from a local basic to a commercial comprehensive EHR. Changes in the percentage of providers with positive perceptions of EHR benefit were captured via a survey of academic health care providers before (baseline) and at 6-12 months (short term) and 12-24 months (long term) after the transition. We analyzed 32 items for the overall group and by practice setting, provider age, and specialty using separate multivariable-adjusted random effects logistic regression models. A total of 223 providers completed all 3 surveys (30% response rate): 85.6% had outpatient practices, 56.5% were >45 years old, and 23.8% were primary care providers. The percentage of providers with positive perceptions significantly increased from baseline to long-term follow-up for patient communication, hospital transitions - access to clinical information, preventive care delivery, preventive care prompt, preventive lab prompt, satisfaction with system reliability, and sharing medical information (P < .05 for each). The percentage of providers with positive perceptions significantly decreased over time for overall satisfaction, productivity, better patient care, clinical decision quality, easy access to patient information, monitoring patients, more time for patients, coordination of care, computer access, adequate resources, and satisfaction with ease of use (P < 0.05 for each). Results varied by subgroup. After a transition to a commercial comprehensive EHR, items with significant increases and significant decreases in the percentage of providers with positive perceptions of EHR benefit were identified, overall and by subgroup.

Effects of electronic health record use on the exam room communication skills of resident physicians: a randomized within-subjects study.

PubMed

Taft, Teresa; Lenert, Leslie; Sakaguchi, Farrant; Stoddard, Gregory; Milne, Caroline

2015-01-01

The effects of electronic health records (EHRs) on doctor-patient communication are unclear. To evaluate the effects of EHR use compared with paper chart use, on novice physicians' communication skills. Within-subjects randomized controlled trial using observed structured clinical examination methods to assess the impact of use of an EHR on communication. A large academic internal medicine training program. First-year internal medicine residents. Residents interviewed, diagnosed, and initiated treatment of simulated patients using a paper chart or an EHR on a laptop computer. Video recordings of interviews were rated by three trained observers using the Four Habits scale. Thirty-two residents completed the study and had data available for review (61.5% of those enrolled in the residency program). In most skill areas in the Four Habits model, residents performed at least as well using the EHR and were statistically better in six of 23 skills areas (p<0.05). The overall average communication score was better when using an EHR: mean difference 0.254 (95% CI 0.05 to 0.45), p = 0.012, Cohen's d of 0.47 (a moderate effect). Residents scoring poorly (>3 average score) with paper methods (n = 8) had clinically important improvement when using the EHR. This study was conducted in first-year residents in a training environment using simulated patients at a single institution. Use of an EHR on a laptop computer appears to improve the ability of first-year residents to communicate with patients relative to using a paper chart. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Effects of electronic health record use on the exam room communication skills of resident physicians: a randomized within-subjects study

PubMed Central

Taft, Teresa; Lenert, Leslie; Sakaguchi, Farrant; Stoddard, Gregory; Milne, Caroline

2015-01-01

Background The effects of electronic health records (EHRs) on doctor–patient communication are unclear. Objective To evaluate the effects of EHR use compared with paper chart use, on novice physicians’ communication skills. Design Within-subjects randomized controlled trial using observed structured clinical examination methods to assess the impact of use of an EHR on communication. Setting A large academic internal medicine training program. Population First-year internal medicine residents. Intervention Residents interviewed, diagnosed, and initiated treatment of simulated patients using a paper chart or an EHR on a laptop computer. Video recordings of interviews were rated by three trained observers using the Four Habits scale. Results Thirty-two residents completed the study and had data available for review (61.5% of those enrolled in the residency program). In most skill areas in the Four Habits model, residents performed at least as well using the EHR and were statistically better in six of 23 skills areas (p<0.05). The overall average communication score was better when using an EHR: mean difference 0.254 (95% CI 0.05 to 0.45), p = 0.012, Cohen's d of 0.47 (a moderate effect). Residents scoring poorly (>3 average score) with paper methods (n = 8) had clinically important improvement when using the EHR. Limitations This study was conducted in first-year residents in a training environment using simulated patients at a single institution. Conclusions Use of an EHR on a laptop computer appears to improve the ability of first-year residents to communicate with patients relative to using a paper chart. PMID:25336596

Identifying Barriers in the Use of Electronic Health Records in Hawai‘i

PubMed Central

Hamamura, Faith D; Hughes, Kira

2017-01-01

Hawai‘i faces unique challenges to Electronic Health Record (EHR) adoption due to physician shortages, a widespread distribution of Medically Underserved Areas and Populations (MUA/P), and a higher percentage of small independent practices. However, research on EHR adoption in Hawai‘i is limited. To address this gap, this article examines the current state of EHR in Hawai‘i, the barriers to adoption, and the future of Health Information Technology (HIT) initiatives to improve the health of Hawai‘i's people. Eight focus groups were conducted on Lana‘i, Maui, Hawai‘i Island, Kaua‘i, Moloka‘i, and O‘ahu. In these groups, a total of 51 diverse health professionals were asked about the functionality of EHR systems, barriers to use, facilitators of use, and what EHRs would look like in a perfect world. Responses were summarized and analyzed based on constant comparative analysis techniques. Responses were then clustered into thirteen themes: system compatibility, loss of productivity, poor interface, IT support, hardware/software, patient factors, education/training, noise in the system, safety, data quality concerns, quality metrics, workflow, and malpractice concerns. Results show that every group mentioned system compatibility. In response to these findings, the Health eNet Community Health Record initiative — which allows providers web-based access to patient health information from the patient's provider network— was developed as a step toward alleviating some of the barriers to sharing information between different EHRs. The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) legislation will introduce a new payment model in 2017 that is partially based on EHR utilization. Therefore, more research should be done to understand EHR adoption and how this ruling will affect providers in Hawai‘i. PMID:28435756

The Impact of Electronic Health Records and Teamwork on Diabetes Care Quality

PubMed Central

Graetz, Ilana; Huang, Jie; Brand, Richard; Shortell, Stephen M.; Rundall, Thomas G.; Bellows, Jim; Hsu, John; Jaffe, Marc; Reed, Mary E.

2016-01-01

Objective Evidence of the impact Electronic Health Records (EHR) on clinical outcomes remains mixed. The impact EHRs likely depends on the organizational context in which they are used. We focus on one aspect of the organizational context: cohesion of primary care teams. We examined whether team cohesion among primary care team members changed the association of EHR use and changes in clinical outcomes for patients with diabetes. Study Design We combined provider-reported primary care team cohesion with lab values for patients with diabetes collected during the staggered EHR implementation (2005–2009). We used multivariate regression models with patient-level fixed effects to assess whether team cohesion levels changed the association between outpatient EHR use and clinical outcomes for patients with diabetes. Subjects 80,611 patients with diabetes mellitus. Measures Changes in hemoglobin A1c (HbA1c) and low-density lipoprotein cholesterol (LDL-C) Results For HbA1c, EHR use was associated with an average decrease of 0.11% for patients with higher cohesion primary care teams compared with a decrease of 0.08% for patients with lower cohesion teams (difference 0.02% in HbA1c, 95%CI: 0.01–0.03). For LDL-C, EHR use was associated with a decrease of 2.15 mg/dL for patients with higher cohesion primary teams compared with a decrease of 1.42 mg/dL for patients with lower cohesion teams (difference 0.73 mg/dL, 95%CI: 0.41–1.11 mg/dL). Conclusions Patients cared for by higher cohesion primary care teams experienced modest but statistically significantly greater EHR-related health outcome improvements, compared with patients cared for by providers practicing in lower cohesion teams. PMID:26671699

Identifying Barriers in the Use of Electronic Health Records in Hawai'i.

PubMed

Hamamura, Faith D; Withy, Kelley; Hughes, Kira

2017-03-01

Hawai'i faces unique challenges to Electronic Health Record (EHR) adoption due to physician shortages, a widespread distribution of Medically Underserved Areas and Populations (MUA/P), and a higher percentage of small independent practices. However, research on EHR adoption in Hawai'i is limited. To address this gap, this article examines the current state of EHR in Hawai'i, the barriers to adoption, and the future of Health Information Technology (HIT) initiatives to improve the health of Hawai'i's people. Eight focus groups were conducted on Lana'i, Maui, Hawai'i Island, Kaua'i, Moloka'i, and O'ahu. In these groups, a total of 51 diverse health professionals were asked about the functionality of EHR systems, barriers to use, facilitators of use, and what EHRs would look like in a perfect world. Responses were summarized and analyzed based on constant comparative analysis techniques. Responses were then clustered into thirteen themes: system compatibility, loss of productivity, poor interface, IT support, hardware/software, patient factors, education/training, noise in the system, safety, data quality concerns, quality metrics, workflow, and malpractice concerns. Results show that every group mentioned system compatibility. In response to these findings, the Health eNet Community Health Record initiative - which allows providers web-based access to patient health information from the patient's provider network- was developed as a step toward alleviating some of the barriers to sharing information between different EHRs. The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) legislation will introduce a new payment model in 2017 that is partially based on EHR utilization. Therefore, more research should be done to understand EHR adoption and how this ruling will affect providers in Hawai'i.

Reconciliation of the cloud computing model with US federal electronic health record regulations

PubMed Central

2011-01-01

Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing. PMID:21727204

A cloud-based approach for interoperable electronic health records (EHRs).

PubMed

Bahga, Arshdeep; Madisetti, Vijay K

2013-09-01

We present a cloud-based approach for the design of interoperable electronic health record (EHR) systems. Cloud computing environments provide several benefits to all the stakeholders in the healthcare ecosystem (patients, providers, payers, etc.). Lack of data interoperability standards and solutions has been a major obstacle in the exchange of healthcare data between different stakeholders. We propose an EHR system - cloud health information systems technology architecture (CHISTAR) that achieves semantic interoperability through the use of a generic design methodology which uses a reference model that defines a general purpose set of data structures and an archetype model that defines the clinical data attributes. CHISTAR application components are designed using the cloud component model approach that comprises of loosely coupled components that communicate asynchronously. In this paper, we describe the high-level design of CHISTAR and the approaches for semantic interoperability, data integration, and security.

Development and evaluation of nursing user interface screens using multiple methods.

PubMed

Hyun, Sookyung; Johnson, Stephen B; Stetson, Peter D; Bakken, Suzanne

2009-12-01

Building upon the foundation of the Structured Narrative Electronic Health Record (EHR) model, we applied theory-based (combined Technology Acceptance Model and Task-Technology Fit Model) and user-centered methods to explore nurses' perceptions of functional requirements for an electronic nursing documentation system, design user interface screens reflective of the nurses' perspectives, and assess nurses' perceptions of the usability of the prototype user interface screens. The methods resulted in user interface screens that were perceived to be easy to use, potentially useful, and well-matched to nursing documentation tasks associated with Nursing Admission Assessment, Blood Administration, and Nursing Discharge Summary. The methods applied in this research may serve as a guide for others wishing to implement user-centered processes to develop or extend EHR systems. In addition, some of the insights obtained in this study may be informative to the development of safe and efficient user interface screens for nursing document templates in EHRs.

Reconciliation of the cloud computing model with US federal electronic health record regulations.

PubMed

Schweitzer, Eugene J

2012-01-01

Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing.

Commentary: Lost in translation? How electronic health records structure communication, relationships, and meaning.

PubMed

Lown, Beth A; Rodriguez, Dayron

2012-04-01

The media through which we communicate shape how we think, how we act, and who we are. Electronic health records (EHRs) may promote more effective, efficient, coordinated, safer care. Research is emerging, but more is needed to assess the effect of EHRs on communication, relationships, patients' trust, adherence, and health outcomes. The authors posit that EHRs introduce a "third party" into exam room interactions that competes with the patient for clinicians' attention, affects clinicians' capacity to be fully present, and alters the nature of communication, relationships, and physicians' sense of professional role. Screen-driven communication inhibits patients' narratives and diminishes clinicians' responses to patients' cues about psychosocial issues and emotional concerns. Students, trainees, and clinicians can, however, learn to integrate EHRs into triadic exam room interactions to facilitate information sharing and shared decision making.Student exposure to EHRs is currently limited. Educators and researchers should implement curricula and assessment tools to help learners integrate EHRs into clinical interactions in ways that foster, rather than diminish, communication and relationships. Further, educators must prioritize the teaching and modeling of self-awareness and self-calibration, mindful presence, and compassion within such curricula to prevent these important qualities and skills from being lost in translation in the digital era.

Integrated secure solution for electronic healthcare records sharing

NASA Astrophysics Data System (ADS)

Yao, Yehong; Zhang, Chenghao; Sun, Jianyong; Jin, Jin; Zhang, Jianguo

2007-03-01

The EHR is a secure, real-time, point-of-care, patient-centric information resource for healthcare providers. Many countries and regional districts have set long-term goals to build EHRs, and most of EHRs are usually built based on the integration of different information systems with different information models and platforms. A number of hospitals in Shanghai are also piloting the development of an EHR solution based on IHE XDS/XDS-I profiles with a service-oriented architecture (SOA). The first phase of the project targets the Diagnostic Imaging domain and allows seamless sharing of images and reports across the multiple hospitals. To develop EHRs for regional coordinated healthcare, some factors should be considered in designing architecture, one of which is security issue. In this paper, we present some approaches and policies to improve and strengthen the security among the different hospitals' nodes, which are compliant with the security requirements defined by IHE IT Infrastructure (ITI) Technical Framework. Our security solution includes four components: Time Sync System (TSS), Digital Signature Manage System (DSMS), Data Exchange Control Component (DECC) and Single Sign-On (SSO) System. We give a design method and implementation strategy of these security components, and then evaluate the performance and overheads of the security services or features by integrating the security components into an image-based EHR system.

Development of the quality assessment model of EHR software in family medicine practices: research based on user satisfaction.

PubMed

Kralj, Damir; Kern, Josipa; Tonkovic, Stanko; Koncar, Miroslav

2015-09-09

Family medicine practices (FMPs) make the basis for the Croatian health care system. Use of electronic health record (EHR) software is mandatory and it plays an important role in running these practices, but important functional features still remain uneven and largely left to the will of the software developers. The objective of this study was to develop a novel and comprehensive model for functional evaluation of the EHR software in FMPs, based on current world standards, models and projects, as well as on actual user satisfaction and requirements. Based on previous theoretical and experimental research in this area, we made the initial framework model consisting of six basic categories as a base for online survey questionnaire. Family doctors assessed perceived software quality by using a five-point Likert-type scale. Using exploratory factor analysis and appropriate statistical methods over the collected data, the final optimal structure of the novel model was formed. Special attention was focused on the validity and quality of the novel model. The online survey collected a total of 384 cases. The obtained results indicate both the quality of the assessed software and the quality in use of the novel model. The intense ergonomic orientation of the novel measurement model was particularly emphasised. The resulting novel model is multiple validated, comprehensive and universal. It could be used to assess the user-perceived quality of almost all forms of the ambulatory EHR software and therefore useful to all stakeholders in this area of the health care informatisation.

Readmission prediction via deep contextual embedding of clinical concepts.

PubMed

Xiao, Cao; Ma, Tengfei; Dieng, Adji B; Blei, David M; Wang, Fei

2018-01-01

Hospital readmission costs a lot of money every year. Many hospital readmissions are avoidable, and excessive hospital readmissions could also be harmful to the patients. Accurate prediction of hospital readmission can effectively help reduce the readmission risk. However, the complex relationship between readmission and potential risk factors makes readmission prediction a difficult task. The main goal of this paper is to explore deep learning models to distill such complex relationships and make accurate predictions. We propose CONTENT, a deep model that predicts hospital readmissions via learning interpretable patient representations by capturing both local and global contexts from patient Electronic Health Records (EHR) through a hybrid Topic Recurrent Neural Network (TopicRNN) model. The experiment was conducted using the EHR of a real world Congestive Heart Failure (CHF) cohort of 5,393 patients. The proposed model outperforms state-of-the-art methods in readmission prediction (e.g. 0.6103 ± 0.0130 vs. second best 0.5998 ± 0.0124 in terms of ROC-AUC). The derived patient representations were further utilized for patient phenotyping. The learned phenotypes provide more precise understanding of readmission risks. Embedding both local and global context in patient representation not only improves prediction performance, but also brings interpretable insights of understanding readmission risks for heterogeneous chronic clinical conditions. This is the first of its kind model that integrates the power of both conventional deep neural network and the probabilistic generative models for highly interpretable deep patient representation learning. Experimental results and case studies demonstrate the improved performance and interpretability of the model.

Impact of electronic health records on malpractice claims in a sample of physician offices in Colorado: a retrospective cohort study.

PubMed

Victoroff, Michael S; Drury, Barbara M; Campagna, Elizabeth J; Morrato, Elaine H

2013-05-01

Electronic health records (EHRs) might reduce medical liability claims and potentially justify premium credits from liability insurers, but the evidence is limited. To evaluate the association between EHR use and medical liability claims in a population of office-based physicians, including claims that could potentially be directly prevented by features available in EHRs ("EHR-sensitive" claims). Retrospective cohort study of medical liability claims and analysis of claim abstracts. The 26 % of Colorado office-based physicians insured through COPIC Insurance Company who responded to a survey on EHR use (894 respondents out of 3,502 invitees). Claims incidence rate ratio (IRR); prevalence of "EHR-sensitive" claims. 473 physicians (53 % of respondents) used an office-based EHR. After adjustment for sex, birth cohort, specialty, practice setting and use of an EHR in settings other than an office, IRR for all claims was not significantly different between EHR users and non-users (0.88, 95 % CI 0.52-1.46; p = 0.61), or for users after EHR implementation as compared to before (0.73, 95 % CI 0.41-1.29; p = 0.28). Of 1,569 claim abstracts reviewed, 3 % were judged "Plausibly EHR-sensitive," 82 % "Unlikely EHR-sensitive," and 15 % "Unable to determine." EHR-sensitive claims occurred in six out of 633 non-users and two out of 251 EHR users. Incidence rate ratios were 0.01 for both groups. Colorado physicians using office-based EHRs did not have significantly different rates of liability claims than non-EHR users; nor were rates different for EHR users before and after EHR implementation. The lack of significant effect may be due to a low prevalence of EHR-sensitive claims. Further research on EHR use and medical liability across a larger population of physicians is warranted.

A Standards-Based Architecture Proposal for Integrating Patient mHealth Apps to Electronic Health Record Systems

PubMed Central

Fontelo, P.; Rossi, E.; Ackerman, MJ

2015-01-01

Summary Background Mobile health Applications (mHealth Apps) are opening the way to patients’ responsible and active involvement with their own healthcare management. However, apart from Apps allowing patient’s access to their electronic health records (EHRs), mHealth Apps are currently developed as dedicated “island systems”. Objective Although much work has been done on patient’s access to EHRs, transfer of information from mHealth Apps to EHR systems is still low. This study proposes a standards-based architecture that can be adopted by mHealth Apps to exchange information with EHRs to support better quality of care. Methods Following the definition of requirements for the EHR/mHealth App information exchange recently proposed, and after reviewing current standards, we designed the architecture for EHR/mHealth App integration. Then, as a case study, we modeled a system based on the proposed architecture aimed to support home monitoring for congestive heart failure patients. We simulated such process using, on the EHR side, OpenMRS, an open source longitudinal EHR and, on the mHealth App side, the iOS platform. Results The integration architecture was based on the bi-directional exchange of standard documents (clinical document architecture rel2 – CDA2). In the process, the clinician “prescribes” the home monitoring procedures by creating a CDA2 prescription in the EHR that is sent, encrypted and de-identified, to the mHealth App to create the monitoring calendar. At the scheduled time, the App alerts the patient to start the monitoring. After the measurements are done, the App generates a structured CDA2-compliant monitoring report and sends it to the EHR, thus avoiding local storage. Conclusions The proposed architecture, even if validated only in a simulation environment, represents a step forward in the integration of personal mHealth Apps into the larger health-IT ecosystem, allowing the bi-directional data exchange between patients and healthcare professionals, supporting the patient’s engagement in self-management and self-care. PMID:26448794

A business case for HIT adoption: effects of "meaningful use" EHR financial incentives on clinic revenue.

PubMed

Behkami, Nima A; Dorr, David A; Morrice, Stuart

2010-01-01

The goal of this study is to describe a framework that allows decision makers to efficiently evaluate factors that affect Electronic Health Record (EHR) adoption and test suitable interventions; specifically financial incentives. The United States healthcare delivery system is experiencing a transformation to improve population health. There is strong agreement that "meaningful use" of Health Information Technology (HIT) is a major enabler in this effort. However it's also understood that the high cost of implementing an EHR is an obstacle for adoption. To help understand these complexities we developed a simulation model designed to capture the dynamic nature of policy interventions that affect the adoption of EHR. We found that "Effective" use of HIT approaches break-even-point and larger clinic revenue many times faster that "average" or "poor" use of HIT. This study uses a systems perspective to the evaluate EHR adoption process through the "meaningful use" redesign as proposed in the American Reinvestment and Recovery Act 2009 in the United States healthcare industry by utilizing the System Dynamics methodology and Scenario Analysis.

Facilitating secondary use of medical data by using openEHR archetypes.

PubMed

Kohl, Christian D; Garde, Sebastian; Knaup, Petra

2010-01-01

Clinical trials are of high importance for medical progress. But even though more and more clinical data is available in electronic patient records (EPRs) and more and more electronic data capture (EDC) systems are used in trials, there is still a gap which makes EPR / EDC interoperability difficult and hampers secondary use of medical routine data. The openEHR architecture for Electronic Health Records is based on a two level modeling approach which makes use of 'archetypes'. We want to analyze whether archetypes can help to bridge this gap by building an integrated EPR / EDC system based on openEHR archetypes. We used the 'openEHR Reference Framework and Application' (Opereffa) and existing archetypes for medical data. Furthermore, we developed dedicated archetypes to document study meta data. We developed a first prototype implementation of an archetype based integrated EPR / EDC system. Next steps will be the evaluation of an extended prototype in a real clinical trial scenario. Opereffa was a good starting point for our work. OpenEHR archetypes proved useful for secondary use of health data.

Security challenges in integration of a PHR-S into a standards based national EHR.

PubMed

Mense, Alexander; Hoheiser Pförtner, Franz; Sauermann, Stefan

2014-01-01

Health related data provided by patients themselves is expected to play a major role in future healthcare. Data from personal health devices, vaccination records, health diaries or observations of daily living, for instance, is stored in personal health records (PHR) which are maintained by personal health record systems (PHR-S). Combining this information with medical records provided by healthcare providers in electronic health records (EHR) is one of the next steps towards "personal care". Austria currently sets up a nationwide EHR system that incorporates all healthcare providers and is technically based on international standards (IHE, HL7, OASIS, ...). Looking at the expected potential of merging PHR and EHR data it is worth to analyse integration approaches. Although knowing that an integration requires the coordination of processes, information models and technical architectures, this paper specifically focuses on security issues by evaluating general security requirements for a PHR-S (based on HL7 PHR-S FM), comparing them with the information security specifications for the Austrian's national EHR (based on ISO/IES 27000 series) and identifying the main challenges as well as possible approaches.

Archetype-based electronic health records: a literature review and evaluation of their applicability to health data interoperability and access.

PubMed

Wollersheim, Dennis; Sari, Anny; Rahayu, Wenny

Health Information Managers (HIMs) are responsible for overseeing health information. The change management necessary during the transition to electronic health records (EHR) is substantial, and ongoing. Archetype-based EHRs are a core health information system component which solve many of the problems that arise during this period of change. Archetypes are models of clinical content, and they have many beneficial properties. They are interoperable, both between settings and through time. They are more amenable to change than conventional paradigms, and their design is congruent with clinical practice. This paper is an overview of the current archetype literature relevant to Health Information Managers. The literature was sourced in the English language sections of ScienceDirect, IEEE Explore, Pubmed, Google Scholar, ACM Digital library and other databases on the usage of archetypes for electronic health record storage, looking at the current areas of archetype research, appropriate usage, and future research. We also used reference lists from the cited papers, papers referenced by the openEHR website, and the recommendations from experts in the area. Criteria for inclusion were (a) if studies covered archetype research and (b) were either studies of archetype use, archetype system design, or archetype effectiveness. The 47 papers included show a wide and increasing worldwide archetype usage, in a variety of medical domains. Most of the papers noted that archetypes are an appropriate solution for future-proof and interoperable medical data storage. We conclude that archetypes are a suitable solution for the complex problem of electronic health record storage and interoperability.

Agile Acceptance Test–Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software

PubMed Central

Baldwin, Krystal L; Kannan, Vaishnavi; Flahaven, Emily L; Parks, Cassandra J; Ott, Jason M; Willett, Duwayne L

2018-01-01

Background Moving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test–driven development and automated regression testing promotes reliability. Test–driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a “safety net” for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and “living” design documentation. Rapid-cycle development or “agile” methods are being successfully applied to CDS development. The agile practice of automated test–driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as “executable requirements.” Objective We aimed to establish feasibility of acceptance test–driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse). Methods Acceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory’s expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite. Results We used test–driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the “executable requirements” are shown prior to building the CDS alert, during build, and after successful build. Conclusions Automated acceptance test–driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test–driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization. PMID:29653922

Agile Acceptance Test-Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software.

PubMed

Basit, Mujeeb A; Baldwin, Krystal L; Kannan, Vaishnavi; Flahaven, Emily L; Parks, Cassandra J; Ott, Jason M; Willett, Duwayne L

2018-04-13

Moving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test-driven development and automated regression testing promotes reliability. Test-driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a "safety net" for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and "living" design documentation. Rapid-cycle development or "agile" methods are being successfully applied to CDS development. The agile practice of automated test-driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as "executable requirements." We aimed to establish feasibility of acceptance test-driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse). Acceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory's expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite. We used test-driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the "executable requirements" are shown prior to building the CDS alert, during build, and after successful build. Automated acceptance test-driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test-driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization. ©Mujeeb A Basit, Krystal L Baldwin, Vaishnavi Kannan, Emily L Flahaven, Cassandra J Parks, Jason M Ott, Duwayne L Willett. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 13.04.2018.

EBMPracticeNet: A Bilingual National Electronic Point-Of-Care Project for Retrieval of Evidence-Based Clinical Guideline Information and Decision Support

PubMed Central

2013-01-01

Background In Belgium, the construction of a national electronic point-of-care information service, EBMPracticeNet, was initiated in 2011 to optimize quality of care by promoting evidence-based decision-making. The collaboration of the government, health care providers, evidence-based medicine (EBM) partners, and vendors of electronic health records (EHR) is unique to this project. All Belgian health care professionals get free access to an up-to-date database of validated Belgian and nearly 1000 international guidelines, incorporated in a portal that also provides EBM information from other sources than guidelines, including computerized clinical decision support that is integrated in the EHRs. Objective The objective of this paper was to describe the development strategy, the overall content, and the management of EBMPracticeNet which may be of relevance to other health organizations creating national or regional electronic point-of-care information services. Methods Several candidate providers of comprehensive guideline solutions were evaluated and one database was selected. Translation of the guidelines to Dutch and French was done with translation software, post-editing by translators and medical proofreading. A strategy is determined to adapt the guideline content to the Belgian context. Acceptance of the computerized clinical decision support tool has been tested and a randomized controlled trial is planned to evaluate the effect on process and patient outcomes. Results Currently, EBMPracticeNet is in "work in progress" state. Reference is made to the results of a pilot study and to further planned research including a randomized controlled trial. Conclusions The collaboration of government, health care providers, EBM partners, and vendors of EHRs is unique. The potential value of the project is great. The link between all the EHRs from different vendors and a national database held on a single platform that is controlled by all EBM organizations in Belgium are the strengths of EBMPracticeNet. PMID:23842038

Use of Headings and Classifications by Physicians in Medical Narratives of EHRs

PubMed Central

Häyrinen, K.; Harno, K.; Nykänen, P.

2011-01-01

Objective The purpose of this study was to describe and evaluate patient care documentation by hospital physicians in EHRs and especially the use of national headings and classifications in these documentations Material and Methods The initial material consisted of a random sample of 3,481 medical narratives documented in EHRs during the period 2004-2005 in one department of a Finnish central hospital. The final material comprised a subset of 1,974 medical records with a focus on consultation requests and consultation responses by two specialist groups from 871 patients. This electronic documentation was analyzed using deductive content analyses and descriptive statistics. Results The physicians documented patient care in EHRs principally as narrative text. The medical narratives recorded by specialists were structured with headings in less than half of the patient cases. Consultation responses in general were more often structured with headings than consultation requests. The use of classifications was otherwise insignificant, but diagnoses were documented as ICD 10 codes in over 50% of consultation responses by both medical specialties. Conclusion There is an obvious need to improve the structuring of narrative text with national headings and classifications. According to the findings of this study, reason for care, patient history, health status, follow-up care plan and diagnosis are meaningful headings in physicians’ documentation. The existing list of headings needs to be analyzed within a consistent unified terminology system as a basis for further development. Adhering to headings and classifications in EHR documentation enables patient data to be shared and aggregated. The secondary use of data is expected to improve care management and quality of care. PMID:23616866

NETIMIS: Dynamic Simulation of Health Economics Outcomes Using Big Data.

PubMed

Johnson, Owen A; Hall, Peter S; Hulme, Claire

2016-02-01

Many healthcare organizations are now making good use of electronic health record (EHR) systems to record clinical information about their patients and the details of their healthcare. Electronic data in EHRs is generated by people engaged in complex processes within complex environments, and their human input, albeit shaped by computer systems, is compromised by many human factors. These data are potentially valuable to health economists and outcomes researchers but are sufficiently large and complex enough to be considered part of the new frontier of 'big data'. This paper describes emerging methods that draw together data mining, process modelling, activity-based costing and dynamic simulation models. Our research infrastructure includes safe links to Leeds hospital's EHRs with 3 million secondary and tertiary care patients. We created a multidisciplinary team of health economists, clinical specialists, and data and computer scientists, and developed a dynamic simulation tool called NETIMIS (Network Tools for Intervention Modelling with Intelligent Simulation; http://www.netimis.com ) suitable for visualization of both human-designed and data-mined processes which can then be used for 'what-if' analysis by stakeholders interested in costing, designing and evaluating healthcare interventions. We present two examples of model development to illustrate how dynamic simulation can be informed by big data from an EHR. We found the tool provided a focal point for multidisciplinary team work to help them iteratively and collaboratively 'deep dive' into big data.

Archetype-based semantic integration and standardization of clinical data.

PubMed

Moner, David; Maldonado, Jose A; Bosca, Diego; Fernandez, Jesualdo T; Angulo, Carlos; Crespo, Pere; Vivancos, Pedro J; Robles, Montserrat

2006-01-01

One of the basic needs for any healthcare professional is to be able to access to clinical information of patients in an understandable and normalized way. The lifelong clinical information of any person supported by electronic means configures his/her Electronic Health Record (EHR). This information is usually distributed among several independent and heterogeneous systems that may be syntactically or semantically incompatible. The Dual Model architecture has appeared as a new proposal for maintaining a homogeneous representation of the EHR with a clear separation between information and knowledge. Information is represented by a Reference Model which describes common data structures with minimal semantics. Knowledge is specified by archetypes, which are formal representations of clinical concepts built upon a particular Reference Model. This kind of architecture is originally thought for implantation of new clinical information systems, but archetypes can be also used for integrating data of existing and not normalized systems, adding at the same time a semantic meaning to the integrated data. In this paper we explain the possible use of a Dual Model approach for semantic integration and standardization of heterogeneous clinical data sources and present LinkEHR-Ed, a tool for developing archetypes as elements for integration purposes. LinkEHR-Ed has been designed to be easily used by the two main participants of the creation process of archetypes for clinical data integration: the Health domain expert and the Information Technologies domain expert.

XML technologies for the Omaha System: a data model, a Java tool and several case studies supporting home healthcare.

PubMed

Vittorini, Pierpaolo; Tarquinio, Antonietta; di Orio, Ferdinando

2009-03-01

The eXtensible markup language (XML) is a metalanguage which is useful to represent and exchange data between heterogeneous systems. XML may enable healthcare practitioners to document, monitor, evaluate, and archive medical information and services into distributed computer environments. Therefore, the most recent proposals on electronic health records (EHRs) are usually based on XML documents. Since none of the existing nomenclatures were specifically developed for use in automated clinical information systems, but were adapted to such use, numerous current EHRs are organized as a sequence of events, each represented through codes taken from international classification systems. In nursing, a hierarchically organized problem-solving approach is followed, which hardly couples with the sequential organization of such EHRs. Therefore, the paper presents an XML data model for the Omaha System taxonomy, which is one of the most important international nomenclatures used in the home healthcare nursing context. Such a data model represents the formal definition of EHRs specifically developed for nursing practice. Furthermore, the paper delineates a Java application prototype which is able to manage such documents, shows the possibility to transform such documents into readable web pages, and reports several case studies, one currently managed by the home care service of a Health Center in Central Italy.

An Interoperability Platform Enabling Reuse of Electronic Health Records for Signal Verification Studies

PubMed Central

Yuksel, Mustafa; Gonul, Suat; Laleci Erturkmen, Gokce Banu; Sinaci, Ali Anil; Invernizzi, Paolo; Facchinetti, Sara; Migliavacca, Andrea; Bergvall, Tomas; Depraetere, Kristof; De Roo, Jos

2016-01-01

Depending mostly on voluntarily sent spontaneous reports, pharmacovigilance studies are hampered by low quantity and quality of patient data. Our objective is to improve postmarket safety studies by enabling safety analysts to seamlessly access a wide range of EHR sources for collecting deidentified medical data sets of selected patient populations and tracing the reported incidents back to original EHRs. We have developed an ontological framework where EHR sources and target clinical research systems can continue using their own local data models, interfaces, and terminology systems, while structural interoperability and Semantic Interoperability are handled through rule-based reasoning on formal representations of different models and terminology systems maintained in the SALUS Semantic Resource Set. SALUS Common Information Model at the core of this set acts as the common mediator. We demonstrate the capabilities of our framework through one of the SALUS safety analysis tools, namely, the Case Series Characterization Tool, which have been deployed on top of regional EHR Data Warehouse of the Lombardy Region containing about 1 billion records from 16 million patients and validated by several pharmacovigilance researchers with real-life cases. The results confirm significant improvements in signal detection and evaluation compared to traditional methods with the missing background information. PMID:27123451

Developing and evaluating an automated appendicitis risk stratification algorithm for pediatric patients in the emergency department.

PubMed

Deleger, Louise; Brodzinski, Holly; Zhai, Haijun; Li, Qi; Lingren, Todd; Kirkendall, Eric S; Alessandrini, Evaline; Solti, Imre

2013-12-01

To evaluate a proposed natural language processing (NLP) and machine-learning based automated method to risk stratify abdominal pain patients by analyzing the content of the electronic health record (EHR). We analyzed the EHRs of a random sample of 2100 pediatric emergency department (ED) patients with abdominal pain, including all with a final diagnosis of appendicitis. We developed an automated system to extract relevant elements from ED physician notes and lab values and to automatically assign a risk category for acute appendicitis (high, equivocal, or low), based on the Pediatric Appendicitis Score. We evaluated the performance of the system against a manually created gold standard (chart reviews by ED physicians) for recall, specificity, and precision. The system achieved an average F-measure of 0.867 (0.869 recall and 0.863 precision) for risk classification, which was comparable to physician experts. Recall/precision were 0.897/0.952 in the low-risk category, 0.855/0.886 in the high-risk category, and 0.854/0.766 in the equivocal-risk category. The information that the system required as input to achieve high F-measure was available within the first 4 h of the ED visit. Automated appendicitis risk categorization based on EHR content, including information from clinical notes, shows comparable performance to physician chart reviewers as measured by their inter-annotator agreement and represents a promising new approach for computerized decision support to promote application of evidence-based medicine at the point of care.

Electronic health record - public health (EHR-PH) system prototype for interoperability in 21st century healthcare systems.

PubMed

Orlova, Anna O; Dunnagan, Mark; Finitzo, Terese; Higgins, Michael; Watkins, Todd; Tien, Allen; Beales, Steven

2005-01-01

Information exchange, enabled by computable interoperability, is the key to many of the initiatives underway including the development of Regional Health Information Exchanges, Regional Health Information Organizations, and the National Health Information Network. These initiatives must include public health as a full partner in the emerging transformation of our nation's healthcare system through the adoption and use of information technology. An electronic health record - public health (EHR-PH)system prototype was developed to demonstrate the feasibility of electronic data transfer from a health care provider, i.e. hospital or ambulatory care settings, to multiple customized public health systems which include a Newborn Metabolic Screening Registry, a Newborn Hearing Screening Registry, an Immunization Registry and a Communicable Disease Registry, using HL7 messaging standards. Our EHR-PH system prototype can be considered a distributed EHR-based RHIE/RHIO model - a principal element for a potential technical architecture for a NHIN.

Promoting Secondary Analysis of Electronic Medical Records in China: Summary of the PLAGH-MIT Critical Data Conference and Health Datathon

PubMed Central

Pollard, Tom; Johnson, Alistair Edward William; Cao, Desen; Kang, Hongjun; Liang, Hong; Zhang, Yuezhou; Liu, Xiaoli; Fan, Yong; Zhang, Yuan; Xue, Wanguo; Xie, Lixin; Celi, Leo Anthony

2017-01-01

Electronic health records (EHRs) have been widely adopted among modern hospitals to collect and track clinical data. Secondary analysis of EHRs could complement the traditional randomized control trial (RCT) research model. However, most researchers in China lack either the technical expertise or the resources needed to utilize EHRs as a resource. In addition, a climate of cross-disciplinary collaboration to gain insights from EHRs, a crucial component of a learning healthcare system, is not prevalent. To address these issues, members from the Massachusetts Institute of Technology (MIT) and the People’s Liberation Army General Hospital (PLAGH) organized the first clinical data conference and health datathon in China, which provided a platform for clinicians, statisticians, and data scientists to team up and address information gaps in the intensive care unit (ICU). PMID:29138126

ResearchEHR: use of semantic web technologies and archetypes for the description of EHRs.

PubMed

Robles, Montserrat; Fernández-Breis, Jesualdo Tomás; Maldonado, Jose A; Moner, David; Martínez-Costa, Catalina; Bosca, Diego; Menárguez-Tortosa, Marcos

2010-01-01

In this paper, we present the ResearchEHR project. It focuses on the usability of Electronic Health Record (EHR) sources and EHR standards for building advanced clinical systems. The aim is to support healthcare professional, institutions and authorities by providing a set of generic methods and tools for the capture, standardization, integration, description and dissemination of health related information. ResearchEHR combines several tools to manage EHR at two different levels. The internal level that deals with the normalization and semantic upgrading of exiting EHR by using archetypes and the external level that uses Semantic Web technologies to specify clinical archetypes for advanced EHR architectures and systems.

The Electronic Health Record Objective Structured Clinical Examination: Assessing Student Competency in Patient Interactions While Using the Electronic Health Record.

PubMed

Biagioli, Frances E; Elliot, Diane L; Palmer, Ryan T; Graichen, Carla C; Rdesinski, Rebecca E; Ashok Kumar, Kaparaboyna; Galper, Ari B; Tysinger, James W

2017-01-01

Because many medical students do not have access to electronic health records (EHRs) in the clinical environment, simulated EHR training is necessary. Explicitly training medical students to use EHRs appropriately during patient encounters equips them to engage patients while also attending to the accuracy of the record and contributing to a culture of information safety. Faculty developed and successfully implemented an EHR objective structured clinical examination (EHR-OSCE) for clerkship students at two institutions. The EHR-OSCE objectives include assessing EHR-related communication and data management skills. The authors collected performance data for students (n = 71) at the first institution during academic years 2011-2013 and for students (n = 211) at the second institution during academic year 2013-2014. EHR-OSCE assessment checklist scores showed that students performed well in EHR-related communication tasks, such as maintaining eye contact and stopping all computer work when the patient expresses worry. Findings indicated student EHR skill deficiencies in the areas of EHR data management including medical history review, medication reconciliation, and allergy reconciliation. Most students' EHR skills failed to improve as the year progressed, suggesting that they did not gain the EHR training and experience they need in clinics and hospitals. Cross-institutional data comparisons will help determine whether differences in curricula affect students' EHR skills. National and institutional policies and faculty development are needed to ensure that students receive adequate EHR education, including hands-on experience in the clinic as well as simulated EHR practice.

Patient and public attitudes towards informed consent models and levels of awareness of Electronic Health Records in the UK.

PubMed

Riordan, Fiona; Papoutsi, Chrysanthi; Reed, Julie E; Marston, Cicely; Bell, Derek; Majeed, Azeem

2015-04-01

The development of Electronic Health Records (EHRs) forms an integral part of the information strategy for the National Health Service (NHS) in the UK, with the aim of facilitating health information exchange for patient care and secondary use, including research and healthcare planning. Implementing EHR systems requires an understanding of patient expectations for consent mechanisms and consideration of public awareness towards information sharing as might be made possible through integrated EHRs across primary and secondary health providers. To explore levels of public awareness about EHRs and to examine attitudes towards different consent models with respect to sharing identifiable and de-identified records for healthcare provision, research and planning. A cross-sectional questionnaire survey was administered to adult patients and members of the public in primary and secondary care clinics in West London, UK in 2011. In total, 5331 individuals participated in the survey, and 3157 were included in the final analysis. The majority (91%) of respondents expected to be explicitly asked for consent for their identifiable records to be accessed for health provision, research or planning. Half the respondents (49%) did not expect to be asked for consent before their de-identified records were accessed. Compared with White British respondents, those from all other ethnic groups were more likely to anticipate their permission would be obtained before their de-identified records were used. Of the study population, 59% reported already being aware of EHRs before the survey. Older respondents and individuals with complex patterns of interaction with healthcare services were more likely to report prior awareness of EHRs. Individuals self-identifying as belonging to ethnic groups other than White British, and those with lower educational qualifications were less likely to report being aware of EHRs than White British respondents and respondents with degree-level education, respectively. Those who reported being aware of EHRs were less likely to say they expected explicit consent to be sought before use of their de-identified record. A large number of patients remain unaware of EHRs, while preference for implicit consent is stronger among those who report previous awareness. Differences in awareness levels and consent expectations between groups with different socio-demographic characteristics suggest that public education and information campaigns should target specific groups to increase public awareness and ensure meaningful informed consent mechanisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Open-Source Electronic Health Record Systems for Low-Resource Settings: Systematic Review

PubMed Central

Zolfo, Maria; Diro, Ermias

2017-01-01

Background Despite the great impact of information and communication technologies on clinical practice and on the quality of health services, this trend has been almost exclusive to developed countries, whereas countries with poor resources suffer from many economic and social issues that have hindered the real benefits of electronic health (eHealth) tools. As a component of eHealth systems, electronic health records (EHRs) play a fundamental role in patient management and effective medical care services. Thus, the adoption of EHRs in regions with a lack of infrastructure, untrained staff, and ill-equipped health care providers is an important task. However, the main barrier to adopting EHR software in low- and middle-income countries is the cost of its purchase and maintenance, which highlights the open-source approach as a good solution for these underserved areas. Objective The aim of this study was to conduct a systematic review of open-source EHR systems based on the requirements and limitations of low-resource settings. Methods First, we reviewed existing literature on the comparison of available open-source solutions. In close collaboration with the University of Gondar Hospital, Ethiopia, we identified common limitations in poor resource environments and also the main requirements that EHRs should support. Then, we extensively evaluated the current open-source EHR solutions, discussing their strengths and weaknesses, and their appropriateness to fulfill a predefined set of features relevant for low-resource settings. Results The evaluation methodology allowed assessment of several key aspects of available solutions that are as follows: (1) integrated applications, (2) configurable reports, (3) custom reports, (4) custom forms, (5) interoperability, (6) coding systems, (7) authentication methods, (8) patient portal, (9) access control model, (10) cryptographic features, (11) flexible data model, (12) offline support, (13) native client, (14) Web client,(15) other clients, (16) code-based language, (17) development activity, (18) modularity, (19) user interface, (20) community support, and (21) customization. The quality of each feature is discussed for each of the evaluated solutions and a final comparison is presented. Conclusions There is a clear demand for open-source, reliable, and flexible EHR systems in low-resource settings. In this study, we have evaluated and compared five open-source EHR systems following a multidimensional methodology that can provide informed recommendations to other implementers, developers, and health care professionals. We hope that the results of this comparison can guide decision making when needing to adopt, install, and maintain an open-source EHR solution in low-resource settings. PMID:29133283

Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning.

PubMed

Munkhdalai, Tsendsuren; Liu, Feifan; Yu, Hong

2018-04-25

Medication and adverse drug event (ADE) information extracted from electronic health record (EHR) notes can be a rich resource for drug safety surveillance. Existing observational studies have mainly relied on structured EHR data to obtain ADE information; however, ADEs are often buried in the EHR narratives and not recorded in structured data. To unlock ADE-related information from EHR narratives, there is a need to extract relevant entities and identify relations among them. In this study, we focus on relation identification. This study aimed to evaluate natural language processing and machine learning approaches using the expert-annotated medical entities and relations in the context of drug safety surveillance, and investigate how different learning approaches perform under different configurations. We have manually annotated 791 EHR notes with 9 named entities (eg, medication, indication, severity, and ADEs) and 7 different types of relations (eg, medication-dosage, medication-ADE, and severity-ADE). Then, we explored 3 supervised machine learning systems for relation identification: (1) a support vector machines (SVM) system, (2) an end-to-end deep neural network system, and (3) a supervised descriptive rule induction baseline system. For the neural network system, we exploited the state-of-the-art recurrent neural network (RNN) and attention models. We report the performance by macro-averaged precision, recall, and F1-score across the relation types. Our results show that the SVM model achieved the best average F1-score of 89.1% on test data, outperforming the long short-term memory (LSTM) model with attention (F1-score of 65.72%) as well as the rule induction baseline system (F1-score of 7.47%) by a large margin. The bidirectional LSTM model with attention achieved the best performance among different RNN models. With the inclusion of additional features in the LSTM model, its performance can be boosted to an average F1-score of 77.35%. It shows that classical learning models (SVM) remains advantageous over deep learning models (RNN variants) for clinical relation identification, especially for long-distance intersentential relations. However, RNNs demonstrate a great potential of significant improvement if more training data become available. Our work is an important step toward mining EHRs to improve the efficacy of drug safety surveillance. Most importantly, the annotated data used in this study will be made publicly available, which will further promote drug safety research in the community. ©Tsendsuren Munkhdalai, Feifan Liu, Hong Yu. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 25.04.2018.

Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning

PubMed Central

Munkhdalai, Tsendsuren; Liu, Feifan

2018-01-01

Background Medication and adverse drug event (ADE) information extracted from electronic health record (EHR) notes can be a rich resource for drug safety surveillance. Existing observational studies have mainly relied on structured EHR data to obtain ADE information; however, ADEs are often buried in the EHR narratives and not recorded in structured data. Objective To unlock ADE-related information from EHR narratives, there is a need to extract relevant entities and identify relations among them. In this study, we focus on relation identification. This study aimed to evaluate natural language processing and machine learning approaches using the expert-annotated medical entities and relations in the context of drug safety surveillance, and investigate how different learning approaches perform under different configurations. Methods We have manually annotated 791 EHR notes with 9 named entities (eg, medication, indication, severity, and ADEs) and 7 different types of relations (eg, medication-dosage, medication-ADE, and severity-ADE). Then, we explored 3 supervised machine learning systems for relation identification: (1) a support vector machines (SVM) system, (2) an end-to-end deep neural network system, and (3) a supervised descriptive rule induction baseline system. For the neural network system, we exploited the state-of-the-art recurrent neural network (RNN) and attention models. We report the performance by macro-averaged precision, recall, and F1-score across the relation types. Results Our results show that the SVM model achieved the best average F1-score of 89.1% on test data, outperforming the long short-term memory (LSTM) model with attention (F1-score of 65.72%) as well as the rule induction baseline system (F1-score of 7.47%) by a large margin. The bidirectional LSTM model with attention achieved the best performance among different RNN models. With the inclusion of additional features in the LSTM model, its performance can be boosted to an average F1-score of 77.35%. Conclusions It shows that classical learning models (SVM) remains advantageous over deep learning models (RNN variants) for clinical relation identification, especially for long-distance intersentential relations. However, RNNs demonstrate a great potential of significant improvement if more training data become available. Our work is an important step toward mining EHRs to improve the efficacy of drug safety surveillance. Most importantly, the annotated data used in this study will be made publicly available, which will further promote drug safety research in the community. PMID:29695376

Mixed Influence of Electronic Health Record Implementation on Diabetes Order Patterns for Michigan Medicaid Adults.

PubMed

Corser, William; Yuan, Sha

2015-08-20

These 2011-2013 analyses examined the authors' hypothesis that relative diabetes care order changes would be measured after electronic health record (EHR) implementation for 291 Medicaid adults who received all of their office-based care at one midwestern federally qualified health center (FQHC) over a 24-month period (n = 2727 encounters, 2489 claims). Beneficiary sociodemographic, clinical, and claims data were validated with clinic EHR and state Medicaid claims linked to providers' national identifier numbers. Overall pre-post order rate comparisons, and a series of controlled within group binary logistic models were conducted under penalized maximum likelihood estimation terms. After EHR implementation, both the overall order rates and odds ratios of per beneficiary hemoglobin A1C (HbA1C) orders increased significantly (ie, from mean of 0.65 [SD = 1.19] annual tests to 0.96 tests [SD = 1.24] [P < .001]). Although the overall post-EHR order rates of dilated eye exams and microalbumin urine tests appeared fairly stable, the odds of eye exam orders being placed at the claims level decreased significantly (OR = 0.774, P = .0030). These mixed results provide evidence of the varied diabetes care ordering patterns likely seen from increased office use of EHR technologies. The authors attempt to explain these post-EHR differences (or lack of) that generally resemble some of the authors' results from another funded project. Ideally, these findings provide Medicaid and health care officials with a more realistic indication of how EHRs may, or may not, influence diabetes care ordering patterns for vulnerable lower-income primary health care consumers. © 2015 Diabetes Technology Society.

Writing and reading in the electronic health record: an entirely new world.

PubMed

Han, Heeyoung; Lopp, Lauri

2013-02-05

Electronic health records (EHRs) are structured, distributed documentation systems that differ from paper charts. These systems require skills not traditionally used to navigate a paper chart and to produce a written clinic note. Despite these differences, little attention has been given to physicians' electronic health record (EHR)-writing and -reading competence. This study aims to investigate physicians' self-assessed competence to document and to read EHR notes; writing and reading preferences in an EHR; and demographic characteristics associated with their perceived EHR ability and preference. Fourteen 5-point Likert scale items, based on EHR system characteristics and a literature review, were developed to measure EHR-writing and -reading competence and preference. Physicians in the midwest region of the United States were invited via e-mail to complete the survey online from February to April 2011. Factor analysis and reliability testing were conducted to provide validity and reliability of the instrument. Correlation and regression analysis were conducted to pursue answers to the research questions. Ninety-one physicians (12.5%), from general and specialty fields, working in inpatient and outpatient settings, participated in the survey. Despite over 3 years of EHR experience, respondents perceived themselves to be incompetent in EHR writing and reading (Mean = 2.74, SD = 0.76). They preferred to read succinct, narrative notes in EHR systems. However, physicians with higher perceived EHR-writing and -reading competence had less preference toward reading succinct (r= - 0.33, p<0.001) and narrative (r= - 0.36, p<0.001) EHR notes than physicians with lower perceived EHR competence. Physicians' perceived EHR-writing and -reading competence was strongly related to their EHR navigation skills (r=0.55, p<0.0001). Writing and reading EHR documentation is different for physicians. Maximizing navigation skills can optimize non-linear EHR writing and reading. Pedagogical questions remain related to how physicians and medical students are able to retrieve correct information effectively and to understand thought patterns in collectively lengthier and sometimes fragmented EHR chart notes.

Validating EHR documents: automatic schematron generation using archetypes.

PubMed

Pfeiffer, Klaus; Duftschmid, Georg; Rinner, Christoph

2014-01-01

The goal of this study was to examine whether Schematron schemas can be generated from archetypes. The openEHR Java reference API was used to transform an archetype into an object model, which was then extended with context elements. The model was processed and the constraints were transformed into corresponding Schematron assertions. A prototype of the generator for the reference model HL7 v3 CDA R2 was developed and successfully tested. Preconditions for its reusability with other reference models were set. Our results indicate that an automated generation of Schematron schemas is possible with some limitations.

Computer use in primary care practices in Canada.

PubMed

Anisimowicz, Yvonne; Bowes, Andrea E; Thompson, Ashley E; Miedema, Baukje; Hogg, William E; Wong, Sabrina T; Katz, Alan; Burge, Fred; Aubrey-Bassler, Kris; Yelland, Gregory S; Wodchis, Walter P

2017-05-01

To examine the use of computers in primary care practices. The international Quality and Cost of Primary Care study was conducted in Canada in 2013 and 2014 using a descriptive cross-sectional survey method to collect data from practices across Canada. Participating practices filled out several surveys, one of them being the Family Physician Survey, from which this study collected its data. All 10 Canadian provinces. A total of 788 family physicians. A computer use scale measured the extent to which family physicians integrated computers into their practices, with higher scores indicating a greater integration of computer use in practice. Analyses included t tests and 2 tests comparing new and traditional models of primary care on measures of computer use and electronic health record (EHR) use, as well as descriptive statistics. Nearly all (97.5%) physicians reported using a computer in their practices, with moderately high computer use scale scores (mean [SD] score of 5.97 [2.96] out of 9), and many (65.7%) reported using EHRs. Physicians with practices operating under new models of primary care reported incorporating computers into their practices to a greater extent (mean [SD] score of 6.55 [2.64]) than physicians operating under traditional models did (mean [SD] score of 5.33 [3.15]; t 726.60 = 5.84; P < .001; Cohen d = 0.42, 95% CI 0.808 to 1.627) and were more likely to report using EHRs (73.8% vs 56.7%; [Formula: see text]; P < .001; odds ratio = 2.15). Overall, there was a statistically significant variability in computer use across provinces. Most family physicians in Canada have incorporated computers into their practices for administrative and scholarly activities; however, EHRs have not been adopted consistently across the country. Physicians with practices operating under the new, more collaborative models of primary care use computers more comprehensively and are more likely to use EHRs than those in practices operating under traditional models of primary care. Copyright© the College of Family Physicians of Canada.

Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium

PubMed Central

Pathak, Jyotishman; Bailey, Kent R; Beebe, Calvin E; Bethard, Steven; Carrell, David S; Chen, Pei J; Dligach, Dmitriy; Endle, Cory M; Hart, Lacey A; Haug, Peter J; Huff, Stanley M; Kaggal, Vinod C; Li, Dingcheng; Liu, Hongfang; Marchant, Kyle; Masanz, James; Miller, Timothy; Oniki, Thomas A; Palmer, Martha; Peterson, Kevin J; Rea, Susan; Savova, Guergana K; Stancl, Craig R; Sohn, Sunghwan; Solbrig, Harold R; Suesse, Dale B; Tao, Cui; Taylor, David P; Westberg, Les; Wu, Stephen; Zhuo, Ning; Chute, Christopher G

2013-01-01

Research objective To develop scalable informatics infrastructure for normalization of both structured and unstructured electronic health record (EHR) data into a unified, concept-based model for high-throughput phenotype extraction. Materials and methods Software tools and applications were developed to extract information from EHRs. Representative and convenience samples of both structured and unstructured data from two EHR systems—Mayo Clinic and Intermountain Healthcare—were used for development and validation. Extracted information was standardized and normalized to meaningful use (MU) conformant terminology and value set standards using Clinical Element Models (CEMs). These resources were used to demonstrate semi-automatic execution of MU clinical-quality measures modeled using the Quality Data Model (QDM) and an open-source rules engine. Results Using CEMs and open-source natural language processing and terminology services engines—namely, Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) and Common Terminology Services (CTS2)—we developed a data-normalization platform that ensures data security, end-to-end connectivity, and reliable data flow within and across institutions. We demonstrated the applicability of this platform by executing a QDM-based MU quality measure that determines the percentage of patients between 18 and 75 years with diabetes whose most recent low-density lipoprotein cholesterol test result during the measurement year was <100 mg/dL on a randomly selected cohort of 273 Mayo Clinic patients. The platform identified 21 and 18 patients for the denominator and numerator of the quality measure, respectively. Validation results indicate that all identified patients meet the QDM-based criteria. Conclusions End-to-end automated systems for extracting clinical information from diverse EHR systems require extensive use of standardized vocabularies and terminologies, as well as robust information models for storing, discovering, and processing that information. This study demonstrates the application of modular and open-source resources for enabling secondary use of EHR data through normalization into standards-based, comparable, and consistent format for high-throughput phenotyping to identify patient cohorts. PMID:24190931

Observing health professionals' workflow patterns for diabetes care - First steps towards an ontology for EHR services.

PubMed

Schweitzer, M; Lasierra, N; Hoerbst, A

2015-01-01

Increasing the flexibility from a user-perspective and enabling a workflow based interaction, facilitates an easy user-friendly utilization of EHRs for healthcare professionals' daily work. To offer such versatile EHR-functionality, our approach is based on the execution of clinical workflows by means of a composition of semantic web-services. The backbone of such architecture is an ontology which enables to represent clinical workflows and facilitates the selection of suitable services. In this paper we present the methods and results after running observations of diabetes routine consultations which were conducted in order to identify those workflows and the relation among the included tasks. Mentioned workflows were first modeled by BPMN and then generalized. As a following step in our study, interviews will be conducted with clinical personnel to validate modeled workflows.

Integrating clinical research with the Healthcare Enterprise: from the RE-USE project to the EHR4CR platform.

PubMed

El Fadly, AbdenNaji; Rance, Bastien; Lucas, Noël; Mead, Charles; Chatellier, Gilles; Lastic, Pierre-Yves; Jaulent, Marie-Christine; Daniel, Christel

2011-12-01

There are different approaches for repurposing clinical data collected in the Electronic Healthcare Record (EHR) for use in clinical research. Semantic integration of "siloed" applications across domain boundaries is the raison d'être of the standards-based profiles developed by the Integrating the Healthcare Enterprise (IHE) initiative - an initiative by healthcare professionals and industry promoting the coordinated use of established standards such as DICOM and HL7 to address specific clinical needs in support of optimal patient care. In particular, the combination of two IHE profiles - the integration profile "Retrieve Form for Data Capture" (RFD), and the IHE content profile "Clinical Research Document" (CRD) - offers a straightforward approach to repurposing EHR data by enabling the pre-population of the case report forms (eCRF) used for clinical research data capture by Clinical Data Management Systems (CDMS) with previously collected EHR data. Implement an alternative solution of the RFD-CRD integration profile centered around two approaches: (i) Use of the EHR as the single-source data-entry and persistence point in order to ensure that all the clinical data for a given patient could be found in a single source irrespective of the data collection context, i.e. patient care or clinical research; and (ii) Maximize the automatic pre-population process through the use of a semantic interoperability services that identify duplicate or semantically-equivalent eCRF/EHR data elements as they were collected in the EHR context. The RE-USE architecture and associated profiles are focused on defining a set of scalable, standards-based, IHE-compliant profiles that can enable single-source data collection/entry and cross-system data reuse through semantic integration. Specifically, data reuse is realized through the semantic mapping of data collection fields in electronic Case Report Forms (eCRFs) to data elements previously defined as part of patient care-centric templates in the EHR context. The approach was evaluated in the context of a multi-center clinical trial conducted in a large, multi-disciplinary hospital with an installed EHR. Data elements of seven eCRFs used in a multi-center clinical trial were mapped to data elements of patient care-centric templates in use in the EHR at the George Pompidou hospital. 13.4% of the data elements of the eCRFs were found to be represented in EHR templates and were therefore candidate for pre-population. During the execution phase of the clinical study, the semantic mapping architecture enabled data persisted in the EHR context as part of clinical care to be used to pre-populate eCRFS for use without secondary data entry. To ensure that the pre-populated data is viable for use in the clinical research context, all pre-populated eCRF data needs to be first approved by a trial investigator prior to being persisted in a research data store within a CDMS. Single-source data entry in the clinical care context for use in the clinical research context - a process enabled through the use of the EHR as single point of data entry, can - if demonstrated to be a viable strategy - not only significantly reduce data collection efforts while simultaneously increasing data collection accuracy secondary to elimination of transcription or double-entry errors between the two contexts but also ensure that all the clinical data for a given patient, irrespective of the data collection context, are available in the EHR for decision support and treatment planning. The RE-USE approach used mapping algorithms to identify semantic coherence between clinical care and clinical research data elements and pre-populate eCRFs. The RE-USE project utilized SNOMED International v.3.5 as its "pivot reference terminology" to support EHR-to-eCRF mapping, a decision that likely enhanced the "recall" of the mapping algorithms. The RE-USE results demonstrate the difficult challenges involved in semantic integration between the clinical care and clinical research contexts. Copyright © 2011 Elsevier Inc. All rights reserved.

Generation of openEHR Test Datasets for Benchmarking.

PubMed

El Helou, Samar; Karvonen, Tuukka; Yamamoto, Goshiro; Kume, Naoto; Kobayashi, Shinji; Kondo, Eiji; Hiragi, Shusuke; Okamoto, Kazuya; Tamura, Hiroshi; Kuroda, Tomohiro

2017-01-01

openEHR is a widely used EHR specification. Given its technology-independent nature, different approaches for implementing openEHR data repositories exist. Public openEHR datasets are needed to conduct benchmark analyses over different implementations. To address their current unavailability, we propose a method for generating openEHR test datasets that can be publicly shared and used.

Open source electronic health records and chronic disease management.

PubMed

Goldwater, Jason C; Kwon, Nancy J; Nathanson, Ashley; Muckle, Alison E; Brown, Alexa; Cornejo, Kerri

2014-02-01

To study and report on the use of open source electronic health records (EHR) to assist with chronic care management within safety net medical settings, such as community health centers (CHC). The study was conducted by NORC at the University of Chicago from April to September 2010. The NORC team undertook a comprehensive environmental scan, including a literature review, a dozen key informant interviews using a semistructured protocol, and a series of site visits to CHC that currently use an open source EHR. Two of the sites chosen by NORC were actively using an open source EHR to assist in the redesign of their care delivery system to support more effective chronic disease management. This included incorporating the chronic care model into an CHC and using the EHR to help facilitate its elements, such as care teams for patients, in addition to maintaining health records on indigent populations, such as tuberculosis status on homeless patients. The ability to modify the open-source EHR to adapt to the CHC environment and leverage the ecosystem of providers and users to assist in this process provided significant advantages in chronic care management. Improvements in diabetes management, controlled hypertension and increases in tuberculosis vaccinations were assisted through the use of these open source systems. The flexibility and adaptability of open source EHR demonstrated its utility and viability in the provision of necessary and needed chronic disease care among populations served by CHC.

Bidirectional RNN for Medical Event Detection in Electronic Health Records.

PubMed

Jagannatha, Abhyuday N; Yu, Hong

2016-06-01

Sequence labeling for extraction of medical events and their attributes from unstructured text in Electronic Health Record (EHR) notes is a key step towards semantic understanding of EHRs. It has important applications in health informatics including pharmacovigilance and drug surveillance. The state of the art supervised machine learning models in this domain are based on Conditional Random Fields (CRFs) with features calculated from fixed context windows. In this application, we explored recurrent neural network frameworks and show that they significantly out-performed the CRF models.

Challenges of interoperability using HL7 v3 in Czech healthcare.

PubMed

Nagy, Miroslav; Preckova, Petra; Seidl, Libor; Zvarova, Jana

2010-01-01

The paper describes several classification systems that could improve patient safety through semantic interoperability among contemporary electronic health record systems (EHR-Ss) with support of the HL7 v3 standard. We describe a proposal and a pilot implementation of a semantic interoperability platform (SIP) interconnecting current EHR-Ss by using HL7 v3 messages and concepts mappings on most widely used classification systems. The increasing number of classification systems and nomenclatures requires designing of various conversion tools for transfer between main classification systems. We present the so-called LIM filler module and the HL7 broker, which are parts of the SIP, playing the role of such conversion tools. The analysis of suitability and usability of individual terminological thesauri has been started by mapping of clinical contents of the Minimal Data Model for Cardiology (MDMC) to various terminological classification systems. A national-wide implementation of the SIP would include adopting and translating international coding systems and nomenclatures, and developing implementation guidelines facilitating the migration from national standards to international ones. Our research showed that creation of such a platform is feasible; however, it will require a huge effort to adapt fully the Czech healthcare system to the European environment.

A patient centered care plan in the EHR: improving collaboration and engagement.

PubMed

Chunchu, Kavitha; Mauksch, Larry; Charles, Carol; Ross, Valerie; Pauwels, Judith

2012-09-01

Patients attempting to manage their chronic conditions require ongoing support in changing and adopting self-management behaviors. However, patient values, health goals, and action plans are not well represented in the electronic health record (EHR) impeding the ability of the team (MA and providers) to provide respectful, ongoing self-management support. We evaluated whether a team approach to using an EHR based patient centered care plan (PCCP) improved collaborative self-management planning. An experimental, prospective cohort study was conducted in a family medicine residency clinic. The experimental group included 7 physicians and a medical assistant who received 2 hr of PCCP training. The control group consisted of 7 physicians and a medical assistant. EHR charts were analyzed for evidence of 8 behavior change elements. Follow-up interviews with experimental group patients and physicians and the medical assistant assessed their experiences. We found that PCCP charts had more documented behavior change elements than control charts in all 8 domains (p < .001). Experimental group physicians valued the PCCP model and suggested ways to improve its use. Patient feedback demonstrated support for the model. A PCCP can help team members to engage patients with chronic illnesses in goal setting and action planning to support self-management. An EHR design that stores patient values, health goals, and action plans may strengthen continuity and quality of care between patients and primary care team members. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Trust and Privacy in Healthcare

NASA Astrophysics Data System (ADS)

Singleton, Peter; Kalra, Dipak

This paper considers issues of trust and privacy in healthcare around increased data-sharing through Electronic Health Records (EHRs). It uses a model structured around different aspects of trust in the healthcare organisation’s reasons for greater data-sharing and their ability to execute EHR projects, particularly any associated confidentiality controls. It reflects the individual’s personal circumstances and attitude to use of health records.

Quality requirements for EHR archetypes.

PubMed

Kalra, Dipak; Tapuria, Archana; Austin, Tony; De Moor, Georges

2012-01-01

The realisation of semantic interoperability, in which any EHR data may be communicated between heterogeneous systems and fully understood by computers as well as people on receipt, is a challenging goal. Despite the use of standardised generic models for the EHR and standard terminology systems, too much optionality and variability exists in how particular clinical entries may be represented. Clinical archetypes provide a means of defining how generic models should be shaped and bound to terminology for specific kinds of clinical data. However, these will only contribute to semantic interoperability if libraries of archetypes can be built up consistently. This requires the establishment of design principles, editorial and governance policies, and further research to develop ways for archetype authors to structure clinical data and to use terminology consistently. Drawing on several years of work within communities of practice developing archetypes and implementing systems from them, this paper presents quality requirements for the development of archetypes. Clinical engagement on a wide scale is also needed to help grow libraries of good quality archetypes that can be certified. Vendor and eHealth programme engagement is needed to validate such archetypes and achieve safe, meaningful exchange of EHR data between systems.

Sparse modeling of spatial environmental variables associated with asthma

PubMed Central

Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.

2014-01-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437

Sparse modeling of spatial environmental variables associated with asthma.

PubMed

Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

2015-02-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Electronic health records improve clinical note quality.

PubMed

Burke, Harry B; Sessums, Laura L; Hoang, Albert; Becher, Dorothy A; Fontelo, Paul; Liu, Fang; Stephens, Mark; Pangaro, Louis N; O'Malley, Patrick G; Baxi, Nancy S; Bunt, Christopher W; Capaldi, Vincent F; Chen, Julie M; Cooper, Barbara A; Djuric, David A; Hodge, Joshua A; Kane, Shawn; Magee, Charles; Makary, Zizette R; Mallory, Renee M; Miller, Thomas; Saperstein, Adam; Servey, Jessica; Gimbel, Ronald W

2015-01-01

The clinical note documents the clinician's information collection, problem assessment, clinical management, and its used for administrative purposes. Electronic health records (EHRs) are being implemented in clinical practices throughout the USA yet it is not known whether they improve the quality of clinical notes. The goal in this study was to determine if EHRs improve the quality of outpatient clinical notes. A five and a half year longitudinal retrospective multicenter quantitative study comparing the quality of handwritten and electronic outpatient clinical visit notes for 100 patients with type 2 diabetes at three time points: 6 months prior to the introduction of the EHR (before-EHR), 6 months after the introduction of the EHR (after-EHR), and 5 years after the introduction of the EHR (5-year-EHR). QNOTE, a validated quantitative instrument, was used to assess the quality of outpatient clinical notes. Its scores can range from a low of 0 to a high of 100. Sixteen primary care physicians with active practices used QNOTE to determine the quality of the 300 patient notes. The before-EHR, after-EHR, and 5-year-EHR grand mean scores (SD) were 52.0 (18.4), 61.2 (16.3), and 80.4 (8.9), respectively, and the change in scores for before-EHR to after-EHR and before-EHR to 5-year-EHR were 18% (p<0.0001) and 55% (p<0.0001), respectively. All the element and grand mean quality scores significantly improved over the 5-year time interval. The EHR significantly improved the overall quality of the outpatient clinical note and the quality of all its elements, including the core and non-core elements. To our knowledge, this is the first study to demonstrate that the EHR significantly improves the quality of clinical notes. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Using statistical and machine learning to help institutions detect suspicious access to electronic health records.

PubMed

Boxwala, Aziz A; Kim, Jihoon; Grillo, Janice M; Ohno-Machado, Lucila

2011-01-01

To determine whether statistical and machine-learning methods, when applied to electronic health record (EHR) access data, could help identify suspicious (ie, potentially inappropriate) access to EHRs. From EHR access logs and other organizational data collected over a 2-month period, the authors extracted 26 features likely to be useful in detecting suspicious accesses. Selected events were marked as either suspicious or appropriate by privacy officers, and served as the gold standard set for model evaluation. The authors trained logistic regression (LR) and support vector machine (SVM) models on 10-fold cross-validation sets of 1291 labeled events. The authors evaluated the sensitivity of final models on an external set of 58 events that were identified as truly inappropriate and investigated independently from this study using standard operating procedures. The area under the receiver operating characteristic curve of the models on the whole data set of 1291 events was 0.91 for LR, and 0.95 for SVM. The sensitivity of the baseline model on this set was 0.8. When the final models were evaluated on the set of 58 investigated events, all of which were determined as truly inappropriate, the sensitivity was 0 for the baseline method, 0.76 for LR, and 0.79 for SVM. The LR and SVM models may not generalize because of interinstitutional differences in organizational structures, applications, and workflows. Nevertheless, our approach for constructing the models using statistical and machine-learning techniques can be generalized. An important limitation is the relatively small sample used for the training set due to the effort required for its construction. The results suggest that statistical and machine-learning methods can play an important role in helping privacy officers detect suspicious accesses to EHRs.

Using statistical and machine learning to help institutions detect suspicious access to electronic health records

PubMed Central

Kim, Jihoon; Grillo, Janice M; Ohno-Machado, Lucila

2011-01-01

Objective To determine whether statistical and machine-learning methods, when applied to electronic health record (EHR) access data, could help identify suspicious (ie, potentially inappropriate) access to EHRs. Methods From EHR access logs and other organizational data collected over a 2-month period, the authors extracted 26 features likely to be useful in detecting suspicious accesses. Selected events were marked as either suspicious or appropriate by privacy officers, and served as the gold standard set for model evaluation. The authors trained logistic regression (LR) and support vector machine (SVM) models on 10-fold cross-validation sets of 1291 labeled events. The authors evaluated the sensitivity of final models on an external set of 58 events that were identified as truly inappropriate and investigated independently from this study using standard operating procedures. Results The area under the receiver operating characteristic curve of the models on the whole data set of 1291 events was 0.91 for LR, and 0.95 for SVM. The sensitivity of the baseline model on this set was 0.8. When the final models were evaluated on the set of 58 investigated events, all of which were determined as truly inappropriate, the sensitivity was 0 for the baseline method, 0.76 for LR, and 0.79 for SVM. Limitations The LR and SVM models may not generalize because of interinstitutional differences in organizational structures, applications, and workflows. Nevertheless, our approach for constructing the models using statistical and machine-learning techniques can be generalized. An important limitation is the relatively small sample used for the training set due to the effort required for its construction. Conclusion The results suggest that statistical and machine-learning methods can play an important role in helping privacy officers detect suspicious accesses to EHRs. PMID:21672912

Evaluating Model-Driven Development for large-scale EHRs through the openEHR approach.

PubMed

Christensen, Bente; Ellingsen, Gunnar

2016-05-01

In healthcare, the openEHR standard is a promising Model-Driven Development (MDD) approach for electronic healthcare records. This paper aims to identify key socio-technical challenges when the openEHR approach is put to use in Norwegian hospitals. More specifically, key fundamental assumptions are investigated empirically. These assumptions promise a clear separation of technical and domain concerns, users being in control of the modelling process, and widespread user commitment. Finally, these assumptions promise an easy way to model and map complex organizations. This longitudinal case study is based on an interpretive approach, whereby data were gathered through 440h of participant observation, 22 semi-structured interviews and extensive document studies over 4 years. The separation of clinical and technical concerns seemed to be aspirational, because both designing the technical system and modelling the domain required technical and clinical competence. Hence developers and clinicians found themselves working together in both arenas. User control and user commitment seemed not to apply in large-scale projects, as modelling the domain turned out to be too complicated and hence to appeal only to especially interested users worldwide, not the local end-users. Modelling proved to be a complex standardization process that shaped both the actual modelling and healthcare practice itself. A broad assemblage of contributors seems to be needed for developing an archetype-based system, in which roles, responsibilities and contributions cannot be clearly defined and delimited. The way MDD occurs has implications for medical practice per se in the form of the need to standardize practices to ensure that medical concepts are uniform across practices. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Electronic Health Record Design and Implementation for Pharmacogenomics: a Local Perspective

PubMed Central

Peterson, Josh F.; Bowton, Erica; Field, Julie R.; Beller, Marc; Mitchell, Jennifer; Schildcrout, Jonathan; Gregg, William; Johnson, Kevin; Jirjis, Jim N; Roden, Dan M.; Pulley, Jill M.; Denny, Josh C.

2014-01-01

Purpose The design of electronic health records (EHR) to translate genomic medicine into clinical care is crucial to successful introduction of new genomic services, yet there are few published guides to implementation. Methods The design, implemented features, and evolution of a locally developed EHR that supports a large pharmacogenomics program at a tertiary care academic medical center was tracked over a 4-year development period. Results Developers and program staff created EHR mechanisms for ordering a pharmacogenomics panel in advance of clinical need (preemptive genotyping) and in response to a specific drug indication. Genetic data from panel-based genotyping were sequestered from the EHR until drug-gene interactions (DGIs) met evidentiary standards and deemed clinically actionable. A service to translate genotype to predicted drug response phenotype populated a summary of DGIs, triggered inpatient and outpatient clinical decision support, updated laboratory records, and created gene results within online personal health records. Conclusion The design of a locally developed EHR supporting pharmacogenomics has generalizable utility. The challenge of representing genomic data in a comprehensible and clinically actionable format is discussed along with reflection on the scalability of the model to larger sets of genomic data. PMID:24009000

Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients.

PubMed

Chen, Jinying; Yu, Hong

2017-04-01

Allowing patients to access their own electronic health record (EHR) notes through online patient portals has the potential to improve patient-centered care. However, EHR notes contain abundant medical jargon that can be difficult for patients to comprehend. One way to help patients is to reduce information overload and help them focus on medical terms that matter most to them. Targeted education can then be developed to improve patient EHR comprehension and the quality of care. The aim of this work was to develop FIT (Finding Important Terms for patients), an unsupervised natural language processing (NLP) system that ranks medical terms in EHR notes based on their importance to patients. We built FIT on a new unsupervised ensemble ranking model derived from the biased random walk algorithm to combine heterogeneous information resources for ranking candidate terms from each EHR note. Specifically, FIT integrates four single views (rankers) for term importance: patient use of medical concepts, document-level term salience, word co-occurrence based term relatedness, and topic coherence. It also incorporates partial information of term importance as conveyed by terms' unfamiliarity levels and semantic types. We evaluated FIT on 90 expert-annotated EHR notes and used the four single-view rankers as baselines. In addition, we implemented three benchmark unsupervised ensemble ranking methods as strong baselines. FIT achieved 0.885 AUC-ROC for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FIT for identifying important terms from EHR notes was 0.813 AUC-ROC. Both performance scores significantly exceeded the corresponding scores from the four single rankers (P<0.001). FIT also outperformed the three ensemble rankers for most metrics. Its performance is relatively insensitive to its parameter. FIT can automatically identify EHR terms important to patients. It may help develop future interventions to improve quality of care. By using unsupervised learning as well as a robust and flexible framework for information fusion, FIT can be readily applied to other domains and applications. Copyright © 2017 Elsevier Inc. All rights reserved.

Detailed clinical models: representing knowledge, data and semantics in healthcare information technology.

PubMed

Goossen, William T F

2014-07-01

This paper will present an overview of the developmental effort in harmonizing clinical knowledge modeling using the Detailed Clinical Models (DCMs), and will explain how it can contribute to the preservation of Electronic Health Records (EHR) data. Clinical knowledge modeling is vital for the management and preservation of EHR and data. Such modeling provides common data elements and terminology binding with the intention of capturing and managing clinical information over time and location independent from technology. Any EHR data exchange without an agreed clinical knowledge modeling will potentially result in loss of information. Many attempts exist from the past to model clinical knowledge for the benefits of semantic interoperability using standardized data representation and common terminologies. The objective of each project is similar with respect to consistent representation of clinical data, using standardized terminologies, and an overall logical approach. However, the conceptual, logical, and the technical expressions are quite different in one clinical knowledge modeling approach versus another. There currently are synergies under the Clinical Information Modeling Initiative (CIMI) in order to create a harmonized reference model for clinical knowledge models. The goal for the CIMI is to create a reference model and formalisms based on for instance the DCM (ISO/TS 13972), among other work. A global repository of DCMs may potentially be established in the future.

An evaluation of the NQF Quality Data Model for representing Electronic Health Record driven phenotyping algorithms.

PubMed

Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Peissig, Peggy L; Denny, Joshua C; Kho, Abel N; Miller, Aaron; Pathak, Jyotishman

2012-01-01

The development of Electronic Health Record (EHR)-based phenotype selection algorithms is a non-trivial and highly iterative process involving domain experts and informaticians. To make it easier to port algorithms across institutions, it is desirable to represent them using an unambiguous formal specification language. For this purpose we evaluated the recently developed National Quality Forum (NQF) information model designed for EHR-based quality measures: the Quality Data Model (QDM). We selected 9 phenotyping algorithms that had been previously developed as part of the eMERGE consortium and translated them into QDM format. Our study concluded that the QDM contains several core elements that make it a promising format for EHR-driven phenotyping algorithms for clinical research. However, we also found areas in which the QDM could be usefully extended, such as representing information extracted from clinical text, and the ability to handle algorithms that do not consist of Boolean combinations of criteria.

Meaningful Use of Electronic Health Records and Medicare Expenditures: Evidence from a Panel Data Analysis of U.S. Health Care Markets, 2010-2013.

PubMed

Lammers, Eric J; McLaughlin, Catherine G

2017-08-01

To determine if recent growth in hospital and physician electronic health record (EHR) adoption and use is correlated with decreases in expenditures for elderly Medicare beneficiaries. American Hospital Association (AHA) General Survey and Information Technology Supplement, Health Information Management Systems Society (HIMSS) Analytics survey, SK&A Information Services, and the Centers for Medicare & Medicaid Services (CMS) Chronic Conditions Data Warehouse Geographic Variation Database for 2010 through 2013. Fixed effects model comparing associations between hospital referral region (HRR) level measures of hospital and physician EHR penetration and annual Medicare expenditures for beneficiaries with one of four chronic conditions. Calculated hospital penetration rates as the percentage of Medicare discharges from hospitals that satisfied criteria analogous to Meaningful Use (MU) Stage 1 requirements and physician rates as the percentage of physicians using ambulatory care EHRs. An increase in the hospital penetration rate was associated with a small but statistically significant decrease in total Medicare and Medicare Part A acute care expenditures per beneficiary. An increase in physician EHR penetration was also associated with a significant decrease in total Medicare and Medicare Part A acute care expenditures per beneficiary as well as a decrease in Medicare Part B expenditures per beneficiary. For the study population, we estimate approximately $3.8 billion in savings related to hospital and physician EHR adoption during 2010-2013. We also found that an increase in physician EHR penetration was associated with an increase in lab test expenses. Health care markets that had steeper increases in EHR penetration during 2010-2013 also had steeper decreases in total Medicare and acute care expenditures per beneficiary. Markets with greater increases in physician EHR had greater declines in Medicare Part B expenditures per beneficiary. © Health Research and Educational Trust.

Modeling Disease Severity in Multiple Sclerosis Using Electronic Health Records

PubMed Central

Xia, Zongqi; Secor, Elizabeth; Chibnik, Lori B.; Bove, Riley M.; Cheng, Suchun; Chitnis, Tanuja; Cagan, Andrew; Gainer, Vivian S.; Chen, Pei J.; Liao, Katherine P.; Shaw, Stanley Y.; Ananthakrishnan, Ashwin N.; Szolovits, Peter; Weiner, Howard L.; Karlson, Elizabeth W.; Murphy, Shawn N.; Savova, Guergana K.; Cai, Tianxi; Churchill, Susanne E.; Plenge, Robert M.; Kohane, Isaac S.; De Jager, Philip L.

2013-01-01

Objective To optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of principle, we showcased how to leverage routinely collected EHR data to identify patients with a complex neurological disorder and derive an important surrogate measure of disease severity heretofore only available in research settings. Methods In a cross-sectional observational study, 5,495 MS patients were identified from the EHR systems of two major referral hospitals using an algorithm that includes codified and narrative information extracted using natural language processing. In the subset of patients who receive neurological care at a MS Center where disease measures have been collected, we used routinely collected EHR data to extract two aggregate indicators of MS severity of clinical relevance multiple sclerosis severity score (MSSS) and brain parenchymal fraction (BPF, a measure of whole brain volume). Results The EHR algorithm that identifies MS patients has an area under the curve of 0.958, 83% sensitivity, 92% positive predictive value, and 89% negative predictive value when a 95% specificity threshold is used. The correlation between EHR-derived and true MSSS has a mean R2 = 0.38±0.05, and that between EHR-derived and true BPF has a mean R2 = 0.22±0.08. To illustrate its clinical relevance, derived MSSS captures the expected difference in disease severity between relapsing-remitting and progressive MS patients after adjusting for sex, age of symptom onset and disease duration (p = 1.56×10−12). Conclusion Incorporation of sophisticated codified and narrative EHR data accurately identifies MS patients and provides estimation of a well-accepted indicator of MS severity that is widely used in research settings but not part of the routine medical records. Similar approaches could be applied to other complex neurological disorders. PMID:24244385

Security and privacy in electronic health records: a systematic literature review.

PubMed

Fernández-Alemán, José Luis; Señor, Inmaculada Carrión; Lozoya, Pedro Ángel Oliver; Toval, Ambrosio

2013-06-01

To report the results of a systematic literature review concerning the security and privacy of electronic health record (EHR) systems. Original articles written in English found in MEDLINE, ACM Digital Library, Wiley InterScience, IEEE Digital Library, Science@Direct, MetaPress, ERIC, CINAHL and Trip Database. Only those articles dealing with the security and privacy of EHR systems. The extraction of 775 articles using a predefined search string, the outcome of which was reviewed by three authors and checked by a fourth. A total of 49 articles were selected, of which 26 used standards or regulations related to the privacy and security of EHR data. The most widely used regulations are the Health Insurance Portability and Accountability Act (HIPAA) and the European Data Protection Directive 95/46/EC. We found 23 articles that used symmetric key and/or asymmetric key schemes and 13 articles that employed the pseudo anonymity technique in EHR systems. A total of 11 articles propose the use of a digital signature scheme based on PKI (Public Key Infrastructure) and 13 articles propose a login/password (seven of them combined with a digital certificate or PIN) for authentication. The preferred access control model appears to be Role-Based Access Control (RBAC), since it is used in 27 studies. Ten of these studies discuss who should define the EHR systems' roles. Eleven studies discuss who should provide access to EHR data: patients or health entities. Sixteen of the articles reviewed indicate that it is necessary to override defined access policies in the case of an emergency. In 25 articles an audit-log of the system is produced. Only four studies mention that system users and/or health staff should be trained in security and privacy. Recent years have witnessed the design of standards and the promulgation of directives concerning security and privacy in EHR systems. However, more work should be done to adopt these regulations and to deploy secure EHR systems. Copyright © 2013 Elsevier Inc. All rights reserved.

Measuring use of electronic health record functionality using system audit information.

PubMed

Bowes, Watson A

2010-01-01

Meaningful and efficient methods for measuring Electronic Health Record (EHR) adoption and functional usage patterns have recently become important for hospitals, clinics, and health care networks in the United State due to recent government initiatives to increase EHR use. To date, surveys have been the method of choice to measure EHR adoption. This paper describes another method for measuring EHR adoption which capitalizes on audit logs, which are often common components of modern EHRs. An Audit Data Mart is described which identified EHR functionality within 836 Departments, within 22 Hospitals and 170 clinics at Intermountain Healthcare, a large integrated delivery system. The Audit Data Mart successfully identified important and differing EHR functional usage patterns. These patterns were useful in strategic planning, tracking EHR implementations, and will likely be utilized to assist in documentation of "Meaningful Use" of EHR functionality.

[Smart eye data : Development of a foundation for medical research using Smart Data applications].

PubMed

Kortüm, K; Müller, M; Hirneiß, C; Babenko, A; Nasseh, D; Kern, C; Kampik, A; Priglinger, S; Kreutzer, T C

2016-06-01

Smart Data means intelligent data accumulation and the evaluation of large data sets. This is particularly important in ophthalmology as more and more data are being created. Increasing knowledge and personalized therapies are expected by combining clinical data from electronic health records (EHR) with measurement data. In this study we investigated the possibilities to consolidate data from measurement devices and clinical data in a data warehouse (DW). An EHR was adjusted to the needs of ophthalmology and the contents of referral letters were extracted. The data were imported into a DW overnight. Measuring devices were connected to the EHR by an HL7 standard interface and the use of a picture archiving and communications system (PACS). Data were exported from the review software using a self-developed software. For data analysis the software was modified to the specific requirements of ophthalmology. In the EHR 12 graphical user interfaces were created and the data from 32,234 referral letters were extracted. A total of 23 diagnostic devices could be linked to the PACS and 85,114 optical coherence tomography (OCT) scans, 19,098 measurements from IOLMaster as well as 5,425 pentacam examinations were imported into the DW including over 300,000 patients. Data discovery software was modified providing filtering methods. By building a DW a foundation for clinical and epidemiological studies could be implemented. In the future, decision support systems and strategies for personalized therapies can be based on such a database.

Development of a Cancer Care Summary Through the Electronic Health Record.

PubMed

Carr, Laurie L; Zelarney, Pearlanne; Meadows, Sarah; Kern, Jeffrey A; Long, M Bronwyn; Kern, Elizabeth

2016-02-01

Our objective was to improve communication concerning lung cancer patients by developing and distributing a Cancer Care Summary that would provide clinically useful information about the patient's diagnosis and care to providers in diverse settings. We designed structured, electronic forms for the electronic health record (EHR), detailing tumor staging, classification, and treatment. To ensure completeness and accuracy of the information, we implemented a data quality cycle, composed of reports that are reviewed by oncology clinicians. The data from the EHR forms are extracted into a structured query language database system on a daily basis, from which the Summaries are derived. We conducted focus groups regarding the utility, format, and content of the Summary. Cancer Care Summaries are automatically generated 4 months after a patient's date of diagnosis, then every 6 months for those receiving treatment, and on an as-needed basis for urgent care or hospital admission. The product of our improvement project is the Cancer Care Summary. To date, 102 individual patient Summaries have been generated. These documents are automatically entered into the National Jewish Health (NJH) EHR, attached to correspondence to primary care providers, available to patients as electronic documents on the NJH patient portal, and faxed to emergency departments and admitting physicians on patient evaluation. We developed a sustainable tool to improve cancer care communication. The Cancer Care Summary integrates information from the EHR in a timely manner and distributes the information through multiple avenues. Copyright © 2016 by American Society of Clinical Oncology.

Development of Hospital-based Data Sets as a Vehicle for Implementation of a National Electronic Health Record

PubMed Central

Keikha, Leila; Farajollah, Seyede Sedigheh Seied; Safdari, Reza; Ghazisaeedi, Marjan; Mohammadzadeh, Niloofar

2018-01-01

Background In developing countries such as Iran, international standards offer good sources to survey and use for appropriate planning in the domain of electronic health records (EHRs). Therefore, in this study, HL7 and ASTM standards were considered as the main sources from which to extract EHR data. Objective The objective of this study was to propose a hospital data set for a national EHR consisting of data classes and data elements by adjusting data sets extracted from the standards and paper-based records. Method This comparative study was carried out in 2017 by studying the contents of the paper-based records approved by the health ministry in Iran and the international ASTM and HL7 standards in order to extract a minimum hospital data set for a national EHR. Results As a result of studying the standards and paper-based records, a total of 526 data elements in 174 classes were extracted. An examination of the data indicated that the highest number of extracted data came from the free text elements, both in the paper-based records and in the standards related to the administrative data. The major sources of data extracted from ASTM and HL7 were the E1384 and Hl7V.x standards, respectively. In the paper-based records, data were extracted from 19 forms sporadically. Discussion By declaring the confidentiality of information, the ASTM standards acknowledge the issue of confidentiality of information as one of the main challenges of EHR development, and propose new types of admission, such as teleconference, tele-video, and home visit, which are inevitable with the advent of new technology for providing healthcare and treating diseases. Data related to finance and insurance, which were scattered in different categories by three organizations, emerged as the financial category. Documenting the role and responsibility of the provider by adding the authenticator/signature data element was deemed essential. Conclusion Not only using well-defined and standardized data, but also adapting EHR systems to the local facilities and the existing social and cultural conditions, will facilitate the development of structured data sets. PMID:29618962

Development of Hospital-based Data Sets as a Vehicle for Implementation of a National Electronic Health Record.

PubMed

Keikha, Leila; Farajollah, Seyede Sedigheh Seied; Safdari, Reza; Ghazisaeedi, Marjan; Mohammadzadeh, Niloofar

2018-01-01

In developing countries such as Iran, international standards offer good sources to survey and use for appropriate planning in the domain of electronic health records (EHRs). Therefore, in this study, HL7 and ASTM standards were considered as the main sources from which to extract EHR data. The objective of this study was to propose a hospital data set for a national EHR consisting of data classes and data elements by adjusting data sets extracted from the standards and paper-based records. This comparative study was carried out in 2017 by studying the contents of the paper-based records approved by the health ministry in Iran and the international ASTM and HL7 standards in order to extract a minimum hospital data set for a national EHR. As a result of studying the standards and paper-based records, a total of 526 data elements in 174 classes were extracted. An examination of the data indicated that the highest number of extracted data came from the free text elements, both in the paper-based records and in the standards related to the administrative data. The major sources of data extracted from ASTM and HL7 were the E1384 and Hl7V.x standards, respectively. In the paper-based records, data were extracted from 19 forms sporadically. By declaring the confidentiality of information, the ASTM standards acknowledge the issue of confidentiality of information as one of the main challenges of EHR development, and propose new types of admission, such as teleconference, tele-video, and home visit, which are inevitable with the advent of new technology for providing healthcare and treating diseases. Data related to finance and insurance, which were scattered in different categories by three organizations, emerged as the financial category. Documenting the role and responsibility of the provider by adding the authenticator/signature data element was deemed essential. Not only using well-defined and standardized data, but also adapting EHR systems to the local facilities and the existing social and cultural conditions, will facilitate the development of structured data sets.

Clinical information modeling processes for semantic interoperability of electronic health records: systematic review and inductive analysis.

PubMed

Moreno-Conde, Alberto; Moner, David; Cruz, Wellington Dimas da; Santos, Marcelo R; Maldonado, José Alberto; Robles, Montserrat; Kalra, Dipak

2015-07-01

This systematic review aims to identify and compare the existing processes and methodologies that have been published in the literature for defining clinical information models (CIMs) that support the semantic interoperability of electronic health record (EHR) systems. Following the preferred reporting items for systematic reviews and meta-analyses systematic review methodology, the authors reviewed published papers between 2000 and 2013 that covered that semantic interoperability of EHRs, found by searching the PubMed, IEEE Xplore, and ScienceDirect databases. Additionally, after selection of a final group of articles, an inductive content analysis was done to summarize the steps and methodologies followed in order to build CIMs described in those articles. Three hundred and seventy-eight articles were screened and thirty six were selected for full review. The articles selected for full review were analyzed to extract relevant information for the analysis and characterized according to the steps the authors had followed for clinical information modeling. Most of the reviewed papers lack a detailed description of the modeling methodologies used to create CIMs. A representative example is the lack of description related to the definition of terminology bindings and the publication of the generated models. However, this systematic review confirms that most clinical information modeling activities follow very similar steps for the definition of CIMs. Having a robust and shared methodology could improve their correctness, reliability, and quality. Independently of implementation technologies and standards, it is possible to find common patterns in methods for developing CIMs, suggesting the viability of defining a unified good practice methodology to be used by any clinical information modeler. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Defining a Contemporary Ischemic Heart Disease Genetic Risk Profile Using Historical Data.

PubMed

Mosley, Jonathan D; van Driest, Sara L; Wells, Quinn S; Shaffer, Christian M; Edwards, Todd L; Bastarache, Lisa; McCarty, Catherine A; Thompson, Will; Chute, Christopher G; Jarvik, Gail P; Crosslin, David R; Larson, Eric B; Kullo, Iftikhar J; Pacheco, Jennifer A; Peissig, Peggy L; Brilliant, Murray H; Linneman, James G; Denny, Josh C; Roden, Dan M

2016-12-01

Continued reductions in morbidity and mortality attributable to ischemic heart disease (IHD) require an understanding of the changing epidemiology of this disease. We hypothesized that we could use genetic correlations, which quantify the shared genetic architectures of phenotype pairs and extant risk factors from a historical prospective study to define the risk profile of a contemporary IHD phenotype. We used 37 phenotypes measured in the ARIC study (Atherosclerosis Risk in Communities; n=7716, European ancestry subjects) and clinical diagnoses from an electronic health record (EHR) data set (n=19 093). All subjects had genome-wide single-nucleotide polymorphism genotyping. We measured pairwise genetic correlations (rG) between the ARIC and EHR phenotypes using linear mixed models. The genetic correlation estimates between the ARIC risk factors and the EHR IHD were modestly linearly correlated with hazards ratio estimates for incident IHD in ARIC (Pearson correlation [r]=0.62), indicating that the 2 IHD phenotypes had differing risk profiles. For comparison, this correlation was 0.80 when comparing EHR and ARIC type 2 diabetes mellitus phenotypes. The EHR IHD phenotype was most strongly correlated with ARIC metabolic phenotypes, including total:high-density lipoprotein cholesterol ratio (rG=-0.44, P=0.005), high-density lipoprotein (rG=-0.48, P=0.005), systolic blood pressure (rG=0.44, P=0.02), and triglycerides (rG=0.38, P=0.02). EHR phenotypes related to type 2 diabetes mellitus, atherosclerotic, and hypertensive diseases were also genetically correlated with these ARIC risk factors. The EHR IHD risk profile differed from ARIC and indicates that treatment and prevention efforts in this population should target hypertensive and metabolic disease. © 2016 American Heart Association, Inc.

The SAFER guides: empowering organizations to improve the safety and effectiveness of electronic health records.

PubMed

Sittig, Dean F; Ash, Joan S; Singh, Hardeep

2014-05-01

Electronic health records (EHRs) have potential to improve quality and safety of healthcare. However, EHR users have experienced safety concerns from EHR design and usability features that are not optimally adapted for the complex work flow of real-world practice. Few strategies exist to address unintended consequences from implementation of EHRs and other health information technologies. We propose that organizations equipped with EHRs should consider the strategy of "proactive risk assessment" of their EHR-enabled healthcare system to identify and address EHR-related safety concerns. In this paper, we describe the conceptual underpinning of an EHR-related self-assessment strategy to provide institutions a foundation upon which they could build their safety efforts. With support from the Office of the National Coordinator for Health Information Technology (ONC), we used a rigorous, iterative process to develop a set of 9 self-assessment tools to optimize the safety and safe use of EHRs. These tools, referred to as the Safety Assurance Factors for EHR Resilience (SAFER) guides, could be used to self-assess safety and effectiveness of EHR implementations, identify specific areas of vulnerability, and create solutions and culture change to mitigate risks. A variety of audiences could conduct these assessments, including frontline clinicians or care teams in different practices, or clinical, quality, or administrative leaders within larger institutions. The guides use a multifaceted systems-based approach to assess risk and empower organizations to work with internal or external stakeholders (eg, EHR developers) on optimizing EHR functionality and using EHRs to drive improvements in the quality and safety of healthcare.

Simulated electronic health record (Sim-EHR) curriculum: teaching EHR skills and use of the EHR for disease management and prevention.

PubMed

Milano, Christina E; Hardman, Joseph A; Plesiu, Adeline; Rdesinski, Rebecca E; Biagioli, Frances E

2014-03-01

Electronic health records (EHRs) can improve many aspects of patient care, yet few formal EHR curricula exist to teach optimal use to students and other trainees. The Simulated EHR (Sim-EHR) curriculum was introduced in January 2011 at Oregon Health & Science University (OHSU) to provide learners with a safe hands-on environment in which to apply evidence-based guidelines while learning EHR skills. Using an EHR training platform identical to the OHSU EHR system, learners review and correct a simulated medical chart for a complex virtual patient with chronic diseases and years of fragmented care. They write orders and prescriptions, create an evidence-based plan of care for indicated disease prevention and management, and review their work in a small-group setting. Third-year students complete the Sim-EHR curriculum as part of the required family medicine clerkship; their chart work is assessed using a rubric tied to the curriculum's general and specific objectives. As of January 2014, 406 third-year OHSU medical students, on campus or at remote clerkship sites, and 21 OHSU internal medicine interns had completed simulated charts.In this article, the authors describe the development and implementation of the Sim-EHR curriculum, with a focus on use of the curriculum in the family medicine clerkship. They also share preliminary findings and lessons learned. They suggest that the Sim-EHR curriculum is an effective, interactive method for providing learners with EHR skills education while demonstrating how a well-organized chart helps ensure safe, efficient, and quality patient care.

RAVEL: retrieval and visualization in ELectronic health records.

PubMed

Thiessard, Frantz; Mougin, Fleur; Diallo, Gayo; Jouhet, Vianney; Cossin, Sébastien; Garcelon, Nicolas; Campillo, Boris; Jouini, Wassim; Grosjean, Julien; Massari, Philippe; Griffon, Nicolas; Dupuch, Marie; Tayalati, Fayssal; Dugas, Edwige; Balvet, Antonio; Grabar, Natalia; Pereira, Suzanne; Frandji, Bruno; Darmoni, Stefan; Cuggia, Marc

2012-01-01

Because of the ever-increasing amount of information in patients' EHRs, healthcare professionals may face difficulties for making diagnoses and/or therapeutic decisions. Moreover, patients may misunderstand their health status. These medical practitioners need effective tools to locate in real time relevant elements within the patients' EHR and visualize them according to synthetic and intuitive presentation models. The RAVEL project aims at achieving this goal by performing a high profile industrial research and development program on the EHR considering the following areas: (i) semantic indexing, (ii) information retrieval, and (iii) data visualization. The RAVEL project is expected to implement a generic, loosely coupled to data sources prototype so that it can be transposed into different university hospitals information systems.

Characteristics of patient portals developed in the context of health information exchanges: early policy effects of incentives in the meaningful use program in the United States.

PubMed

Otte-Trojel, Terese; de Bont, Antoinette; van de Klundert, Joris; Rundall, Thomas G

2014-11-21

In 2014, the Centers for Medicare & Medicaid Services in the United States launched the second stage of its Electronic Health Record (EHR) Incentive Program, providing financial incentives to providers to meaningfully use their electronic health records to engage patients online. Patient portals are electronic means to engage patients by enabling secure access to personal medical records, communication with providers, various self-management tools, and administrative functionalities. Outcomes of patient portals have mainly been reported in large integrated health systems. This may now change as the EHR Incentive Program enables and supports the use of patient portals in other types of health systems. In this paper, we focus on Health Information Exchanges (HIE): entities that facilitate data exchange within networks of independent providers. In response to the EHR Incentive Program, some Health Information Exchanges in the United States are developing patient portals and offering them to their network of providers. Such patient portals hold high value for patients, especially in fragmented health system contexts, due to the portals' ability to integrate health information from an array of providers and give patients one access point to this information. Our aim was to report on the early effects of the EHR incentives on patient portal development by HIEs. Specifically, we describe the characteristics of these portals, identify factors affecting adoption by providers during the 2013-2014 time frame, and consider what may be the primary drivers of providers' adoption of patient portals in the future. We identified four HIEs that were developing patient portals as of spring 2014. We collected relevant documents and conducted interviews with six HIE leaders as well as two providers that were implementing the portals in their practices. We performed content analysis on these data to extract information pertinent to our study objectives. Our findings suggest that there are two primary types of patient portals available to providers in HIEs: (1) portals linked to EHRs of individual providers or health systems and (2) HIE-sponsored portals that link information from multiple providers' EHRs. The decision of providers in the HIEs to adopt either one of these portals appears to be a trade-off between functionality, connectivity, and cost. Our findings also suggest that while the EHR Incentive Program is influencing these decisions, it may not be enough to drive adoption. Rather, patient demand for access to patient portals will be necessary to achieve widespread portal adoption and realization of potential benefits. Optimizing patient value should be the main principle underlying policies intending to increase online patient engagement in the third stage of the EHR Incentive Program. We propose a number of features for the EHR Incentive Program that will enhance patient value and thereby support the growth and sustainability of patient portals provided by Health Information Exchanges.

Return on Investment in Electronic Health Records in Primary Care Practices: A Mixed-Methods Study

PubMed Central

Sanche, Steven

2014-01-01

Background The use of electronic health records (EHR) in clinical settings is considered pivotal to a patient-centered health care delivery system. However, uncertainty in cost recovery from EHR investments remains a significant concern in primary care practices. Objective Guided by the question of “When implemented in primary care practices, what will be the return on investment (ROI) from an EHR implementation?”, the objectives of this study are two-fold: (1) to assess ROI from EHR in primary care practices and (2) to identify principal factors affecting the realization of positive ROI from EHR. We used a break-even point, that is, the time required to achieve cost recovery from an EHR investment, as an ROI indicator of an EHR investment. Methods Given the complexity exhibited by most EHR implementation projects, this study adopted a retrospective mixed-method research approach, particularly a multiphase study design approach. For this study, data were collected from community-based primary care clinics using EHR systems. Results We collected data from 17 primary care clinics using EHR systems. Our data show that the sampled primary care clinics recovered their EHR investments within an average period of 10 months (95% CI 6.2-17.4 months), seeing more patients with an average increase of 27% in the active-patients-to-clinician-FTE (full time equivalent) ratio and an average increase of 10% in the active-patients-to-clinical-support-staff-FTE ratio after an EHR implementation. Our analysis suggests, with a 95% confidence level, that the increase in the number of active patients (P=.006), the increase in the active-patients-to-clinician-FTE ratio (P<.001), and the increase in the clinic net revenue (P<.001) are positively associated with the EHR implementation, likely contributing substantially to an average break-even point of 10 months. Conclusions We found that primary care clinics can realize a positive ROI with EHR. Our analysis of the variances in the time required to achieve cost recovery from EHR investments suggests that a positive ROI does not appear automatically upon implementing an EHR and that a clinic’s ability to leverage EHR for process changes seems to play a role. Policies that provide support to help primary care practices successfully make EHR-enabled changes, such as support of clinic workflow optimization with an EHR system, could facilitate the realization of positive ROI from EHR in primary care practices. PMID:25600508

A two-phase Poisson process model and its application to analysis of cancer mortality among A-bomb survivors.

PubMed

Ohtaki, Megu; Tonda, Tetsuji; Aihara, Kazuyuki

2015-10-01

We consider a two-phase Poisson process model where only early successive transitions are assumed to be sensitive to exposure. In the case where intensity transitions are low, we derive analytically an approximate formula for the distribution of time to event for the excess hazard ratio (EHR) due to a single point exposure. The formula for EHR is a polynomial in exposure dose. Since the formula for EHR contains no unknown parameters except for the number of total stages, number of exposure-sensitive stages, and a coefficient of exposure effect, it is applicable easily under a variety of situations where there exists a possible latency time from a single point exposure to occurrence of event. Based on the multistage hypothesis of cancer, we formulate a radiation carcinogenesis model in which only some early consecutive stages of the process are sensitive to exposure, whereas later stages are not affected. An illustrative analysis using the proposed model is given for cancer mortality among A-bomb survivors. Copyright © 2015 Elsevier Inc. All rights reserved.

Cloud-based Predictive Modeling System and its Application to Asthma Readmission Prediction

PubMed Central

Chen, Robert; Su, Hang; Khalilia, Mohammed; Lin, Sizhe; Peng, Yue; Davis, Tod; Hirsh, Daniel A; Searles, Elizabeth; Tejedor-Sojo, Javier; Thompson, Michael; Sun, Jimeng

2015-01-01

The predictive modeling process is time consuming and requires clinical researchers to handle complex electronic health record (EHR) data in restricted computational environments. To address this problem, we implemented a cloud-based predictive modeling system via a hybrid setup combining a secure private server with the Amazon Web Services (AWS) Elastic MapReduce platform. EHR data is preprocessed on a private server and the resulting de-identified event sequences are hosted on AWS. Based on user-specified modeling configurations, an on-demand web service launches a cluster of Elastic Compute 2 (EC2) instances on AWS to perform feature selection and classification algorithms in a distributed fashion. Afterwards, the secure private server aggregates results and displays them via interactive visualization. We tested the system on a pediatric asthma readmission task on a de-identified EHR dataset of 2,967 patients. We conduct a larger scale experiment on the CMS Linkable 2008–2010 Medicare Data Entrepreneurs’ Synthetic Public Use File dataset of 2 million patients, which achieves over 25-fold speedup compared to sequential execution. PMID:26958172

Mapping HL7 CDA R2 Formatted Mass Screening Data to OpenEHR Archetypes.

PubMed

Kobayashi, Shinji; Kume, Naoto; Yoshihara, Hiroyuki

2017-01-01

Mass screening of adults was performed to manage employee healthcare. The screening service defined the data collection format as HL7 Clinical Document Architecture (CDA) R2. To capture mass screening data for nationwide electronic health records (her), we programmed a model within the CDA format and mapped the data items to the ISO13606/openEHR archetype for semantic interoperabiilty.

EHR Safety: The Way Forward to Safe and Effective Systems

PubMed Central

Walker, James M.; Carayon, Pascale; Leveson, Nancy; Paulus, Ronald A.; Tooker, John; Chin, Homer; Bothe, Albert; Stewart, Walter F.

2008-01-01

Diverse stakeholders—clinicians, researchers, business leaders, policy makers, and the public—have good reason to believe that the effective use of electronic health care records (EHRs) is essential to meaningful advances in health care quality and patient safety. However, several reports have documented the potential of EHRs to contribute to health care system flaws and patient harm. As organizations (including small hospitals and physician practices) with limited resources for care-process transformation, human-factors engineering, software safety, and project management begin to use EHRs, the chance of EHR-associated harm may increase. The authors propose a coordinated set of steps to advance the practice and theory of safe EHR design, implementation, and continuous improvement. These include setting EHR implementation in the context of health care process improvement, building safety into the specification and design of EHRs, safety testing and reporting, and rapid communication of EHR-related safety flaws and incidents. PMID:18308981

A secure EHR system based on hybrid clouds.

PubMed

Chen, Yu-Yi; Lu, Jun-Chao; Jan, Jinn-Ke

2012-10-01

Consequently, application services rendering remote medical services and electronic health record (EHR) have become a hot topic and stimulating increased interest in studying this subject in recent years. Information and communication technologies have been applied to the medical services and healthcare area for a number of years to resolve problems in medical management. Sharing EHR information can provide professional medical programs with consultancy, evaluation, and tracing services can certainly improve accessibility to the public receiving medical services or medical information at remote sites. With the widespread use of EHR, building a secure EHR sharing environment has attracted a lot of attention in both healthcare industry and academic community. Cloud computing paradigm is one of the popular healthIT infrastructures for facilitating EHR sharing and EHR integration. In this paper, we propose an EHR sharing and integration system in healthcare clouds and analyze the arising security and privacy issues in access and management of EHRs.

Are physicians' perceptions of healthcare quality and practice satisfaction affected by errors associated with electronic health record use?

PubMed Central

Wright, Adam; Simon, Steven R; Jenter, Chelsea A; Soran, Christine S; Volk, Lynn A; Bates, David W; Poon, Eric G

2011-01-01

Background Electronic health record (EHR) adoption is a national priority in the USA, and well-designed EHRs have the potential to improve quality and safety. However, physicians are reluctant to implement EHRs due to financial constraints, usability concerns, and apprehension about unintended consequences, including the introduction of medical errors related to EHR use. The goal of this study was to characterize and describe physicians' attitudes towards three consequences of EHR implementation: (1) the potential for EHRs to introduce new errors; (2) improvements in healthcare quality; and (3) changes in overall physician satisfaction. Methods Using data from a 2007 statewide survey of Massachusetts physicians, we conducted multivariate regression analysis to examine relationships between practice characteristics, perceptions of EHR-related errors, perceptions of healthcare quality, and overall physician satisfaction. Results 30% of physicians agreed that EHRs create new opportunities for error, but only 2% believed their EHR has created more errors than it prevented. With respect to perceptions of quality, there was no significant association between perceptions of EHR-associated errors and perceptions of EHR-associated changes in healthcare quality. Finally, physicians who believed that EHRs created new opportunities for error were less likely be satisfied with their practice situation (adjusted OR 0.49, p=0.001). Conclusions Almost one third of physicians perceived that EHRs create new opportunities for error. This perception was associated with lower levels of physician satisfaction. PMID:22199017

Data extraction from electronic health records (EHRs) for quality measurement of the physical therapy process: comparison between EHR data and survey data.

PubMed

Scholte, Marijn; van Dulmen, Simone A; Neeleman-Van der Steen, Catherina W M; van der Wees, Philip J; Nijhuis-van der Sanden, Maria W G; Braspenning, Jozé

2016-11-08

With the emergence of the electronic health records (EHRs) as a pervasive healthcare information technology, new opportunities and challenges for use of clinical data for quality measurements arise with respect to data quality, data availability and comparability. The objective of this study is to test whether data extracted from electronic health records (EHRs) was of comparable quality as survey data for the calculation of quality indicators. Data from surveys describing patient cases and filled out by physiotherapists in 2009-2010 were used to calculate scores on eight quality indicators (QIs) to measure the quality of physiotherapy care. In 2011, data was extracted directly from EHRs. The data collection methods were evaluated for comparability. EHR data was compared to survey data on completeness and correctness. Five of the eight QIs could be extracted from the EHRs. Three were omitted from the indicator set, as they proved too difficult to be extracted from the EHRs. Another QI proved incomparable due to errors in the extraction software of some of the EHRs. Three out of four comparable QIs performed better (p < 0.001) in EHR data on completeness. EHR data also proved to be correct; the relative change in indicator scores between EHR and survey data were small (<5 %) in three out of four QIs. Data quality of EHRs was sufficient to be used for the calculation of QIs, although comparability to survey data was problematic. Standardization is needed, not only to be able to compare different data collection methods properly, but also to compare between practices with different EHRs. EHRs have the option to administrate narrative data, but natural language processing tools are needed to quantify these text boxes. Such development, can narrow the comparability gap between scoring QIs based on EHR data and based on survey data. EHRs have the potential to provide real time feedback to professionals and quality measurements for research, but more effort is needed to create unambiguous and uniform information and to unlock written text in a standardized manner.

SemEHR: A general-purpose semantic search system to surface semantic data from clinical notes for tailored care, trial recruitment, and clinical research.

PubMed

Wu, Honghan; Toti, Giulia; Morley, Katherine I; Ibrahim, Zina M; Folarin, Amos; Jackson, Richard; Kartoglu, Ismail; Agrawal, Asha; Stringer, Clive; Gale, Darren; Gorrell, Genevieve; Roberts, Angus; Broadbent, Matthew; Stewart, Robert; Dobson, Richard J B

2018-05-01

Unlocking the data contained within both structured and unstructured components of electronic health records (EHRs) has the potential to provide a step change in data available for secondary research use, generation of actionable medical insights, hospital management, and trial recruitment. To achieve this, we implemented SemEHR, an open source semantic search and analytics tool for EHRs. SemEHR implements a generic information extraction (IE) and retrieval infrastructure by identifying contextualized mentions of a wide range of biomedical concepts within EHRs. Natural language processing annotations are further assembled at the patient level and extended with EHR-specific knowledge to generate a timeline for each patient. The semantic data are serviced via ontology-based search and analytics interfaces. SemEHR has been deployed at a number of UK hospitals, including the Clinical Record Interactive Search, an anonymized replica of the EHR of the UK South London and Maudsley National Health Service Foundation Trust, one of Europe's largest providers of mental health services. In 2 Clinical Record Interactive Search-based studies, SemEHR achieved 93% (hepatitis C) and 99% (HIV) F-measure results in identifying true positive patients. At King's College Hospital in London, as part of the CogStack program (github.com/cogstack), SemEHR is being used to recruit patients into the UK Department of Health 100 000 Genomes Project (genomicsengland.co.uk). The validation study suggests that the tool can validate previously recruited cases and is very fast at searching phenotypes; time for recruitment criteria checking was reduced from days to minutes. Validated on open intensive care EHR data, Medical Information Mart for Intensive Care III, the vital signs extracted by SemEHR can achieve around 97% accuracy. Results from the multiple case studies demonstrate SemEHR's efficiency: weeks or months of work can be done within hours or minutes in some cases. SemEHR provides a more comprehensive view of patients, bringing in more and unexpected insight compared to study-oriented bespoke IE systems. SemEHR is open source, available at https://github.com/CogStack/SemEHR.

Open-Source Electronic Health Record Systems for Low-Resource Settings: Systematic Review.

PubMed

Syzdykova, Assel; Malta, André; Zolfo, Maria; Diro, Ermias; Oliveira, José Luis

2017-11-13

Despite the great impact of information and communication technologies on clinical practice and on the quality of health services, this trend has been almost exclusive to developed countries, whereas countries with poor resources suffer from many economic and social issues that have hindered the real benefits of electronic health (eHealth) tools. As a component of eHealth systems, electronic health records (EHRs) play a fundamental role in patient management and effective medical care services. Thus, the adoption of EHRs in regions with a lack of infrastructure, untrained staff, and ill-equipped health care providers is an important task. However, the main barrier to adopting EHR software in low- and middle-income countries is the cost of its purchase and maintenance, which highlights the open-source approach as a good solution for these underserved areas. The aim of this study was to conduct a systematic review of open-source EHR systems based on the requirements and limitations of low-resource settings. First, we reviewed existing literature on the comparison of available open-source solutions. In close collaboration with the University of Gondar Hospital, Ethiopia, we identified common limitations in poor resource environments and also the main requirements that EHRs should support. Then, we extensively evaluated the current open-source EHR solutions, discussing their strengths and weaknesses, and their appropriateness to fulfill a predefined set of features relevant for low-resource settings. The evaluation methodology allowed assessment of several key aspects of available solutions that are as follows: (1) integrated applications, (2) configurable reports, (3) custom reports, (4) custom forms, (5) interoperability, (6) coding systems, (7) authentication methods, (8) patient portal, (9) access control model, (10) cryptographic features, (11) flexible data model, (12) offline support, (13) native client, (14) Web client,(15) other clients, (16) code-based language, (17) development activity, (18) modularity, (19) user interface, (20) community support, and (21) customization. The quality of each feature is discussed for each of the evaluated solutions and a final comparison is presented. There is a clear demand for open-source, reliable, and flexible EHR systems in low-resource settings. In this study, we have evaluated and compared five open-source EHR systems following a multidimensional methodology that can provide informed recommendations to other implementers, developers, and health care professionals. We hope that the results of this comparison can guide decision making when needing to adopt, install, and maintain an open-source EHR solution in low-resource settings. ©Assel Syzdykova, André Malta, Maria Zolfo, Ermias Diro, José Luis Oliveira. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 13.11.2017.

The Promise of Information and Communication Technology in Healthcare: Extracting Value From the Chaos.

PubMed

Mamlin, Burke W; Tierney, William M

2016-01-01

Healthcare is an information business with expanding use of information and communication technologies (ICTs). Current ICT tools are immature, but a brighter future looms. We examine 7 areas of ICT in healthcare: electronic health records (EHRs), health information exchange (HIE), patient portals, telemedicine, social media, mobile devices and wearable sensors and monitors, and privacy and security. In each of these areas, we examine the current status and future promise, highlighting how each might reach its promise. Steps to better EHRs include a universal programming interface, universal patient identifiers, improved documentation and improved data analysis. HIEs require federal subsidies for sustainability and support from EHR vendors, targeting seamless sharing of EHR data. Patient portals must bring patients into the EHR with better design and training, greater provider engagement and leveraging HIEs. Telemedicine needs sustainable payment models, clear rules of engagement, quality measures and monitoring. Social media needs consensus on rules of engagement for providers, better data mining tools and approaches to counter disinformation. Mobile and wearable devices benefit from a universal programming interface, improved infrastructure, more rigorous research and integration with EHRs and HIEs. Laws for privacy and security need updating to match current technologies, and data stewards should share information on breaches and standardize best practices. ICT tools are evolving quickly in healthcare and require a rational and well-funded national agenda for development, use and assessment. Copyright © 2016 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

Open source electronic health records and chronic disease management

PubMed Central

Goldwater, Jason C; Kwon, Nancy J; Nathanson, Ashley; Muckle, Alison E; Brown, Alexa; Cornejo, Kerri

2014-01-01

Objective To study and report on the use of open source electronic health records (EHR) to assist with chronic care management within safety net medical settings, such as community health centers (CHC). Methods and Materials The study was conducted by NORC at the University of Chicago from April to September 2010. The NORC team undertook a comprehensive environmental scan, including a literature review, a dozen key informant interviews using a semistructured protocol, and a series of site visits to CHC that currently use an open source EHR. Results Two of the sites chosen by NORC were actively using an open source EHR to assist in the redesign of their care delivery system to support more effective chronic disease management. This included incorporating the chronic care model into an CHC and using the EHR to help facilitate its elements, such as care teams for patients, in addition to maintaining health records on indigent populations, such as tuberculosis status on homeless patients. Discussion The ability to modify the open-source EHR to adapt to the CHC environment and leverage the ecosystem of providers and users to assist in this process provided significant advantages in chronic care management. Improvements in diabetes management, controlled hypertension and increases in tuberculosis vaccinations were assisted through the use of these open source systems. Conclusions The flexibility and adaptability of open source EHR demonstrated its utility and viability in the provision of necessary and needed chronic disease care among populations served by CHC. PMID:23813566

Learning Optimal Individualized Treatment Rules from Electronic Health Record Data

PubMed Central

Wang, Yuanjia; Wu, Peng; Liu, Ying; Weng, Chunhua; Zeng, Donglin

2016-01-01

Medical research is experiencing a paradigm shift from “one-size-fits-all” strategy to a precision medicine approach where the right therapy, for the right patient, and at the right time, will be prescribed. We propose a statistical method to estimate the optimal individualized treatment rules (ITRs) that are tailored according to subject-specific features using electronic health records (EHR) data. Our approach merges statistical modeling and medical domain knowledge with machine learning algorithms to assist personalized medical decision making using EHR. We transform the estimation of optimal ITR into a classification problem and account for the non-experimental features of the EHR data and confounding by clinical indication. We create a broad range of feature variables that reflect both patient health status and healthcare data collection process. Using EHR data collected at Columbia University clinical data warehouse, we construct a decision tree for choosing the best second line therapy for treating type 2 diabetes patients. PMID:28503676

Health Information Technology, Patient Safety, and Professional Nursing Care Documentation in Acute Care Settings.

PubMed

Lavin, Mary Ann; Harper, Ellen; Barr, Nancy

2015-04-14

The electronic health record (EHR) is a documentation tool that yields data useful in enhancing patient safety, evaluating care quality, maximizing efficiency, and measuring staffing needs. Although nurses applaud the EHR, they also indicate dissatisfaction with its design and cumbersome electronic processes. This article describes the views of nurses shared by members of the Nursing Practice Committee of the Missouri Nurses Association; it encourages nurses to share their EHR concerns with Information Technology (IT) staff and vendors and to take their place at the table when nursing-related IT decisions are made. In this article, we describe the experiential-reflective reasoning and action model used to understand staff nurses' perspectives, share committee reflections and recommendations for improving both documentation and documentation technology, and conclude by encouraging nurses to develop their documentation and informatics skills. Nursing issues include medication safety, documentation and standards of practice, and EHR efficiency. IT concerns include interoperability, vendors, innovation, nursing voice, education, and collaboration.

An Electronic Health Record - Public Health (EHR-PH) System Prototype for Interoperability in 21st Century Healthcare Systems

PubMed Central

Orlova, Anna O.; Dunnagan, Mark; Finitzo, Terese; Higgins, Michael; Watkins, Todd; Tien, Allen; Beales, Steven

2005-01-01

Information exchange, enabled by computable interoperability, is the key to many of the initiatives underway including the development of Regional Health Information Exchanges, Regional Health Information Organizations, and the National Health Information Network. These initiatives must include public health as a full partner in the emerging transformation of our nation’s healthcare system through the adoption and use of information technology. An electronic health record - public health (EHR-PH) system prototype was developed to demonstrate the feasibility of electronic data transfer from a health care provider, i.e. hospital or ambulatory care settings, to multiple customized public health systems which include a Newborn Metabolic Screening Registry, a Newborn Hearing Screening Registry, an Immunization Registry and a Communicable Disease Registry, using HL7 messaging standards. Our EHR-PH system prototype can be considered a distributed EHR-based RHIE/RHIO model - a principal element for a potential technical architecture for a NHIN. PMID:16779105

Consent-based access to core EHR information. Collaborative approaches in Norway.

PubMed

Heimly, Vigdis; Berntsen, Kirsti E

2009-01-01

Lack of access to updated drug information is a challenge for healthcare providers in Norway. Drug charts are updated in separate EHR systems but exchange of drug information between them is lacking. In order to provide ready access to updated medication information, a project for consent-based access to a core EHR has been established. End users have developed requirements for additions to the medication modules in the EHR systems in cooperation with vendors, researchers and standardization workers. The modules are then implemented by the vendors, tested in the usability lab, and finally tested by the national testing and approval service before implementation. An ethnographic study, with focus on future users and their interaction with other actors regarding medicines and medication, has included semi-/unstructured interviews with the involved organizational units. The core EHR uses the EHR kept by the patient's regular GP as the main source of information. A server-based solution has been chosen in order to keep the core EHR accessible outside the GP's regular work hours. The core EHR is being tested, and the EHR-vendors are implementing additions to their systems in order to facilitate communication with the core EHR. All major EHR-system vendors in Norway participate in the project. The core EHR provides a generic basis that may be used as a pilot for a national patient summary. Examples of a wider use of the core EHR can be: shared individual plans to support continuity of care, summary of the patient's contacts with health providers in different organizations, and core EHR information such as important diagnoses, allergies and contact information. Extensive electronic cooperation and communication requires that all partners adjust their documentation practices to fit with other actors' needs. The implementation effects on future work practices will be followed by researchers.

75 FR 62686 - Health Information Technology: Revisions to Initial Set of Standards, Implementation...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-13

... program whereby the National Coordinator would authorize organizations to test and certify Complete EHRs... Certification Bodies (ONC-ATCBs)) to test and certify Complete EHRs and/or EHR Modules to the certification... Coordinator to test and certify Complete EHRs and/or EHR Modules, it will be subject, depending on the scope...

Perioperative nurses' attitudes toward the electronic health record.

PubMed

Yontz, Laura S; Zinn, Jennifer L; Schumacher, Edward J

2015-02-01

The adoption of an electronic health record (EHR) is mandated under current health care legislation reform. The EHR provides data that are patient centered and improves patient safety. There are limited data; however, regarding the attitudes of perioperative nurses toward the use of the EHR. The purpose of this project was to identify perioperative nurses' attitudes toward the use of the EHR. Quantitative descriptive survey was used to determine attitudes toward the electronic health record. Perioperative nurses in a southeastern health system completed an online survey to determine their attitudes toward the EHR in providing patient care. Overall, respondents felt the EHR was beneficial, did not add to the workload, improved documentation, and would not eliminate any nursing jobs. Nursing acceptance and the utilization of the EHR are necessary for the successful integration of an EHR and to support the goal of patient-centered care. Identification of attitudes and potential barriers of perioperative nurses in using the EHR will improve patient safety, communication, reduce costs, and empower those who implement an EHR. Copyright © 2015 American Society of PeriAnesthesia Nurses. Published by Elsevier Inc. All rights reserved.

Respirator Performance against Nanoparticles under Simulated Workplace Activities

PubMed Central

Vo, Evanly; Zhuang, Ziqing; Horvatin, Matthew; Liu, Yuewei; He, Xinjian; Rengasamy, Samy

2017-01-01

Filtering facepiece respirators (FFRs) and elastomeric half-mask respirators (EHRs) are commonly used by workers for protection against potentially hazardous particles, including engineered nanoparticles. The purpose of this study was to evaluate the performance of these types of respirators against 10–400 nm particles using human subjects exposed to NaCl aerosols under simulated workplace activities. Simulated workplace protection factors (SWPFs) were measured for eight combinations of respirator models (2 N95 FFRs, 2 P100 FFRs, 2 N95 EHRs, and 2 P100 EHRs) worn by 25 healthy test subjects (13 females and 12 males) with varying face sizes. Before beginning a SWPF test for a given respirator model, each subject had to pass a quantitative fit test. Each SWPF test was performed using a protocol of six exercises for 3 min each: (i) normal breathing, (ii) deep breathing, (iii) moving head side to side, (iv) moving head up and down, (v) bending at the waist, and (vi) a simulated laboratory-vessel cleaning motion. Two scanning mobility particle sizers were used simultaneously to measure the upstream (outside the respirator) and downstream (inside the respirator) test aerosol; SWPF was then calculated as a ratio of the upstream and downstream particle concentrations. In general, geometric mean SWPF (GM-SWPF) was highest for the P100 EHRs, followed by P100 FFRs, N95 EHRs, and N95 FFRs. This trend holds true for nanoparticles (10–100 nm), larger size particles (100–400 nm), and the ‘all size’ range (10–400 nm). All respirators provided better or similar performance levels for 10–100 nm particles as compared to larger 100–400 nm particles. This study found that class P100 respirators provided higher SWPFs compared to class N95 respirators (P<0.05) for both FFR and EHR types. All respirators provided expected performance (i.e. fifth percentile SWPF > 10) against all particle size ranges tested. PMID:26180261

Facilitating biomedical researchers' interrogation of electronic health record data: Ideas from outside of biomedical informatics.

PubMed

Hruby, Gregory W; Matsoukas, Konstantina; Cimino, James J; Weng, Chunhua

2016-04-01

Electronic health records (EHR) are a vital data resource for research uses, including cohort identification, phenotyping, pharmacovigilance, and public health surveillance. To realize the promise of EHR data for accelerating clinical research, it is imperative to enable efficient and autonomous EHR data interrogation by end users such as biomedical researchers. This paper surveys state-of-art approaches and key methodological considerations to this purpose. We adapted a previously published conceptual framework for interactive information retrieval, which defines three entities: user, channel, and source, by elaborating on channels for query formulation in the context of facilitating end users to interrogate EHR data. We show the current progress in biomedical informatics mainly lies in support for query execution and information modeling, primarily due to emphases on infrastructure development for data integration and data access via self-service query tools, but has neglected user support needed during iteratively query formulation processes, which can be costly and error-prone. In contrast, the information science literature has offered elaborate theories and methods for user modeling and query formulation support. The two bodies of literature are complementary, implying opportunities for cross-disciplinary idea exchange. On this basis, we outline the directions for future informatics research to improve our understanding of user needs and requirements for facilitating autonomous interrogation of EHR data by biomedical researchers. We suggest that cross-disciplinary translational research between biomedical informatics and information science can benefit our research in facilitating efficient data access in life sciences. Copyright © 2016 Elsevier Inc. All rights reserved.

Integrating Structured and Unstructured EHR Data Using an FHIR-based Type System: A Case Study with Medication Data.

PubMed

Hong, Na; Wen, Andrew; Shen, Feichen; Sohn, Sunghwan; Liu, Sijia; Liu, Hongfang; Jiang, Guoqian

2018-01-01

Standards-based modeling of electronic health records (EHR) data holds great significance for data interoperability and large-scale usage. Integration of unstructured data into a standard data model, however, poses unique challenges partially due to heterogeneous type systems used in existing clinical NLP systems. We introduce a scalable and standards-based framework for integrating structured and unstructured EHR data leveraging the HL7 Fast Healthcare Interoperability Resources (FHIR) specification. We implemented a clinical NLP pipeline enhanced with an FHIR-based type system and performed a case study using medication data from Mayo Clinic's EHR. Two UIMA-based NLP tools known as MedXN and MedTime were integrated in the pipeline to extract FHIR MedicationStatement resources and related attributes from unstructured medication lists. We developed a rule-based approach for assigning the NLP output types to the FHIR elements represented in the type system, whereas we investigated the FHIR elements belonging to the source of the structured EMR data. We used the FHIR resource "MedicationStatement" as an example to illustrate our integration framework and methods. For evaluation, we manually annotated FHIR elements in 166 medication statements from 14 clinical notes generated by Mayo Clinic in the course of patient care, and used standard performance measures (precision, recall and f-measure). The F-scores achieved ranged from 0.73 to 0.99 for the various FHIR element representations. The results demonstrated that our framework based on the FHIR type system is feasible for normalizing and integrating both structured and unstructured EHR data.

Technological trends in health care: electronic health record.

PubMed

Abraham, Sam

2010-01-01

The most relevant technological trend affecting health care organizations and physician services is the electronic health record (EHR). Billions of dollars from the federal government stimulus bill are available for investment toward EHR. Based on the government directives, it is evident EHR has to be a high-priority technological intervention in health care organizations. Addressed in the following pages are the effects of the EHR trend on financial and human resources; analysis of advantages and disadvantages of EHR; action steps involved in implementing EHR, and a timeline for implementation. Medical facilities that do not meet the timetable for using EHR will likely experience reduction of Medicare payments. This article also identifies the strengths, weaknesses, opportunities, and threats of the EHR and steps to be taken by hospitals and physician medical groups to receive stimulus payment.

Modest Associations Between Electronic Health Record Use and Acute Myocardial Infarction Quality of Care and Outcomes: Results From the National Cardiovascular Data Registry.

PubMed

Enriquez, Jonathan R; de Lemos, James A; Parikh, Shailja V; Simon, DaJuanicia N; Thomas, Laine E; Wang, Tracy Y; Chan, Paul S; Spertus, John A; Das, Sandeep R

2015-11-01

In 2009, national legislation promoted wide-spread adoption of electronic health records (EHRs) across US hospitals; however, the association of EHR use with quality of care and outcomes after acute myocardial infarction (AMI) remains unclear. Data on EHR use were collected from the American Hospital Association Annual Surveys (2007-2010) and data on AMI care and outcomes from the National Cardiovascular Data Registry Acute Coronary Treatment and Interventions Outcomes Network Registry-Get With The Guidelines. Comparisons were made between patients treated at hospitals with fully implemented EHR (n=43 527), partially implemented EHR (n=72 029), and no EHR (n=9270). Overall EHR use increased from 82.1% (183/223) hospitals in 2007 to 99.3% (275/277) hospitals in 2010. Patients treated at hospitals with fully implemented EHRs had fewer heparin overdosing errors (45.7% versus 72.8%; P<0.01) and a higher likelihood of guideline-recommended care (adjusted odds ratio, 1.40 [confidence interval, 1.07-1.84]) compared with patients treated at hospitals with no EHR. In non-ST-segment-elevation AMI, fully implemented EHR use was associated with lower risk of major bleeding (adjusted odds ratio, 0.78 [confidence interval, 0.67-0.91]) and mortality (adjusted odds ratio, 0.82 [confidence interval, 0.69-0.97]) compared with no EHR. In ST-segment-elevation MI, outcomes did not significantly differ by EHR status. EHR use has risen to high levels among hospitals in the National Cardiovascular Data Registry. EHR use was associated with less frequent heparin overdosing and modestly greater adherence to acute MI guideline-recommended therapies. In non-ST-segment-elevation MI, slightly lower adjusted risk of major bleeding and mortality were seen in hospitals implemented with full EHRs; however, in ST-segment-elevation MI, differences in outcomes were not seen. © 2015 American Heart Association, Inc.

Design of an extensive information representation scheme for clinical narratives.

PubMed

Deléger, Louise; Campillos, Leonardo; Ligozat, Anne-Laure; Névéol, Aurélie

2017-09-11

Knowledge representation frameworks are essential to the understanding of complex biomedical processes, and to the analysis of biomedical texts that describe them. Combined with natural language processing (NLP), they have the potential to contribute to retrospective studies by unlocking important phenotyping information contained in the narrative content of electronic health records (EHRs). This work aims to develop an extensive information representation scheme for clinical information contained in EHR narratives, and to support secondary use of EHR narrative data to answer clinical questions. We review recent work that proposed information representation schemes and applied them to the analysis of clinical narratives. We then propose a unifying scheme that supports the extraction of information to address a large variety of clinical questions. We devised a new information representation scheme for clinical narratives that comprises 13 entities, 11 attributes and 37 relations. The associated annotation guidelines can be used to consistently apply the scheme to clinical narratives and are https://cabernet.limsi.fr/annotation_guide_for_the_merlot_french_clinical_corpus-Sept2016.pdf . The information scheme includes many elements of the major schemes described in the clinical natural language processing literature, as well as a uniquely detailed set of relations.

Making electronic health records support quality management: A narrative review.

PubMed

Triantafillou, Peter

2017-08-01

Since the 1990s many hospitals in the OECD countries have introduced electronic health record (EHR) systems. A number of studies have examined the factors impinging on EHR implementation. Others have studied the clinical efficacy of EHR. However, only few studies have explored the (intermediary) factors that make EHR systems conducive to quality management (QM). Undertake a narrative review of existing studies in order to identify and discuss the factors conducive to making EHR support three dimensions of QM: clinical outcomes, managerial monitoring and cost-effectiveness. A narrative review of Web of Science, Cochrane, EBSCO, ProQuest, Scopus and three Nordic research databases. most studies do not specify the type of EHR examined. 39 studies were identified for analysis. 10 factors were found to be conducive to make EHR support QM. However, the contribution of EHR to the three specific dimensions of QM varied substantially. Most studies (29) included clinical outcomes. However, only half of these reported EHR to have a positive impact. Almost all the studies (36) dealt with the ability of EHR to enhance managerial monitoring of clinical activities, the far majority of which showed a positive relationship. Finally, only five dealt with cost-effectiveness of which two found positive effects. The findings resonates well with previous reviews, though two factors making EHR support QM seem new, namely: political goals and strategies, and integration of guidelines for clinical conduct. Lacking EHR type specification and diversity in study method imply that there is a strong need for further research on the factors that may make EHR may support QM. Copyright © 2017 Elsevier B.V. All rights reserved.

A Novel Approach to Supporting Relationship-Centered Care Through Electronic Health Record Ergonomic Training in Preclerkship Medical Education

PubMed Central

Silverman, Howard; Ho, Yun-Xian; Kaib, Susan; Ellis, Wendy Danto; Moffitt, Marícela P.; Chen, Qingxia; Nian, Hui; Gadd, Cynthia S.

2014-01-01

Problem How can physicians incorporate the electronic health record (EHR) into clinical practice in a relationship-enhancing fashion (“EHR ergonomics”)? Approach Three convenience samples of 40 second-year medical students with varying levels of EHR ergonomic training were compared in the 2012 spring semester. All participants first received basic EHR training and completed a pre-survey. Two study groups were then instructed to use the EHR during the standardized patient (SP) encounter in each of four regularly scheduled Doctoring (clinical skills) course sessions. One group received additional ergonomic training in each session. Ergonomic assessment data were collected from students, faculty, and SPs in each session. A post-survey was administered to all students, and data were compared across all three groups to assess the impact of EHR use and ergonomic training. Outcomes There was a significant positive effect of EHR ergonomics skills training on students’ relationship-centered EHR use (P < .005). Students who received training reported that they were able to use the EHR to engage with patients more effectively, better articulate the benefits of using the EHR, better address patient concerns, more appropriately position the EHR device, and more effectively integrate the EHR into patient encounters. Additionally, students’ self-assessments were strongly corroborated by SP and faculty assessments. A minimum of three ergonomic training sessions was needed to see an overall improvement in EHR use. Next Steps In addition to replication of these results, further effectiveness studies of this educational intervention need to be carried out in GME, practice, and other environments. PMID:24826851

A novel approach to supporting relationship-centered care through electronic health record ergonomic training in preclerkship medical education.

PubMed

Silverman, Howard; Ho, Yun-Xian; Kaib, Susan; Ellis, Wendy Danto; Moffitt, Marícela P; Chen, Qingxia; Nian, Hui; Gadd, Cynthia S

2014-09-01

How can physicians incorporate the electronic health record (EHR) into clinical practice in a relationship-enhancing fashion ("EHR ergonomics")? Three convenience samples of 40 second-year medical students with varying levels of EHR ergonomic training were compared in the 2012 spring semester. All participants first received basic EHR training and completed a presurvey. Two study groups were then instructed to use the EHR during the standardized patient (SP) encounter in each of four regularly scheduled Doctoring (clinical skills) course sessions. One group received additional ergonomic training in each session. Ergonomic assessment data were collected from students, faculty, and SPs in each session. A postsurvey was administered to all students, and data were compared across all three groups to assess the impact of EHR use and ergonomic training. There was a significant positive effect of EHR ergonomics skills training on students' relationship-centered EHR use (P<.005). Students who received training reported that they were able to use the EHR to engage with patients more effectively, better articulate the benefits of using the EHR, better address patient concerns, more appropriately position the EHR device, and more effectively integrate the EHR into patient encounters. Additionally, students' self-assessments were strongly corroborated by SP and faculty assessments. A minimum of three ergonomic training sessions were needed to see an overall improvement in EHR use. In addition to replication of these results, further effectiveness studies of this educational intervention need to be carried out in GME, practice, and other environments.

Finding Meaning in Medication Reconciliation Using Electronic Health Records: Qualitative Analysis in Safety Net Primary and Specialty Care

PubMed Central

Matta, George Yaccoub; Khoong, Elaine C; Lyles, Courtney R; Schillinger, Dean

2018-01-01

Background Safety net health systems face barriers to effective ambulatory medication reconciliation for vulnerable populations. Although some electronic health record (EHR) systems offer safety advantages, EHR use may affect the quality of patient-provider communication. Objective This mixed-methods observational study aimed to develop a conceptual framework of how clinicians balance the demands and risks of EHR and communication tasks during medication reconciliation discussions in a safety net system. Methods This study occurred 3 to 16 (median 9) months after new EHR implementation in five academic public hospital clinics. We video recorded visits between English-/Spanish-speaking patients and their primary/specialty care clinicians. We analyzed the proportion of medications addressed and coded time spent on nonverbal tasks during medication reconciliation as “multitasking EHR use,” “silent EHR use,” “non-EHR multitasking,” and “focused patient-clinician talk.” Finally, we analyzed communication patterns to develop a conceptual framework. Results We examined 35 visits (17%, 6/35 Spanish) between 25 patients (mean age 57, SD 11 years; 44%, 11/25 women; 48%, 12/25 Hispanic; and 20%, 5/25 with limited health literacy) and 25 clinicians (48%, 12/25 primary care). Patients had listed a median of 7 (IQR 5-12) relevant medications, and clinicians addressed a median of 3 (interquartile range [IQR] 1-5) medications. The median duration of medication reconciliation was 2.1 (IQR 1.0-4.2) minutes, comprising a median of 10% (IQR 3%-17%) of visit time. Multitasking EHR use occurred in 47% (IQR 26%-70%) of the medication reconciliation time. Silent EHR use and non-EHR multitasking occurred a smaller proportion of medication reconciliation time, with a median of 0% for both. Focused clinician-patient talk occurred a median of 24% (IQR 0-39%) of medication reconciliation time. Five communication patterns with EHR medication reconciliation were observed: (1) typical EHR multitasking for medication reconciliation, (2) dynamic EHR use to negotiate medication discrepancies, (3) focused patient-clinician talk for medication counseling and addressing patient concerns, (4) responding to patient concerns while maintaining EHR use, and (5) using EHRs to engage patients during medication reconciliation. We developed a conceptual diagram representing the dilemma of the multitasking clinician during medication reconciliation. Conclusions Safety net visits involve multitasking EHR use during almost half of medication reconciliation time. The multitasking clinician balances the cognitive and emotional demands posed by incoming information from multiple sources, attempts to synthesize and act on this information through EHR and communication tasks, and adopts strategies of silent EHR use and focused patient-clinician talk that may help mitigate the risks of multitasking. Future studies should explore diverse patient perspectives about clinician EHR multitasking, clinical outcomes related to EHR multitasking, and human factors and systems engineering interventions to improve the safety of EHR use during the complex process of medication reconciliation. PMID:29735477

Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.

PubMed

Soguero-Ruiz, Cristina; Hindberg, Kristian; Rojo-Alvarez, Jose Luis; Skrovseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert

2016-09-01

The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, little effort has been invested toward feature selection and the features' corresponding medical interpretation. In this study, we focus on the task of early detection of anastomosis leakage (AL), a severe complication after elective surgery for colorectal cancer (CRC) surgery, using free text extracted from EHRs. We use a bag-of-words model to investigate the potential for feature selection strategies. The purpose is earlier detection of AL and prediction of AL with data generated in the EHR before the actual complication occur. Due to the high dimensionality of the data, we derive feature selection strategies using the robust support vector machine linear maximum margin classifier, by investigating: 1) a simple statistical criterion (leave-one-out-based test); 2) an intensive-computation statistical criterion (Bootstrap resampling); and 3) an advanced statistical criterion (kernel entropy). Results reveal a discriminatory power for early detection of complications after CRC (sensitivity 100%; specificity 72%). These results can be used to develop prediction models, based on EHR data, that can support surgeons and patients in the preoperative decision making phase.

Advanced Proficiency EHR Training: Effect on Physicians’ EHR Efficiency, EHR Satisfaction and Job Satisfaction

PubMed Central

Dastagir, M. Tariq; Chin, Homer L.; McNamara, Michael; Poteraj, Kathy; Battaglini, Sarah; Alstot, Lauren

2012-01-01

The best way to train clinicians to optimize their use of the Electronic Health Record (EHR) remains unclear. Approaches range from web-based training, class-room training, EHR functionality training, case-based training, role-based training, process-based training, mock-clinic training and “on the job” training. Similarly, the optimal timing of training remains unclear--whether to engage in extensive pre go-live training vs. minimal pre go-live training followed by more extensive post go-live training. In addition, the effectiveness of non-clinician trainers, clinician trainers, and peer-trainers, remains unclearly defined. This paper describes a program in which relatively experienced clinician users of an EHR underwent an intensive 3-day Peer-Led EHR advanced proficiency training, and the results of that training based on participant surveys. It highlights the effectiveness of Peer-Led Proficiency Training of existing experienced clinician EHR users in improving self-reported efficiency and satisfaction with an EHR and improvements in perceived work-life balance and job satisfaction. PMID:23304282

Advanced proficiency EHR training: effect on physicians' EHR efficiency, EHR satisfaction and job satisfaction.

PubMed

Dastagir, M Tariq; Chin, Homer L; McNamara, Michael; Poteraj, Kathy; Battaglini, Sarah; Alstot, Lauren

2012-01-01

The best way to train clinicians to optimize their use of the Electronic Health Record (EHR) remains unclear. Approaches range from web-based training, class-room training, EHR functionality training, case-based training, role-based training, process-based training, mock-clinic training and "on the job" training. Similarly, the optimal timing of training remains unclear--whether to engage in extensive pre go-live training vs. minimal pre go-live training followed by more extensive post go-live training. In addition, the effectiveness of non-clinician trainers, clinician trainers, and peer-trainers, remains unclearly defined. This paper describes a program in which relatively experienced clinician users of an EHR underwent an intensive 3-day Peer-Led EHR advanced proficiency training, and the results of that training based on participant surveys. It highlights the effectiveness of Peer-Led Proficiency Training of existing experienced clinician EHR users in improving self-reported efficiency and satisfaction with an EHR and improvements in perceived work-life balance and job satisfaction.

The Impact of Electronic Knowledge-Based Nursing Content and Decision-Support on Nursing-Sensitive Patient Outcomes

DTIC Science & Technology

2014-02-01

aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information...if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE February 2014 2... Akre , et al., 2006) content and evidence-based clinical decision support (CDS) tools were embedded into the EHR of one large health care system. Since

Developing an electronic health record (EHR) for methadone treatment recording and decision support

PubMed Central

2011-01-01

Background In this paper, we give an overview of methadone treatment in Ireland and outline the rationale for designing an electronic health record (EHR) with extensibility, interoperability and decision support functionality. Incorporating several international standards, a conceptual model applying a problem orientated approach in a hierarchical structure has been proposed for building the EHR. Methods A set of archetypes has been designed in line with the current best practice and clinical guidelines which guide the information-gathering process. A web-based data entry system has been implemented, incorporating elements of the paper-based prescription form, while at the same time facilitating the decision support function. Results The use of archetypes was found to capture the ever changing requirements in the healthcare domain and externalises them in constrained data structures. The solution is extensible enabling the EHR to cover medicine management in general as per the programme of the HRB Centre for Primary Care Research. Conclusions The data collected via this Irish system can be aggregated into a larger dataset, if necessary, for analysis and evidence-gathering, since we adopted the openEHR standard. It will be later extended to include the functionalities of prescribing drugs other than methadone along with the research agenda at the HRB Centre for Primary Care Research in Ireland. PMID:21284849

Seniors' views on the use of electronic health records.

PubMed

Morin, Diane; Tourigny, Andre; Pelletier, Daniel; Robichaud, Line; Mathieu, Luc; Vézina, Aline; Bonin, Lucie; Buteau, Martin

2005-01-01

In the Mauricie and Centre-du-Québec region of the province of Quebec, Canada, an integrated services network has been implemented for frail seniors. It combines three of the best practices in the field of integrated services, namely: single-entry point, case management and personalized care plan. A shared interdisciplinary electronic health record (EHR) system was set up in 1998. A consensus on the relevance of using EHRs is growing in Quebec, in Canada and around the world. However, technology has out-paced interest in the notions of confidentiality, informed consent and the impact perceived by the clientele. This study specifically examines how frail seniors perceive these issues related to an EHR. The conceptual framework is inspired by the DeLone and McLean model whose main attributes are: system quality, information quality, utilisation modes and the impact on organisations and individuals. This last attribute is the focus of this study, which is a descriptive with quantitative and qualitative component. Thirty seniors were surveyed. Positive information they provided falls under three headings: (i) being better informed; (ii) trust and consideration for professionals; and (iii) appreciation of innovation. The opinions of the seniors are generally favourable regarding the use of computers and the EHR in their presence. Improvements in EHR systems for seniors can be encouraged.

Workflow and Electronic Health Records in Small Medical Practices

PubMed Central

Ramaiah, Mala; Subrahmanian, Eswaran; Sriram, Ram D; Lide, Bettijoyce B

2012-01-01

This paper analyzes the workflow and implementation of electronic health record (EHR) systems across different functions in small physician offices. We characterize the differences in the offices based on the levels of computerization in terms of workflow, sources of time delay, and barriers to using EHR systems to support the entire workflow. The study was based on a combination of questionnaires, interviews, in situ observations, and data collection efforts. This study was not intended to be a full-scale time-and-motion study with precise measurements but was intended to provide an overview of the potential sources of delays while performing office tasks. The study follows an interpretive model of case studies rather than a large-sample statistical survey of practices. To identify time-consuming tasks, workflow maps were created based on the aggregated data from the offices. The results from the study show that specialty physicians are more favorable toward adopting EHR systems than primary care physicians are. The barriers to adoption of EHR systems by primary care physicians can be attributed to the complex workflows that exist in primary care physician offices, leading to nonstandardized workflow structures and practices. Also, primary care physicians would benefit more from EHR systems if the systems could interact with external entities. PMID:22737096

Postmarketing Safety Study Tool: A Web Based, Dynamic, and Interoperable System for Postmarketing Drug Surveillance Studies

PubMed Central

Sinaci, A. Anil; Laleci Erturkmen, Gokce B.; Gonul, Suat; Yuksel, Mustafa; Invernizzi, Paolo; Thakrar, Bharat; Pacaci, Anil; Cinar, H. Alper; Cicekli, Nihan Kesim

2015-01-01

Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases. PMID:26543873

Incorporating personalized gene sequence variants, molecular genetics knowledge, and health knowledge into an EHR prototype based on the Continuity of Care Record standard.

PubMed

Jing, Xia; Kay, Stephen; Marley, Thomas; Hardiker, Nicholas R; Cimino, James J

2012-02-01

The current volume and complexity of genetic tests, and the molecular genetics knowledge and health knowledge related to interpretation of the results of those tests, are rapidly outstripping the ability of individual clinicians to recall, understand and convey to their patients information relevant to their care. The tailoring of molecular genetics knowledge and health knowledge in clinical settings is important both for the provision of personalized medicine and to reduce clinician information overload. In this paper we describe the incorporation, customization and demonstration of molecular genetic data (mainly sequence variants), molecular genetics knowledge and health knowledge into a standards-based electronic health record (EHR) prototype developed specifically for this study. We extended the CCR (Continuity of Care Record), an existing EHR standard for representing clinical data, to include molecular genetic data. An EHR prototype was built based on the extended CCR and designed to display relevant molecular genetics knowledge and health knowledge from an existing knowledge base for cystic fibrosis (OntoKBCF). We reconstructed test records from published case reports and represented them in the CCR schema. We then used the EHR to dynamically filter molecular genetics knowledge and health knowledge from OntoKBCF using molecular genetic data and clinical data from the test cases. The molecular genetic data were successfully incorporated in the CCR by creating a category of laboratory results called "Molecular Genetics" and specifying a particular class of test ("Gene Mutation Test") in this category. Unlike other laboratory tests reported in the CCR, results of tests in this class required additional attributes ("Molecular Structure" and "Molecular Position") to support interpretation by clinicians. These results, along with clinical data (age, sex, ethnicity, diagnostic procedures, and therapies) were used by the EHR to filter and present molecular genetics knowledge and health knowledge from OntoKBCF. This research shows a feasible model for delivering patient sequence variants and presenting tailored molecular genetics knowledge and health knowledge via a standards-based EHR system prototype. EHR standards can be extended to include the necessary patient data (as we have demonstrated in the case of the CCR), while knowledge can be obtained from external knowledge bases that are created and maintained independently from the EHR. This approach can form the basis for a personalized medicine framework, a more comprehensive standards-based EHR system and a potential platform for advancing translational research by both disseminating results and providing opportunities for new insights into phenotype-genotype relationships. Copyright © 2011 Elsevier Inc. All rights reserved.

Multidisciplinary Modelling of Symptoms and Signs with Archetypes and SNOMED-CT for Clinical Decision Support.

PubMed

Marco-Ruiz, Luis; Maldonado, J Alberto; Karlsen, Randi; Bellika, Johan G

2015-01-01

Clinical Decision Support Systems (CDSS) help to improve health care and reduce costs. However, the lack of knowledge management and modelling hampers their maintenance and reuse. Current EHR standards and terminologies can allow the semantic representation of the data and knowledge of CDSS systems boosting their interoperability, reuse and maintenance. This paper presents the modelling process of respiratory conditions' symptoms and signs by a multidisciplinary team of clinicians and information architects with the help of openEHR, SNOMED and clinical information modelling tools for a CDSS. The information model of the CDSS was defined by means of an archetype and the knowledge model was implemented by means of an SNOMED-CT based ontology.

Workarounds and Test Results Follow-up in Electronic Health Record-Based Primary Care.

PubMed

Menon, Shailaja; Murphy, Daniel R; Singh, Hardeep; Meyer, Ashley N D; Sittig, Dean F

2016-01-01

Electronic health records (EHRs) have potential to facilitate reliable communication and follow-up of test results. However, limitations in EHR functionality remain, leading practitioners to use workarounds while managing test results. Workarounds can lead to patient safety concerns and signify indications as to how to build better EHR systems that meet provider needs. To understand why primary care practitioners (PCPs) use workarounds to manage test results by analyzing data from a previously conducted national cross-sectional survey on test result management. We conducted a secondary data analysis of quantitative and qualitative data from a national survey of PCPs practicing in the Department of Veterans Affairs (VA) and explored the use of workarounds in test results management. We used multivariate logistic regression analysis to examine the association between key sociotechnical factors that could affect test results follow-up (e.g., both technology-related and those unrelated to technology, such as organizational support for patient notification) and workaround use. We conducted a qualitative content analysis of free text survey data to examine reasons for use of workarounds. Of 2554 survey respondents, 1104 (43%) reported using workarounds related to test results management. Of these 1028 (93%) described the type of workaround they were using; 719 (70%) reported paper-based methods, while 230 (22%) used a combination of paper- and computer-based workarounds. Primary care practitioners who self-reported limited administrative support to help them notify patients of test results or described an instance where they personally (or a colleague) missed results, were more likely to use workarounds (p=0.02 and p=0.001, respectively). Qualitative analysis identified three main reasons for workaround use: 1) as a memory aid, 2) for improved efficiency and 3) for facilitating internal and external care coordination. Workarounds to manage EHR-based test results are common, and their use results from unmet provider information management needs. Future EHRs and the respective work systems around them need to evolve to meet these needs.

Computer use in primary care practices in Canada

PubMed Central

Anisimowicz, Yvonne; Bowes, Andrea E.; Thompson, Ashley E.; Miedema, Baukje; Hogg, William E.; Wong, Sabrina T.; Katz, Alan; Burge, Fred; Aubrey-Bassler, Kris; Yelland, Gregory S.; Wodchis, Walter P.

2017-01-01

Abstract Objective To examine the use of computers in primary care practices. Design The international Quality and Cost of Primary Care study was conducted in Canada in 2013 and 2014 using a descriptive cross-sectional survey method to collect data from practices across Canada. Participating practices filled out several surveys, one of them being the Family Physician Survey, from which this study collected its data. Setting All 10 Canadian provinces. Participants A total of 788 family physicians. Main outcome measures A computer use scale measured the extent to which family physicians integrated computers into their practices, with higher scores indicating a greater integration of computer use in practice. Analyses included t tests and 2 tests comparing new and traditional models of primary care on measures of computer use and electronic health record (EHR) use, as well as descriptive statistics. Results Nearly all (97.5%) physicians reported using a computer in their practices, with moderately high computer use scale scores (mean [SD] score of 5.97 [2.96] out of 9), and many (65.7%) reported using EHRs. Physicians with practices operating under new models of primary care reported incorporating computers into their practices to a greater extent (mean [SD] score of 6.55 [2.64]) than physicians operating under traditional models did (mean [SD] score of 5.33 [3.15]; t726.60 = 5.84; P < .001; Cohen d = 0.42, 95% CI 0.808 to 1.627) and were more likely to report using EHRs (73.8% vs 56.7%; χ12=25.43; P < .001; odds ratio = 2.15). Overall, there was a statistically significant variability in computer use across provinces. Conclusion Most family physicians in Canada have incorporated computers into their practices for administrative and scholarly activities; however, EHRs have not been adopted consistently across the country. Physicians with practices operating under the new, more collaborative models of primary care use computers more comprehensively and are more likely to use EHRs than those in practices operating under traditional models of primary care. PMID:28500211

“Meaningful use” of electronic health records and its relevance to laboratories and pathologists

PubMed Central

Henricks, Walter H.

2011-01-01

Electronic health records (EHRs) have emerged as a major topic in health care and are central to the federal government’s strategy for transforming healthcare delivery in the United States. Recent federal actions that aim to promote the use of EHRs promise to have significant implications for laboratories and for pathology practices. Under the HITECH (Health Information Technology Economic and Clinical Health) Act, an EHR incentive program has been established through which individual physicians and hospitals can qualify to receive incentive payments if they achieve “meaningful use” of “certified” EHR technology. The rule also establishes payment penalties in future years for eligible providers who have not met the requirements for meaningful use of EHRs. Meaningful use must be achieved using EHR technology that has been certified in accordance with functional and technical criteria that are set forth a regulation that parallels the meaningful use criteria in the incentive program. These actions and regulations are important to laboratories and pathologists for a number of reasons. Several of the criteria and requirements in the meaningful use rules and EHR certification criteria relate directly or indirectly to laboratory testing and laboratory information management, and future stage requirements are expected to impact the laboratory as well. Furthermore, as EHR uptake expands, there will be greater expectations for electronic interchange of laboratory information and laboratory information system (LIS)-EHR interfaces. Laboratories will need to be aware of the technical, operational, and business challenges that they may face as expectations for LIS-EHR increase. This paper reviews the important recent federal efforts aimed at accelerating EHR use, including the incentive program for EHR meaningful use, provider eligibility, and EHR certification criteria, from a perspective of their relevance for laboratories and pathology practices. PMID:21383931

A review of security of electronic health records.

PubMed

Win, Khin Than

The objective of this study is to answer the research question, "Are current information security technologies adequate for electronic health records (EHRs)?" In order to achieve this, the following matters have been addressed in this article: (i) What is information security in the context of EHRs? (ii) Why is information security important for EHRs? and (iii) What are the current technologies for information security available to EHRs? It is concluded that current EHR security technologies are inadequate and urgently require improvement. Further study regarding information security of EHRs is indicated.

Top ten challenges when interfacing a laboratory information system to an electronic health record: Experience at a large academic medical center.

PubMed

Petrides, Athena K; Tanasijevic, Milenko J; Goonan, Ellen M; Landman, Adam B; Kantartjis, Michalis; Bates, David W; Melanson, Stacy E F

2017-10-01

Recent U.S. government regulations incentivize implementation of an electronic health record (EHR) with computerized order entry and structured results display. Many institutions have also chosen to interface their EHR to their laboratory information system (LIS). Reported long-term benefits include increased efficiency and improved quality and safety. In order to successfully implement an interfaced EHR-LIS, institutions must plan years in advance and anticipate the impact of an integrated system. It can be challenging to fully understand the technical, workflow and resource aspects and adequately prepare for a potentially protracted system implementation and the subsequent stabilization. We describe the top ten challenges that we encountered in our clinical laboratories following the implementation of an interfaced EHR-LIS and offer suggestions on how to overcome these challenges. This study was performed at a 777-bed, tertiary care center which recently implemented an interfaced EHR-LIS. Challenges were recorded during EHR-LIS implementation and stabilization and the authors describe the top ten. Our top ten challenges were selection and harmonization of test codes, detailed training for providers on test ordering, communication with EHR provider champions during the build process, fluid orders and collections, supporting specialized workflows, sufficient reports and metrics, increased volume of inpatient venipunctures, adequate resources during stabilization, unanticipated changes to laboratory workflow and ordering specimens for anatomic pathology. A few suggestions to overcome these challenges include regular meetings with clinical champions, advanced considerations of reports and metrics that will be needed, adequate training of laboratory staff on new workflows in the EHR and defining all tests including anatomic pathology in the LIS. EHR-LIS implementations have many challenges requiring institutions to adapt and develop new infrastructures. This article should be helpful to other institutions facing or undergoing a similar endeavor. Copyright © 2017 Elsevier B.V. All rights reserved.

Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations

PubMed Central

Arndt, Brian G.; Beasley, John W.; Watkinson, Michelle D.; Temte, Jonathan L.; Tuan, Wen-Jan; Sinsky, Christine A.; Gilchrist, Valerie J.

2017-01-01

PURPOSE Primary care physicians spend nearly 2 hours on electronic health record (EHR) tasks per hour of direct patient care. Demand for non–face-to-face care, such as communication through a patient portal and administrative tasks, is increasing and contributing to burnout. The goal of this study was to assess time allocated by primary care physicians within the EHR as indicated by EHR user-event log data, both during clinic hours (defined as 8:00 am to 6:00 pm Monday through Friday) and outside clinic hours. METHODS We conducted a retrospective cohort study of 142 family medicine physicians in a single system in southern Wisconsin. All Epic (Epic Systems Corporation) EHR interactions were captured from “event logging” records over a 3-year period for both direct patient care and non–face-to-face activities, and were validated by direct observation. EHR events were assigned to 1 of 15 EHR task categories and allocated to either during or after clinic hours. RESULTS Clinicians spent 355 minutes (5.9 hours) of an 11.4-hour workday in the EHR per weekday per 1.0 clinical full-time equivalent: 269 minutes (4.5 hours) during clinic hours and 86 minutes (1.4 hours) after clinic hours. Clerical and administrative tasks including documentation, order entry, billing and coding, and system security accounted for nearly one-half of the total EHR time (157 minutes, 44.2%). Inbox management accounted for another 85 minutes (23.7%). CONCLUSIONS Primary care physicians spend more than one-half of their workday, nearly 6 hours, interacting with the EHR during and after clinic hours. EHR event logs can identify areas of EHR-related work that could be delegated, thus reducing workload, improving professional satisfaction, and decreasing burnout. Direct time-motion observations validated EHR-event log data as a reliable source of information regarding clinician time allocation. PMID:28893811

Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations.

PubMed

Arndt, Brian G; Beasley, John W; Watkinson, Michelle D; Temte, Jonathan L; Tuan, Wen-Jan; Sinsky, Christine A; Gilchrist, Valerie J

2017-09-01

Primary care physicians spend nearly 2 hours on electronic health record (EHR) tasks per hour of direct patient care. Demand for non-face-to-face care, such as communication through a patient portal and administrative tasks, is increasing and contributing to burnout. The goal of this study was to assess time allocated by primary care physicians within the EHR as indicated by EHR user-event log data, both during clinic hours (defined as 8:00 am to 6:00 pm Monday through Friday) and outside clinic hours. We conducted a retrospective cohort study of 142 family medicine physicians in a single system in southern Wisconsin. All Epic (Epic Systems Corporation) EHR interactions were captured from "event logging" records over a 3-year period for both direct patient care and non-face-to-face activities, and were validated by direct observation. EHR events were assigned to 1 of 15 EHR task categories and allocated to either during or after clinic hours. Clinicians spent 355 minutes (5.9 hours) of an 11.4-hour workday in the EHR per weekday per 1.0 clinical full-time equivalent: 269 minutes (4.5 hours) during clinic hours and 86 minutes (1.4 hours) after clinic hours. Clerical and administrative tasks including documentation, order entry, billing and coding, and system security accounted for nearly one-half of the total EHR time (157 minutes, 44.2%). Inbox management accounted for another 85 minutes (23.7%). Primary care physicians spend more than one-half of their workday, nearly 6 hours, interacting with the EHR during and after clinic hours. EHR event logs can identify areas of EHR-related work that could be delegated, thus reducing workload, improving professional satisfaction, and decreasing burnout. Direct time-motion observations validated EHR-event log data as a reliable source of information regarding clinician time allocation. © 2017 Annals of Family Medicine, Inc.

Quality Requirements for Electronic Health Record Systems*. A Japanese-German Information Management Perspective.

PubMed

Winter, Alfred; Takabayashi, Katsuhiko; Jahn, Franziska; Kimura, Eizen; Engelbrecht, Rolf; Haux, Reinhold; Honda, Masayuki; Hübner, Ursula H; Inoue, Sozo; Kohl, Christian D; Matsumoto, Takehiro; Matsumura, Yasushi; Miyo, Kengo; Nakashima, Naoki; Prokosch, Hans-Ulrich; Staemmler, Martin

2017-08-07

For more than 30 years, there has been close cooperation between Japanese and German scientists with regard to information systems in health care. Collaboration has been formalized by an agreement between the respective scientific associations. Following this agreement, two joint workshops took place to explore the similarities and differences of electronic health record systems (EHRS) against the background of the two national healthcare systems that share many commonalities. To establish a framework and requirements for the quality of EHRS that may also serve as a basis for comparing different EHRS. Donabedian's three dimensions of quality of medical care were adapted to the outcome, process, and structural quality of EHRS and their management. These quality dimensions were proposed before the first workshop of EHRS experts and enriched during the discussions. The Quality Requirements Framework of EHRS (QRF-EHRS) was defined and complemented by requirements for high quality EHRS. The framework integrates three quality dimensions (outcome, process, and structural quality), three layers of information systems (processes and data, applications, and physical tools) and three dimensions of information management (strategic, tactical, and operational information management). Describing and comparing the quality of EHRS is in fact a multidimensional problem as given by the QRF-EHRS framework. This framework will be utilized to compare Japanese and German EHRS, notably those that were presented at the second workshop.

Macro influencers of electronic health records adoption.

PubMed

Raghavan, Vijay V; Chinta, Ravi; Zhirkin, Nikita

2015-01-01

While adoption rates for electronic health records (EHRs) have improved, the reasons for significant geographical differences in EHR adoption within the USA have remained unclear. To understand the reasons for these variations across states, we have compiled from secondary sources a profile of different states within the USA, based on macroeconomic and macro health-environment factors. Regression analyses were performed using these indicator factors on EHR adoption. The results showed that internet usage and literacy are significantly associated with certain measures of EHR adoption. Income level was not significantly associated with EHR adoption. Per capita patient days (a proxy for healthcare need intensity within a state) is negatively correlated with EHR adoption rate. Health insurance coverage is positively correlated with EHR adoption rate. Older physicians (>60 years) tend to adopt EHR systems less than their younger counterparts. These findings have policy implications on formulating regionally focused incentive programs.

Strategies for Primary Care Stakeholders to Improve Electronic Health Records (EHRs).

PubMed

Olayiwola, J Nwando; Rubin, Ashley; Slomoff, Theo; Woldeyesus, Tem; Willard-Grace, Rachel

2016-01-01

The use of electronic health records (EHRs) and the vendors that develop them have increased exponentially in recent years. While there continues to emerge literature on the challenges EHRs have created related to primary care provider satisfaction and workflow, there is sparse literature on the perspective of the EHR vendors themselves. We examined the role of EHR vendors in optimizing primary care practice through a qualitative study of vendor leadership and developers representing 8 companies. We found that EHR vendors apply a range of strategies to elicit feedback from their clinical users and to engage selected users in their development and design process, but priorities are heavily influenced by the macroenvironment and government regulations. To improve the "marriage" between primary care and the EHR vendor community, we propose 6 strategies that may be most impactful for primary care stakeholders seeking to influence EHR development processes. © Copyright 2016 by the American Board of Family Medicine.

Examining Evidence-Based Content Related to Hospital Acquired Pressure Ulcer Prevention in Paper and Electronic Health Records

ERIC Educational Resources Information Center

Jaekel, Camilla M.

2012-01-01

Although there have been great advancements in the Electronic Health Record (EHR), there is a dearth of rigorous research that examines the relationship between the use of electronic documentation to capture nursing process components and the impact of consistent documentation on patient outcomes (Daly, Buckwalter & Maas, 2002; Gugerty, 2006;…

Combining PubMed knowledge and EHR data to develop a weighted bayesian network for pancreatic cancer prediction.

PubMed

Zhao, Di; Weng, Chunhua

2011-10-01

In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. Copyright © 2011 Elsevier Inc. All rights reserved.

Combining PubMed Knowledge and EHR Data to Develop a Weighted Bayesian Network for Pancreatic Cancer Prediction

PubMed Central

Zhao, Di; Weng, Chunhua

2011-01-01

In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. PMID:21642013

45 CFR 170.302 - General certification criteria for Complete EHRs or EHR Modules.

Code of Federal Regulations, 2013 CFR

2013-10-01

... INFORMATION TECHNOLOGY HEALTH INFORMATION TECHNOLOGY STANDARDS, IMPLEMENTATION SPECIFICATIONS, AND CERTIFICATION CRITERIA AND CERTIFICATION PROGRAMS FOR HEALTH INFORMATION TECHNOLOGY Certification Criteria for Health Information Technology § 170.302 General certification criteria for Complete EHRs or EHR Modules...

45 CFR 170.302 - General certification criteria for Complete EHRs or EHR Modules.

Code of Federal Regulations, 2014 CFR

2014-10-01

... INFORMATION TECHNOLOGY HEALTH INFORMATION TECHNOLOGY STANDARDS, IMPLEMENTATION SPECIFICATIONS, AND CERTIFICATION CRITERIA AND CERTIFICATION PROGRAMS FOR HEALTH INFORMATION TECHNOLOGY Certification Criteria for Health Information Technology § 170.302 General certification criteria for Complete EHRs or EHR Modules...

45 CFR 170.302 - General certification criteria for Complete EHRs or EHR Modules.

Code of Federal Regulations, 2011 CFR

2011-10-01

... INFORMATION TECHNOLOGY HEALTH INFORMATION TECHNOLOGY STANDARDS, IMPLEMENTATION SPECIFICATIONS, AND CERTIFICATION CRITERIA AND CERTIFICATION PROGRAMS FOR HEALTH INFORMATION TECHNOLOGY Certification Criteria for Health Information Technology § 170.302 General certification criteria for Complete EHRs or EHR Modules...

45 CFR 170.302 - General certification criteria for Complete EHRs or EHR Modules.

Code of Federal Regulations, 2012 CFR

2012-10-01

... INFORMATION TECHNOLOGY HEALTH INFORMATION TECHNOLOGY STANDARDS, IMPLEMENTATION SPECIFICATIONS, AND CERTIFICATION CRITERIA AND CERTIFICATION PROGRAMS FOR HEALTH INFORMATION TECHNOLOGY Certification Criteria for Health Information Technology § 170.302 General certification criteria for Complete EHRs or EHR Modules...

45 CFR 170.302 - General certification criteria for Complete EHRs or EHR Modules.

Code of Federal Regulations, 2010 CFR

2010-10-01

... INFORMATION TECHNOLOGY HEALTH INFORMATION TECHNOLOGY STANDARDS, IMPLEMENTATION SPECIFICATIONS, AND CERTIFICATION CRITERIA AND CERTIFICATION PROGRAMS FOR HEALTH INFORMATION TECHNOLOGY Certification Criteria for Health Information Technology § 170.302 General certification criteria for Complete EHRs or EHR Modules...

The association between EHRs and care coordination varies by team cohesion.

PubMed

Graetz, Ilana; Reed, Mary; Shortell, Stephen M; Rundall, Thomas G; Bellows, Jim; Hsu, John

2014-02-01

To examine whether primary care team cohesion changes the association between using an integrated outpatient-inpatient electronic health record (EHR) and clinician-rated care coordination across delivery sites. Self-administered surveys of primary care clinicians in a large integrated delivery system, collected in 2005 (N=565), 2006 (N=678), and 2008 (N=626) during the staggered implementation of an integrated EHR (2005-2010), including validated questions on team cohesion. Using multivariable regression, we examined the combined effect of EHR use and team cohesion on three dimensions of care coordination across delivery sites: access to timely and complete information, treatment agreement, and responsibility agreement. Among clinicians working in teams with higher cohesion, EHR use was associated with significant improvements in reported access to timely and complete information (53.5 percent with EHR vs. 37.6 percent without integrated-EHR), agreement on treatment goals (64.3 percent vs. 50.6 percent), and agreement on responsibilities (63.9 percent vs. 55.2 percent, all p<.05). We found no statistically significant association between use of the integrated-EHR and reported care coordination in less cohesive teams. The association between EHR use and reported care coordination varied by level of team cohesion. EHRs may not improve care coordination in less cohesive teams. © Health Research and Educational Trust.

Community-level determinants of obesity: harnessing the power of electronic health records for retrospective data analysis.

PubMed

Roth, Caryn; Foraker, Randi E; Payne, Philip R O; Embi, Peter J

2014-05-08

Obesity and overweight are multifactorial diseases that affect two thirds of Americans, lead to numerous health conditions and deeply strain our healthcare system. With the increasing prevalence and dangers associated with higher body weight, there is great impetus to focus on public health strategies to prevent or curb the disease. Electronic health records (EHRs) are a powerful source for retrospective health data, but they lack important community-level information known to be associated with obesity. We explored linking EHR and community data to study factors associated with overweight and obesity in a systematic and rigorous way. We augmented EHR-derived data on 62,701 patients with zip code-level socioeconomic and obesogenic data. Using a multinomial logistic regression model, we estimated odds ratios and 95% confidence intervals (OR, 95% CI) for community-level factors associated with overweight and obese body mass index (BMI), accounting for the clustering of patients within zip codes. 33, 31 and 35 percent of individuals had BMIs corresponding to normal, overweight and obese, respectively. Models adjusted for age, race and gender showed more farmers' markets/1,000 people (0.19, 0.10-0.36), more grocery stores/1,000 people (0.58, 0.36-0.93) and a 10% increase in percentage of college graduates (0.80, 0.77-0.84) were associated with lower odds of obesity. The same factors yielded odds ratios of smaller magnitudes for overweight. Our results also indicate that larger grocery stores may be inversely associated with obesity. Integrating community data into the EHR maximizes the potential of secondary use of EHR data to study and impact obesity prevention and other significant public health issues.

An Infinite Mixture Model for Coreference Resolution in Clinical Notes

PubMed Central

Liu, Sijia; Liu, Hongfang; Chaudhary, Vipin; Li, Dingcheng

2016-01-01

It is widely acknowledged that natural language processing is indispensable to process electronic health records (EHRs). However, poor performance in relation detection tasks, such as coreference (linguistic expressions pertaining to the same entity/event) may affect the quality of EHR processing. Hence, there is a critical need to advance the research for relation detection from EHRs. Most of the clinical coreference resolution systems are based on either supervised machine learning or rule-based methods. The need for manually annotated corpus hampers the use of such system in large scale. In this paper, we present an infinite mixture model method using definite sampling to resolve coreferent relations among mentions in clinical notes. A similarity measure function is proposed to determine the coreferent relations. Our system achieved a 0.847 F-measure for i2b2 2011 coreference corpus. This promising results and the unsupervised nature make it possible to apply the system in big-data clinical setting. PMID:27595047

Facilitating the openEHR approach - organizational structures for defining high-quality archetypes.

PubMed

Kohl, Christian Dominik; Garde, Sebastian; Knaup, Petra

2008-01-01

Using openEHR archetypes to establish an electronic patient record promises rapid development and system interoperability by using or adopting existing archetypes. However, internationally accepted, high quality archetypes which enable a comprehensive semantic interoperability require adequate development and maintenance processes. Therefore, structures have to be created involving different health professions. In the following we present a model which facilitates and governs distributed but cooperative development and adoption of archetypes by different professionals including peer reviews. Our model consists of a hierarchical structure of professional committees and descriptions of the archetype development process considering these different committees.

Effects of exam room EHR use on doctor-patient communication: a systematic literature review.

PubMed

Kazmi, Zainab

2013-01-01

High levels of funding have been invested in health information technologies, especially electronic health records (EHRs), in an effect to coordinate and organize patient health data. However, the effect of EHRs in the exam room on doctor-patient communication has not been sufficiently explored. Objective The purpose of this systematic review was to determine how physician use of EHRs in medical consultations affects doctor-patient communication, both in terms of patient perceptions and actual physician behaviours. The reviewer conducted a comprehensive online database search in March 2013 of EMBASE, MEDLINE, and SCOPUS, using a combination of synonyms of the terms "patient", "doctor", "communication", and "EHR" or "computing". For inclusion in this review, articles had to be published in English, take place in an outpatient setting and demonstrate an empirical investigation into whether EHR affects doctor-patient communication. The reviewer then analysed 13 articles that met the inclusion criteria. Studies showed EHR use encouraged biomedical questioning of the patient, and encouraged patient-led questioning and doctor-led information provision. EHR-related behaviours such as keyboarding and screen gaze impaired relationships with patients, by reducing eye contact, rapport, and provision of emotional support. EHRs negatively affected physician-led patient-centred communication. Computer use may have amplified existing physician behaviours regarding medical record use. We noted both positive and negative effects of EHR use. This review highlights the need for increased EHR-specific communication training to mitigate adverse effects and for continued acknowledgement of patient perspectives.

Promoting Secondary Analysis of Electronic Medical Records in China: Summary of the PLAGH-MIT Critical Data Conference and Health Datathon.

PubMed

Li, Peiyao; Xie, Chen; Pollard, Tom; Johnson, Alistair Edward William; Cao, Desen; Kang, Hongjun; Liang, Hong; Zhang, Yuezhou; Liu, Xiaoli; Fan, Yong; Zhang, Yuan; Xue, Wanguo; Xie, Lixin; Celi, Leo Anthony; Zhang, Zhengbo

2017-11-14

Electronic health records (EHRs) have been widely adopted among modern hospitals to collect and track clinical data. Secondary analysis of EHRs could complement the traditional randomized control trial (RCT) research model. However, most researchers in China lack either the technical expertise or the resources needed to utilize EHRs as a resource. In addition, a climate of cross-disciplinary collaboration to gain insights from EHRs, a crucial component of a learning healthcare system, is not prevalent. To address these issues, members from the Massachusetts Institute of Technology (MIT) and the People's Liberation Army General Hospital (PLAGH) organized the first clinical data conference and health datathon in China, which provided a platform for clinicians, statisticians, and data scientists to team up and address information gaps in the intensive care unit (ICU). ©Peiyao Li, Chen Xie, Tom Pollard, Alistair Edward William Johnson, Desen Cao, Hongjun Kang, Hong Liang, Yuezhou Zhang, Xiaoli Liu, Yong Fan, Yuan Zhang, Wanguo Xue, Lixin Xie, Leo Anthony Celi, Zhengbo Zhang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 14.11.2017.

Unintended adverse consequences of electronic health record introduction to a mature universal HIV screening program.

PubMed

Medford-Davis, Laura N; Yang, Katharine; Pasalar, Siavash; Pillow, M Tyson; Miertschin, Nancy P; Peacock, William F; Giordano, Thomas P; Hoxhaj, Shkelzen

2016-01-01

Early HIV detection and treatment decreases morbidity and mortality and reduces high-risk behaviors. Many Emergency Departments (EDs) have HIV screening programs as recommended by the Centers for Disease Control and Prevention. Recent federal legislation includes incentives for electronic health record (EHR) adoption. Our objective was to analyze the impact of conversion to EHR on a mature ED-based HIV screening program. A retrospective pre- and post-EHR implementation cohort study was conducted in a large urban, academic ED. Medical records were reviewed for HIV screening rates from August 2008 through October 2013. On 1 November 2010, a comprehensive EHR system was implemented throughout the hospital. Before EHR implementation, labs were requested by providers by paper orders with HIV-1/2 automatically pre-selected on every form. This universal ordering protocol was not duplicated in the new EHR; rather it required a provider to manually enter the order. Using a chi-squared test, we compared HIV testing in the 6 months before and after EHR implementation; 55,054 patients presented before, and 50,576 after EHR implementation. Age, sex, race, acuity of presenting condition, and HIV seropositivity rates were similar pre- and post-EHR, and there were no major patient or provider changes during this period. Average HIV testing rate was 37.7% of all ED patients pre-, and 22.3% post-EHR, a 41% decline (p < 0.0001), leading to 167 missed new diagnoses after EHR. The rate of HIV screening in the ED decreased after EHR implementation, and could have been improved with more thoughtful inclusion of existing human processes in its design.

Electronic Health Records: Then, Now, and in the Future

PubMed Central

2016-01-01

Summary Objectives Describe the state of Electronic Health Records (EHRs) in 1992 and their evolution by 2015 and where EHRs are expected to be in 25 years. Further to discuss the expectations for EHRs in 1992 and explore which of them were realized and what events accelerated or disrupted/derailed how EHRs evolved. Methods Literature search based on “Electronic Health Record”, “Medical Record”, and “Medical Chart” using Medline, Google, Wikipedia Medical, and Cochrane Libraries resulted in an initial review of 2,356 abstracts and other information in papers and books. Additional papers and books were identified through the review of references cited in the initial review. Results By 1992, hardware had become more affordable, powerful, and compact and the use of personal computers, local area networks, and the Internet provided faster and easier access to medical information. EHRs were initially developed and used at academic medical facilities but since most have been replaced by large vendor EHRs. While EHR use has increased and clinicians are being prepared to practice in an EHR-mediated world, technical issues have been overshadowed by procedural, professional, social, political, and especially ethical issues as well as the need for compliance with standards and information security. There have been enormous advancements that have taken place, but many of the early expectations for EHRs have not been realized and current EHRs still do not meet the needs of today’s rapidly changing healthcare environment. Conclusion The current use of EHRs initiated by new technology would have been hard to foresee. Current and new EHR technology will help to provide international standards for interoperable applications that use health, social, economic, behavioral, and environmental data to communicate, interpret, and act intelligently upon complex healthcare information to foster precision medicine and a learning health system. PMID:27199197

Safeguarding Confidentiality in Electronic Health Records.

PubMed

Shenoy, Akhil; Appel, Jacob M

2017-04-01

Electronic health records (EHRs) offer significant advantages over paper charts, such as ease of portability, facilitated communication, and a decreased risk of medical errors; however, important ethical concerns related to patient confidentiality remain. Although legal protections have been implemented, in practice, EHRs may be still prone to breaches that threaten patient privacy. Potential safeguards are essential, and have been implemented especially in sensitive areas such as mental illness, substance abuse, and sexual health. Features of one institutional model are described that may illustrate the efforts to both ensure adequate transparency and ensure patient confidentiality. Trust and the therapeutic alliance are critical to the provider-patient relationship and quality healthcare services. All of the benefits of an EHR are only possible if patients retain confidence in the security and accuracy of their medical records.

Development of a Web-Based Registry to Support Diabetes Care in Free Medical Clinics.

PubMed

McFadden, Norman; Daniel, Bryan; Hoyt, Robert; Snider, Dallas

2017-01-01

The United States has more than 1,000 free medical clinics. Because these clinics do not bill Medicare or Medicaid, they are not eligible for federal reimbursement for electronic health record (EHR) adoption. As a result, most do not have EHRs or electronic disease registries. A web-based diabetes registry was created with all open-source components for use in an urban free clinic to manage patients with type 2 diabetes and comorbidities. The registry was modeled after the Chronic Disease Electronic Management System and recommendations of the American Diabetes Association. The software was enhanced to include multiple other features, such as progress notes, so that it can function as a simple EHR. The configuration permits other free clinics to join securely, and the software can be shared.

Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies.

PubMed

Cohen, Raphael; Elhadad, Michael; Elhadad, Noémie

2013-01-16

The increasing availability of Electronic Health Record (EHR) data and specifically free-text patient notes presents opportunities for phenotype extraction. Text-mining methods in particular can help disease modeling by mapping named-entities mentions to terminologies and clustering semantically related terms. EHR corpora, however, exhibit specific statistical and linguistic characteristics when compared with corpora in the biomedical literature domain. We focus on copy-and-paste redundancy: clinicians typically copy and paste information from previous notes when documenting a current patient encounter. Thus, within a longitudinal patient record, one expects to observe heavy redundancy. In this paper, we ask three research questions: (i) How can redundancy be quantified in large-scale text corpora? (ii) Conventional wisdom is that larger corpora yield better results in text mining. But how does the observed EHR redundancy affect text mining? Does such redundancy introduce a bias that distorts learned models? Or does the redundancy introduce benefits by highlighting stable and important subsets of the corpus? (iii) How can one mitigate the impact of redundancy on text mining? We analyze a large-scale EHR corpus and quantify redundancy both in terms of word and semantic concept repetition. We observe redundancy levels of about 30% and non-standard distribution of both words and concepts. We measure the impact of redundancy on two standard text-mining applications: collocation identification and topic modeling. We compare the results of these methods on synthetic data with controlled levels of redundancy and observe significant performance variation. Finally, we compare two mitigation strategies to avoid redundancy-induced bias: (i) a baseline strategy, keeping only the last note for each patient in the corpus; (ii) removing redundant notes with an efficient fingerprinting-based algorithm. (a)For text mining, preprocessing the EHR corpus with fingerprinting yields significantly better results. Before applying text-mining techniques, one must pay careful attention to the structure of the analyzed corpora. While the importance of data cleaning has been known for low-level text characteristics (e.g., encoding and spelling), high-level and difficult-to-quantify corpus characteristics, such as naturally occurring redundancy, can also hurt text mining. Fingerprinting enables text-mining techniques to leverage available data in the EHR corpus, while avoiding the bias introduced by redundancy.

How the provenance of electronic health record data matters for research: a case example using system mapping.

PubMed

Johnson, Karin E; Kamineni, Aruna; Fuller, Sharon; Olmstead, Danielle; Wernli, Karen J

2014-01-01

The use of electronic health records (EHRs) for research is proceeding rapidly, driven by computational power, analytical techniques, and policy. However, EHR-based research is limited by the complexity of EHR data and a lack of understanding about data provenance, meaning the context under which the data were collected. This paper presents system flow mapping as a method to help researchers more fully understand the provenance of their EHR data as it relates to local workflow. We provide two specific examples of how this method can improve data identification, documentation, and processing. EHRs store clinical and administrative data, often in unstructured fields. Each clinical system has a unique and dynamic workflow, as well as an EHR customized for local use. The EHR customization may be influenced by a broader context such as documentation required for billing. We present a case study with two examples of using system flow mapping to characterize EHR data for a local colorectal cancer screening process. System flow mapping demonstrated that information entered into the EHR during clinical practice required interpretation and transformation before it could be accurately applied to research. We illustrate how system flow mapping shaped our knowledge of the quality and completeness of data in two examples: (1) determining colonoscopy indication as recorded in the EHR, and (2) discovering a specific EHR form that captured family history. Researchers who do not consider data provenance risk compiling data that are systematically incomplete or incorrect. For example, researchers who are not familiar with the clinical workflow under which data were entered might miss or misunderstand patient information or procedure and diagnostic codes. Data provenance is a fundamental characteristic of research data from EHRs. Given the diversity of EHR platforms and system workflows, researchers need tools for evaluating and reporting data availability, quality, and transformations. Our case study illustrates how system mapping can inform researchers about the provenance of their data as it pertains to local workflows.

Electronic Health Records Data and Metadata: Challenges for Big Data in the United States.

PubMed

Sweet, Lauren E; Moulaison, Heather Lea

2013-12-01

This article, written by researchers studying metadata and standards, represents a fresh perspective on the challenges of electronic health records (EHRs) and serves as a primer for big data researchers new to health-related issues. Primarily, we argue for the importance of the systematic adoption of standards in EHR data and metadata as a way of promoting big data research and benefiting patients. EHRs have the potential to include a vast amount of longitudinal health data, and metadata provides the formal structures to govern that data. In the United States, electronic medical records (EMRs) are part of the larger EHR. EHR data is submitted by a variety of clinical data providers and potentially by the patients themselves. Because data input practices are not necessarily standardized, and because of the multiplicity of current standards, basic interoperability in EHRs is hindered. Some of the issues with EHR interoperability stem from the complexities of the data they include, which can be both structured and unstructured. A number of controlled vocabularies are available to data providers. The continuity of care document standard will provide interoperability in the United States between the EMR and the larger EHR, potentially making data input by providers directly available to other providers. The data involved is nonetheless messy. In particular, the use of competing vocabularies such as the Systematized Nomenclature of Medicine-Clinical Terms, MEDCIN, and locally created vocabularies inhibits large-scale interoperability for structured portions of the records, and unstructured portions, although potentially not machine readable, remain essential. Once EMRs for patients are brought together as EHRs, the EHRs must be managed and stored. Adequate documentation should be created and maintained to assure the secure and accurate use of EHR data. There are currently a few notable international standards initiatives for EHRs. Organizations such as Health Level Seven International and Clinical Data Interchange Standards Consortium are developing and overseeing implementation of interoperability standards. Denmark and Singapore are two countries that have successfully implemented national EHR systems. Future work in electronic health information initiatives should underscore the importance of standards and reinforce interoperability of EHRs for big data research and for the sake of patients.

The impact of interoperability of electronic health records on ambulatory physician practices: a discrete-event simulation study.

PubMed

Zhou, Yuan; Ancker, Jessica S; Upadhye, Mandar; McGeorge, Nicolette M; Guarrera, Theresa K; Hegde, Sudeep; Crane, Peter W; Fairbanks, Rollin J; Bisantz, Ann M; Kaushal, Rainu; Lin, Li

2013-01-01

The effect of health information technology (HIT) on efficiency and workload among clinical and nonclinical staff has been debated, with conflicting evidence about whether electronic health records (EHRs) increase or decrease effort. None of this paper to date, however, examines the effect of interoperability quantitatively using discrete event simulation techniques. To estimate the impact of EHR systems with various levels of interoperability on day-to-day tasks and operations of ambulatory physician offices. Interviews and observations were used to collect workflow data from 12 adult primary and specialty practices. A discrete event simulation model was constructed to represent patient flows and clinical and administrative tasks of physicians and staff members. High levels of EHR interoperability were associated with reduced time spent by providers on four tasks: preparing lab reports, requesting lab orders, prescribing medications, and writing referrals. The implementation of an EHR was associated with less time spent by administrators but more time spent by physicians, compared with time spent at paper-based practices. In addition, the presence of EHRs and of interoperability did not significantly affect the time usage of registered nurses or the total visit time and waiting time of patients. This paper suggests that the impact of using HIT on clinical and nonclinical staff work efficiency varies, however, overall it appears to improve time efficiency more for administrators than for physicians and nurses.

A red-flag-based approach to risk management of EHR-related safety concerns.

PubMed

Sittig, Dean F; Singh, Hardeep

2013-01-01

Although electronic health records (EHRs) have a significant potential to improve patient safety, EHR-related safety concerns have begun to emerge. Based on 369 responses to a survey sent to the memberships of the American Society for Healthcare Risk Management and the American Health Lawyers Association and supplemented by our previous work in EHR-related patient safety, we identified the following common EHR-related safety concerns: (1) incorrect patient identification; (2) extended EHR unavailability (either planned or unplanned); (3) failure to heed a computer-generated warning or alert; (4) system-to-system interface errors; (5) failure to identify, find, or use the most recent patient data; (6) misunderstandings about time; (7) incorrect item selected from a list of items; and (8) open or incomplete orders. In this article, we present a "red-flag"-based approach that can be used by risk managers to identify potential EHR safety concerns in their institutions. An organization that routinely conducts EHR-related surveillance activities, such as the ones proposed here, can significantly reduce risks associated with EHR implementation and use. © 2013 American Society for Healthcare Risk Management of the American Hospital Association.

Clinical Genomics in the World of the Electronic Health Record

PubMed Central

Marsolo, Keith; Spooner, S. Andrew

2014-01-01

The widespread of adoption of EHRs presents a number of benefits to the field of clinical genomics. They include the ability to return results to the practitioner, the ability to use genetic findings in clinical decision support, and to have data collected in the EHR serve as a source of phenotypic information for analysis purposes. Not all EHRs are created equal, however. They differ in their features, capabilities and ease-of-use. Therefore, in order to understand the potential of the EHR, it is first necessary to understand its capabilities and the impact that implementation strategy has on usability. Specifically, we focus on the following areas: 1) how the EHR is used to capture data in clinical practice settings; 2) how the implementation and configuration of the EHR affects the quality and availability of data; 3) the management of clinical genetic test results and the feasibility of EHR integration; and 4) the challenges of implementing an EHR in a research-intensive environment. This is followed by a discussion of the minimum functional requirements that an EHR must meet to enable the satisfactory integration of genomic results as well as the open issues that remain. PMID:23846403

Validation of the openEHR archetype library by using OWL reasoning.

PubMed

Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2011-01-01

Electronic Health Record architectures based on the dual model architecture use archetypes for representing clinical knowledge. Therefore, ensuring their correctness and consistency is a fundamental research goal. In this work, we explore how an approach based on OWL technologies can be used for such purpose. This method has been applied to the openEHR archetype repository, which is the largest available one nowadays. The results of this validation are also reported in this study.

Prediction task guided representation learning of medical codes in EHR.

PubMed

Cui, Liwen; Xie, Xiaolei; Shen, Zuojun

2018-06-18

There have been rapidly growing applications using machine learning models for predictive analytics in Electronic Health Records (EHR) to improve the quality of hospital services and the efficiency of healthcare resource utilization. A fundamental and crucial step in developing such models is to convert medical codes in EHR to feature vectors. These medical codes are used to represent diagnoses or procedures. Their vector representations have a tremendous impact on the performance of machine learning models. Recently, some researchers have utilized representation learning methods from Natural Language Processing (NLP) to learn vector representations of medical codes. However, most previous approaches are unsupervised, i.e. the generation of medical code vectors is independent from prediction tasks. Thus, the obtained feature vectors may be inappropriate for a specific prediction task. Moreover, unsupervised methods often require a lot of samples to obtain reliable results, but most practical problems have very limited patient samples. In this paper, we develop a new method called Prediction Task Guided Health Record Aggregation (PTGHRA), which aggregates health records guided by prediction tasks, to construct training corpus for various representation learning models. Compared with unsupervised approaches, representation learning models integrated with PTGHRA yield a significant improvement in predictive capability of generated medical code vectors, especially for limited training samples. Copyright © 2018. Published by Elsevier Inc.

Do family physicians electronic health records support meaningful use?

PubMed

Peterson, Lars E; Blackburn, Brenna; Ivins, Douglas; Mitchell, Jason; Matson, Christine; Phillips, Robert L

2015-03-01

Spurred by government incentives, the use of electronic health records (EHRs) in the United States has increased; however, whether these EHRs have the functionality necessary to meet meaningful use (MU) criteria remains unknown. Our objective was to characterize family physician access to MU functionality when using a MU-certified EHR. Data were obtained from a convenience survey of family physicians accessing their American Board of Family Medicine online portfolio in 2011. A brief survey queried MU functionality. We used descriptive statistics to characterize the responses and bivariate statistics to test associations between MU and patient communication functions by presence of a MU-certified EHR. Out of 3855 respondents, 60% reported having an EHR that supports MU. Physicians with MU-certified EHRs were more likely than physicians without MU-certified EHRs to report patient registry activities (49.7% vs. 32.3%, p-value<0.01), tracking quality measures (74.1% vs. 56.4%, p-value<0.01), access to labs or consultation notes, and electronic prescribing; but electronic communication abilities were low regardless of EHR capabilities. Family physicians with MU-certified EHRs are more likely to report MU functionality; however, a sizeable minority does not report MU functions. Many family physicians with MU-certified EHRs may not successfully meet the successively stringent MU criteria and may face significant upgrade costs to do so. Cross sectional survey. Copyright © 2014 Elsevier Inc. All rights reserved.

Exploring the business case for ambulatory electronic health record system adoption.

PubMed

Song, Paula H; McAlearney, Ann Scheck; Robbins, Julie; McCullough, Jeffrey S

2011-01-01

Widespread implementation and use of electronic health record (EHR) systems has been recognized by healthcare leaders as a cornerstone strategy for systematically reducing medical errors and improving clinical quality. However, EHR adoption requires a significant capital investment for healthcare providers, and cost is often cited as a barrier. Despite the capital requirements, a true business case for EHR system adoption and implementation has not been made. This is of concern, as the lack of a business case can influence decision making about EHR investments. The purpose of this study was to examine the role of business case analysis in healthcare organizations' decisions to invest in ambulatory EHR systems, and to identify what factors organizations considered when justifying an ambulatory EHR. Using a qualitative case study approach, we explored how five organizations that are considered to have best practices in ambulatory EHR system implementation had evaluated the business case for EHR adoption. We found that although the rigor of formal business case analysis was highly variable, informants across these organizations consistently reported perceiving that a positive business case for EHR system adoption existed, especially when they considered both financial and non-financial benefits. While many consider EHR system adoption inevitable in healthcare, this viewpoint should not deter managers from conducting a business case analysis. Results of such an analysis can inform healthcare organizations' understanding about resource allocation needs, help clarify expectations about financial and clinical performance metrics to be monitored through EHR systems, and form the basis for ongoing organizational support to ensure successful system implementation.

Electronic health records: use, barriers and satisfaction among physicians who care for black and Hispanic patients.

PubMed

Jha, Ashish K; Bates, David W; Jenter, Chelsea; Orav, E John; Zheng, Jie; Cleary, Paul; Simon, Steven R

2009-02-01

Electronic health records (EHRs) are a promising tool to improve the quality of health care, although it remains unclear who will benefit from this new technology. Given that a small group of providers care for most racial/ethnic minorities, we sought to determine whether minority-serving providers adopt EHR systems at comparable rates to other providers. We used survey data from stratified random sample of all medical practices in Massachusetts in 2005. We determined rates of EHR adoption, perceived barriers to adoption, and satisfaction with EHR systems. Physicians who reported patient panels of more than 40% black or Hispanic had comparable levels of EHR adoption than other physicians (27.9% and 21.8%, respectively, P = 0.46). Physicians from minority-serving practices identified financial and other barriers to implementing EHR systems at similar rates, although these physicians were less likely to be concerned with privacy and security concerns of EHRs (47.1% vs. 64.4%, P = 0.01). Finally, physicians from high-minority practices had similar perceptions about the positive impact of EHRs on quality (73.7% vs. 76.6%, P = 0.43) and costs (46.9% vs. 51.5%, P = 0.17) of care. In a state with a diverse minority population, we found no evidence that minority-serving providers had lower EHR adoption rates, faced different barriers to adoption or were less satisfied with EHRs. Given the importance of ensuring that minority-serving providers have equal access to EHR systems, we failed to find evidence of a new digital divide.

The Gap in Big Data: Getting to Wellbeing, Strengths, and a Whole-person Perspective

PubMed Central

Peters, Judith; Schlesner, Sara; Vanderboom, Catherine E.; Holland, Diane E.

2015-01-01

Background: Electronic health records (EHRs) provide a clinical view of patient health. EHR data are becoming available in large data sets and enabling research that will transform the landscape of healthcare research. Methods are needed to incorporate wellbeing dimensions and strengths in large data sets. The purpose of this study was to examine the potential alignment of the Wellbeing Model with a clinical interface terminology standard, the Omaha System, for documenting wellbeing assessments. Objective: To map the Omaha System and Wellbeing Model for use in a clinical EHR wellbeing assessment and to evaluate the feasibility of describing strengths and needs of seniors generated through this assessment. Methods: The Wellbeing Model and Omaha System were mapped using concept mapping techniques. Based on this mapping, a wellbeing assessment was developed and implemented within a clinical EHR. Strengths indicators and signs/symptoms data for 5 seniors living in a residential community were abstracted from wellbeing assessments and analyzed using standard descriptive statistics and pattern visualization techniques. Results: Initial mapping agreement was 93.5%, with differences resolved by consensus. Wellbeing data analysis showed seniors had an average of 34.8 (range=22-49) strengths indicators for 22.8 concepts. They had an average of 6.4 (range=4-8) signs/symptoms for an average of 3.2 (range=2-5) concepts. The ratio of strengths indicators to signs/symptoms was 6:1 (range 2.8-9.6). Problem concepts with more signs/symptoms had fewer strengths. Conclusion: Together, the Wellbeing Model and the Omaha System have potential to enable a whole-person perspective and enhance the potential for a wellbeing perspective in big data research in healthcare. PMID:25984416

The Gap in Big Data: Getting to Wellbeing, Strengths, and a Whole-person Perspective.

PubMed

Monsen, Karen A; Peters, Judith; Schlesner, Sara; Vanderboom, Catherine E; Holland, Diane E

2015-05-01

Electronic health records (EHRs) provide a clinical view of patient health. EHR data are becoming available in large data sets and enabling research that will transform the landscape of healthcare research. Methods are needed to incorporate wellbeing dimensions and strengths in large data sets. The purpose of this study was to examine the potential alignment of the Wellbeing Model with a clinical interface terminology standard, the Omaha System, for documenting wellbeing assessments. To map the Omaha System and Wellbeing Model for use in a clinical EHR wellbeing assessment and to evaluate the feasibility of describing strengths and needs of seniors generated through this assessment. The Wellbeing Model and Omaha System were mapped using concept mapping techniques. Based on this mapping, a wellbeing assessment was developed and implemented within a clinical EHR. Strengths indicators and signs/symptoms data for 5 seniors living in a residential community were abstracted from wellbeing assessments and analyzed using standard descriptive statistics and pattern visualization techniques. Initial mapping agreement was 93.5%, with differences resolved by consensus. Wellbeing data analysis showed seniors had an average of 34.8 (range=22-49) strengths indicators for 22.8 concepts. They had an average of 6.4 (range=4-8) signs/symptoms for an average of 3.2 (range=2-5) concepts. The ratio of strengths indicators to signs/symptoms was 6:1 (range 2.8-9.6). Problem concepts with more signs/symptoms had fewer strengths. Together, the Wellbeing Model and the Omaha System have potential to enable a whole-person perspective and enhance the potential for a wellbeing perspective in big data research in healthcare.

The State of Open Source Electronic Health Record Projects: A Software Anthropology Study

PubMed Central

2017-01-01

Background Electronic health records (EHR) are a key tool in managing and storing patients’ information. Currently, there are over 50 open source EHR systems available. Functionality and usability are important factors for determining the success of any system. These factors are often a direct reflection of the domain knowledge and developers’ motivations. However, few published studies have focused on the characteristics of free and open source software (F/OSS) EHR systems and none to date have discussed the motivation, knowledge background, and demographic characteristics of the developers involved in open source EHR projects. Objective This study analyzed the characteristics of prevailing F/OSS EHR systems and aimed to provide an understanding of the motivation, knowledge background, and characteristics of the developers. Methods This study identified F/OSS EHR projects on SourceForge and other websites from May to July 2014. Projects were classified and characterized by license type, downloads, programming languages, spoken languages, project age, development status, supporting materials, top downloads by country, and whether they were “certified” EHRs. Health care F/OSS developers were also surveyed using an online survey. Results At the time of the assessment, we uncovered 54 open source EHR projects, but only four of them had been successfully certified under the Office of the National Coordinator for Health Information Technology (ONC Health IT) Certification Program. In the majority of cases, the open source EHR software was downloaded by users in the United States (64.07%, 148,666/232,034), underscoring that there is a significant interest in EHR open source applications in the United States. A survey of EHR open source developers was conducted and a total of 103 developers responded to the online questionnaire. The majority of EHR F/OSS developers (65.3%, 66/101) are participating in F/OSS projects as part of a paid activity and only 25.7% (26/101) of EHR F/OSS developers are, or have been, health care providers in their careers. In addition, 45% (45/99) of developers do not work in the health care field. Conclusion The research presented in this study highlights some challenges that may be hindering the future of health care F/OSS. A minority of developers have been health care professionals, and only 55% (54/99) work in the health care field. This undoubtedly limits the ability of functional design of F/OSS EHR systems from being a competitive advantage over prevailing commercial EHR systems. Open source software seems to be a significant interest to many; however, given that only four F/OSS EHR systems are ONC-certified, this interest is unlikely to yield significant adoption of these systems in the United States. Although the Health Information Technology for Economic and Clinical Health (HITECH) act was responsible for a substantial infusion of capital into the EHR marketplace, the lack of a corporate entity in most F/OSS EHR projects translates to a marginal capacity to market the respective F/OSS system and to navigate certification. This likely has further disadvantaged F/OSS EHR adoption in the United States. PMID:28235750

A Digital Architecture for a Network-Based Learning Health System: Integrating Chronic Care Management, Quality Improvement, and Research.

PubMed

Marsolo, Keith; Margolis, Peter A; Forrest, Christopher B; Colletti, Richard B; Hutton, John J

2015-01-01

We collaborated with the ImproveCareNow Network to create a proof-of-concept architecture for a network-based Learning Health System. This collaboration involved transitioning an existing registry to one that is linked to the electronic health record (EHR), enabling a "data in once" strategy. We sought to automate a series of reports that support care improvement while also demonstrating the use of observational registry data for comparative effectiveness research. We worked with three leading EHR vendors to create EHR-based data collection forms. We automated many of ImproveCareNow's analytic reports and developed an application for storing protected health information and tracking patient consent. Finally, we deployed a cohort identification tool to support feasibility studies and hypothesis generation. There is ongoing uptake of the system. To date, 31 centers have adopted the EHR-based forms and 21 centers are uploading data to the registry. Usage of the automated reports remains high and investigators have used the cohort identification tools to respond to several clinical trial requests. The current process for creating EHR-based data collection forms requires groups to work individually with each vendor. A vendor-agnostic model would allow for more rapid uptake. We believe that interfacing network-based registries with the EHR would allow them to serve as a source of decision support. Additional standards are needed in order for this vision to be achieved, however. We have successfully implemented a proof-of-concept Learning Health System while providing a foundation on which others can build. We have also highlighted opportunities where sponsors could help accelerate progress.

Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine.

PubMed

Hanauer, David A; Wu, Danny T Y; Yang, Lei; Mei, Qiaozhu; Murkowski-Steffy, Katherine B; Vydiswaran, V G Vinod; Zheng, Kai

2017-03-01

The utility of biomedical information retrieval environments can be severely limited when users lack expertise in constructing effective search queries. To address this issue, we developed a computer-based query recommendation algorithm that suggests semantically interchangeable terms based on an initial user-entered query. In this study, we assessed the value of this approach, which has broad applicability in biomedical information retrieval, by demonstrating its application as part of a search engine that facilitates retrieval of information from electronic health records (EHRs). The query recommendation algorithm utilizes MetaMap to identify medical concepts from search queries and indexed EHR documents. Synonym variants from UMLS are used to expand the concepts along with a synonym set curated from historical EHR search logs. The empirical study involved 33 clinicians and staff who evaluated the system through a set of simulated EHR search tasks. User acceptance was assessed using the widely used technology acceptance model. The search engine's performance was rated consistently higher with the query recommendation feature turned on vs. off. The relevance of computer-recommended search terms was also rated high, and in most cases the participants had not thought of these terms on their own. The questions on perceived usefulness and perceived ease of use received overwhelmingly positive responses. A vast majority of the participants wanted the query recommendation feature to be available to assist in their day-to-day EHR search tasks. Challenges persist for users to construct effective search queries when retrieving information from biomedical documents including those from EHRs. This study demonstrates that semantically-based query recommendation is a viable solution to addressing this challenge. Published by Elsevier Inc.

The development of a highly constrained health level 7 implementation guide to facilitate electronic laboratory reporting to ambulatory electronic health record systems.

PubMed

Sujansky, Walter V; Overhage, J Marc; Chang, Sophia; Frohlich, Jonah; Faus, Samuel A

2009-01-01

Electronic laboratory interfaces can significantly increase the value of ambulatory electronic health record (EHR) systems by providing laboratory result data automatically and in a computable form. However, many ambulatory EHRs cannot implement electronic laboratory interfaces despite the existence of messaging standards, such as Health Level 7, version 2 (HL7). Among several barriers to implementing laboratory interfaces is the extensive optionality within the HL7 message standard. This paper describes the rationale for and development of an HL7 implementation guide that seeks to eliminate most of the optionality inherent in HL7, but retain the information content required for reporting outpatient laboratory results. A work group of heterogeneous stakeholders developed the implementation guide based on a set of design principles that emphasized parsimony, practical requirements, and near-term adoption. The resulting implementation guide contains 93% fewer optional data elements than HL7. This guide was successfully implemented by 15 organizations during an initial testing phase and has been approved by the HL7 standards body as an implementation guide for outpatient laboratory reporting. Further testing is required to determine whether widespread adoption of the implementation guide by laboratories and EHR systems can facilitate the implementation of electronic laboratory interfaces.

Open data models for smart health interconnected applications: the example of openEHR.

PubMed

Demski, Hans; Garde, Sebastian; Hildebrand, Claudia

2016-10-22

Smart Health is known as a concept that enhances networking, intelligent data processing and combining patient data with other parameters. Open data models can play an important role in creating a framework for providing interoperable data services that support the development of innovative Smart Health applications profiting from data fusion and sharing. This article describes a model-driven engineering approach based on standardized clinical information models and explores its application for the development of interoperable electronic health record systems. The following possible model-driven procedures were considered: provision of data schemes for data exchange, automated generation of artefacts for application development and native platforms that directly execute the models. The applicability of the approach in practice was examined using the openEHR framework as an example. A comprehensive infrastructure for model-driven engineering of electronic health records is presented using the example of the openEHR framework. It is shown that data schema definitions to be used in common practice software development processes can be derived from domain models. The capabilities for automatic creation of implementation artefacts (e.g., data entry forms) are demonstrated. Complementary programming libraries and frameworks that foster the use of open data models are introduced. Several compatible health data platforms are listed. They provide standard based interfaces for interconnecting with further applications. Open data models help build a framework for interoperable data services that support the development of innovative Smart Health applications. Related tools for model-driven application development foster semantic interoperability and interconnected innovative applications.

Screening Electronic Health Record-Related Patient Safety Reports Using Machine Learning.

PubMed

Marella, William M; Sparnon, Erin; Finley, Edward

2017-03-01

The objective of this study was to develop a semiautomated approach to screening cases that describe hazards associated with the electronic health record (EHR) from a mandatory, population-based patient safety reporting system. Potentially relevant cases were identified through a query of the Pennsylvania Patient Safety Reporting System. A random sample of cases were manually screened for relevance and divided into training, testing, and validation data sets to develop a machine learning model. This model was used to automate screening of remaining potentially relevant cases. Of the 4 algorithms tested, a naive Bayes kernel performed best, with an area under the receiver operating characteristic curve of 0.927 ± 0.023, accuracy of 0.855 ± 0.033, and F score of 0.877 ± 0.027. The machine learning model and text mining approach described here are useful tools for identifying and analyzing adverse event and near-miss reports. Although reporting systems are beginning to incorporate structured fields on health information technology and the EHR, these methods can identify related events that reporters classify in other ways. These methods can facilitate analysis of legacy safety reports by retrieving health information technology-related and EHR-related events from databases without fields and controlled values focused on this subject and distinguishing them from reports in which the EHR is mentioned only in passing. Machine learning and text mining are useful additions to the patient safety toolkit and can be used to semiautomate screening and analysis of unstructured text in safety reports from frontline staff.

Desiderata for computable representations of electronic health records-driven phenotype algorithms

PubMed Central

Mo, Huan; Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Jiang, Guoqian; Kiefer, Richard; Zhu, Qian; Xu, Jie; Montague, Enid; Carrell, David S; Lingren, Todd; Mentch, Frank D; Ni, Yizhao; Wehbe, Firas H; Peissig, Peggy L; Tromp, Gerard; Larson, Eric B; Chute, Christopher G; Pathak, Jyotishman; Speltz, Peter; Kho, Abel N; Jarvik, Gail P; Bejan, Cosmin A; Williams, Marc S; Borthwick, Kenneth; Kitchner, Terrie E; Roden, Dan M; Harris, Paul A

2015-01-01

Background Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM). Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms. Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility. Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages. PMID:26342218

An electronic health record based model predicts statin adherence, LDL cholesterol, and cardiovascular disease in the United States Military Health System

PubMed Central

Lucas, Joseph E.; Bazemore, Taylor C.; Alo, Celan; Monahan, Patrick B.

2017-01-01

HMG-CoA reductase inhibitors (or “statins”) are important and commonly used medications to lower cholesterol and prevent cardiovascular disease. Nearly half of patients stop taking statin medications one year after they are prescribed leading to higher cholesterol, increased cardiovascular risk, and costs due to excess hospitalizations. Identifying which patients are at highest risk for not adhering to long-term statin therapy is an important step towards individualizing interventions to improve adherence. Electronic health records (EHR) are an increasingly common source of data that are challenging to analyze but have potential for generating more accurate predictions of disease risk. The aim of this study was to build an EHR based model for statin adherence and link this model to biologic and clinical outcomes in patients receiving statin therapy. We gathered EHR data from the Military Health System which maintains administrative data for active duty, retirees, and dependents of the United States armed forces military that receive health care benefits. Data were gathered from patients prescribed their first statin prescription in 2005 and 2006. Baseline billing, laboratory, and pharmacy claims data were collected from the two years leading up to the first statin prescription and summarized using non-negative matrix factorization. Follow up statin prescription refill data was used to define the adherence outcome (> 80 percent days covered). The subsequent factors to emerge from this model were then used to build cross-validated, predictive models of 1) overall disease risk using coalescent regression and 2) statin adherence (using random forest regression). The predicted statin adherence for each patient was subsequently used to correlate with cholesterol lowering and hospitalizations for cardiovascular disease during the 5 year follow up period using Cox regression. The analytical dataset included 138 731 individuals and 1840 potential baseline predictors that were reduced to 30 independent EHR “factors”. A random forest predictive model taking patient, statin prescription, predicted disease risk, and the EHR factors as potential inputs produced a cross-validated c-statistic of 0.736 for classifying statin non-adherence. The addition of the first refill to the model increased the c-statistic to 0.81. The predicted statin adherence was independently associated with greater cholesterol lowering (correlation = 0.14, p < 1e-20) and lower hospitalization for myocardial infarction, coronary artery disease, and stroke (hazard ratio = 0.84, p = 1.87E-06). Electronic health records data can be used to build a predictive model of statin adherence that also correlates with statins’ cardiovascular benefits. PMID:29155848

The current state of electronic health record (EHR) use in Oklahoma.

PubMed

Khaliq, Amir A; Mwachofi, Ari K; Hughes, Danny R; Broyles, Robert W; Wheeler, Denna; Roswell, Robert H

2013-02-01

There is ample evidence of the positive impact of electronic health records (EHR) on operational efficiencies and quality of care. Yet, growth in the adoption of EHR and sharing of information among providers has been slow. The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 provides financial incentives for eligible providers to adopt and implement EHR. Until now, little information was available regarding the use of EHR in Oklahoma. Sponsored by the Oklahoma Health Information Exchange Trust (OHIET), this study reveals that the frequency of use of EHR among Oklahoma providers is near the national average. Although a large number of Oklahoma physicians have received Medicaid incentive payments for planned adoption, implementation, or upgrade of EHR systems, relatively few eligible providers in Oklahoma have been certified to receive Medicare incentive payments through the Centers for Medicare and Medicaid Services (CMS) and even fewer have actually received these incentive payments.

Electronic Health Record Use a Bitter Pill for Many Physicians.

PubMed

Meigs, Stephen L; Solomon, Michael

2016-01-01

Electronic health record (EHR) adoption among office-based physician practices in the United States has increased significantly in the past decade. However, the challenges of using EHRs have resulted in growing dissatisfaction with the systems among many of these physicians. The purpose of this qualitative multiple-case study was to increase understanding of physician perceptions regarding the value of using EHR technology. Important findings included the belief among physicians that EHR systems need to be more user-friendly and adaptable to individual clinic workflow preferences, physician beliefs that lack of interoperability among EHRs is a major barrier to meaningful use of the systems, and physician beliefs that EHR use does not improve the quality of care provided to patients. These findings suggest that although government initiatives to encourage EHR adoption among office-based physician practices have produced positive results, additional support may be required in the future to maintain this momentum.

Care Coordination and Electronic Health Records: Connecting Clinicians

PubMed Central

Graetz, Ilana; Reed, Mary; Rundall, Thomas; Bellows, Jim; Brand, Richard; Hsu, John

2009-01-01

Objective: To examine the association between use of electronic health records (EHR) and care coordination. Study Design: Two surveys, in 2005 and again in 2006, of primary care clinicians working in a prepaid integrated delivery system during the staggered implementation of an EHR system. Using multivariate logistic regression to adjust for clinician characteristics, we examined the association between EHR use and clinicians’ perceptions of three dimensions of care coordination: timely access to complete information; treatment goal agreement; and role/responsibility agreement. Results: Compared to clinicians without EHR, clinicians with 6+ months of EHR use more frequently reported timely access to complete information, and being in agreement on treatment goals with other involved clinicians. There was no significant association between EHR use and being in agreement on roles and responsibilities with other clinicians. Conclusions: EHR use is associated with aspects of care coordination involving information transfer and communication of treatment goals. PMID:20351851

Risk assessment of integrated electronic health records.

PubMed

Bjornsson, Bjarni Thor; Sigurdardottir, Gudlaug; Stefansson, Stefan Orri

2010-01-01

The paper describes the security concerns related to Electronic Health Records (EHR) both in registration of data and integration of systems. A description of the current state of EHR systems in Iceland is provided, along with the Ministry of Health's future vision and plans. New legislation provides the opportunity for increased integration of EHRs and further collaboration between institutions. Integration of systems, along with greater availability and access to EHR data, requires increased security awareness since additional risks are introduced. The paper describes the core principles of information security as it applies to EHR systems and data. The concepts of confidentiality, integrity, availability, accountability and traceability are introduced and described. The paper discusses the legal requirements and importance of performing risk assessment for EHR data. Risk assessment methodology according to the ISO/IEC 27001 information security standard is described with examples on how it is applied to EHR systems.

Bridging informatics and implementation science: evaluating a framework to assess electronic health record implementations in community settings.

PubMed

Richardson, Joshua E; Abramson, Erika L; Pfoh, Elizabeth R; Kaushal, Rainu

2012-01-01

Effective electronic health record (EHR) implementations in community settings are critical to promoting safe and reliable EHR use as well as mitigating provider dissatisfaction that often results. The implementation challenge is compounded given the scale and scope of EHR installations that are occurring and will continue to occur over the next five years. However, when compared to EHR evaluations relatively few biomedical informatics researchers have published on evaluating EHR implementations. Fewer still have evaluated EHR implementations in community settings. We report on the methods we used to achieve a novel application of an implementation science framework in informatics to qualitatively evaluate community-based EHR implementations. We briefly provide an overview of the implementation science framework, our methods for adapting it to informatics, the effects the framework had on our qualitative methods of inquiry and analysis, and discuss its potential value for informatics research.

Electronic Health Record Use a Bitter Pill for Many Physicians

PubMed Central

Meigs, Stephen L.; Solomon, Michael

2016-01-01

Electronic health record (EHR) adoption among office-based physician practices in the United States has increased significantly in the past decade. However, the challenges of using EHRs have resulted in growing dissatisfaction with the systems among many of these physicians. The purpose of this qualitative multiple-case study was to increase understanding of physician perceptions regarding the value of using EHR technology. Important findings included the belief among physicians that EHR systems need to be more user-friendly and adaptable to individual clinic workflow preferences, physician beliefs that lack of interoperability among EHRs is a major barrier to meaningful use of the systems, and physician beliefs that EHR use does not improve the quality of care provided to patients. These findings suggest that although government initiatives to encourage EHR adoption among office-based physician practices have produced positive results, additional support may be required in the future to maintain this momentum. PMID:26903782

Satisfaction of health-care providers with electronic health records and perceived barriers to its implementation in the United Arab Emirates.

PubMed

Bani-Issa, Wegdan; Al Yateem, Nabeel; Al Makhzoomy, Ibtihal Khalaf; Ibrahim, Ali

2016-08-01

The integration of electronic health records (EHRs) has shown promise in improving health-care quality. In the United Arab Emirates, EHRs have been recently adopted to improve the quality and safety of patient care. A cross-sectional survey of 680 health-care providers (HCPs) was conducted to assess the satisfaction of HCPs in the United Arab Emirates with EHRs' impact on access/viewing, documentation and medication administration and to explore the barriers encountered in their use. Data were collected over 6 months from April to September 2014. High overall satisfaction with EHRs was reported by HCPs, suggesting their acceptance. Physicians reported the greatest overall satisfaction with EHRs, although nurses showed significantly higher satisfaction with the impact on medication administration compared with other HCPs. The most significant barriers reported by nurses were lack of belief in the value of EHRs for patients and lack of adequate computer skills. Given the large investment in technology, additional research is necessary to promote the full utilization of EHRs. Nurses need to be aware of the value of EHRs for patient care and be involved in all stages of EHR implementations to maximize its meaningful use for better clinical outcomes. © 2016 John Wiley & Sons Australia, Ltd.

Implementations of the HL7 Context-Aware Knowledge Retrieval (“Infobutton”) Standard: Challenges, Strengths, Limitations, and Uptake

PubMed Central

Del Fiol, Guilherme; Huser, Vojtech; Strasberg, Howard R; Maviglia, Saverio M; Curtis, Clayton; Cimino, James J

2012-01-01

To support clinical decision-making,computerized information retrieval tools known as “infobuttons” deliver contextually-relevant knowledge resources intoclinical information systems.The Health Level Seven International(HL7)Context-Aware Knowledge Retrieval (Infobutton) Standard specifies a standard mechanism to enable infobuttons on a large scale. Objective To examine the experience of organizations in the course of implementing the HL7 Infobutton Standard. Method Cross-sectionalonline survey and in-depth phone interviews. Results A total of 17 organizations participated in the study.Analysis of the in-depth interviews revealed 20 recurrent themes.Implementers underscored the benefits, simplicity, and flexibility of the HL7 Infobutton Standard. Yet, participants voiced the need for easier access to standard specifications and improved guidance to beginners. Implementers predicted that the Infobutton Standard will be widely or at least fairly well adopted in the next five years, but uptake will dependlargely on adoption among electronic health record (EHR) vendors. To accelerate EHR adoption of the Infobutton Standard,implementers recommended HL7-compliant infobutton capabilities to be included in the United States Meaningful Use Certification Criteria EHR systems. Limitations Opinions and predictions should be interpreted with caution, since all the participant organizations have successfully implemented the Standard and overhalf of the organizations were actively engaged in the development of the Standard. Conclusion Overall, implementers reported a very positive experience with the HL7 Infobutton Standard.Despite indications of increasing uptake, measures should be taken to stimulate adoption of the Infobutton Standard among EHR vendors. Widespread adoption of the Infobutton standard has the potential to bring contextually relevant clinical decision support content into the healthcare provider workflow. PMID:22226933

Developing Teaching Strategies in the EHR Era: A Survey of GME Experts.

PubMed

Atwater, Amber R; Rudd, Mariah; Brown, Audrey; Wiener, John S; Benjamin, Robert; Lee, W Robert; Rosdahl, Jullia A

2016-10-01

There is limited information on the impact of widespread adoption of the electronic health record (EHR) on graduate medical education (GME). To identify areas of consensus by education experts, where the use of EHR impacts GME, with the goal of developing strategies and tools to enhance GME teaching and learning in the EHR environment. Information was solicited from experienced US physician educators who use EPIC EHR following 3 steps: 2 rounds of online surveys using the Delphi technique, followed by telephone interviews. The survey contained 3 stem questions and 52 items with Likert-scale responses. Consensus was defined by predetermined cutoffs. A second survey reassessed items for which consensus was not initially achieved. Common themes to improve GME in settings with an EHR were compiled from the telephone interviews. The panel included 19 physicians in 15 states in Round 1, 12 in Round 2, and 10 for the interviews. Ten items were found important for teaching and learning: balancing focus on EHR documentation with patient engagement achieved 100% consensus. Other items achieving consensus included adequate learning time, balancing EHR data with verbal history and physical examination, communicating clinical thought processes, hands-on EHR practice, minimizing data repetition, and development of shortcuts and templates. Teaching strategies incorporating both online software and face-to-face solutions were identified during the interviews. New strategies are needed for effective teaching and learning of residents and fellows, capitalizing on the potential of the EHR, while minimizing any unintended negative impact on medical education.

EHR adoption among doctors who treat the elderly.

PubMed

Yeager, Valerie A; Menachemi, Nir; Brooks, Robert G

2010-12-01

The purpose of this study is to examine Electronic Health Record (EHR) adoption among Florida doctors who treat the elderly. This analysis contributes to the EHR adoption literature by determining if doctors who disproportionately treat the elderly differ from their counterparts with respect to the utilization of an important quality-enhancing health information technology application. This study is based on a primary survey of a large, statewide sample of doctors practising in outpatient settings in Florida. Logistic regression analysis was used to determine whether doctors who treat a high volume of elderly (HVE) patients were different with respect to EHR adoption. Our analyses included responses from 1724 doctors. In multivariate analyses controlling for doctor age, training, computer sophistication, practice size and practice setting, HVE doctors were significantly less likely to adopt EHR. Specifically, compared with their counterparts, HVE doctors were observed to be 26.7% less likely to be utilizing an EHR system (OR=0.733, 95% CI 0.547-0.982). We also found that doctor age is negatively related to EHR adoption, and practice size and doctor computer savvy-ness is positively associated. Despite the fact that EHR adoption has improved in recent years, doctors in Florida who serve the elderly are less likely to adopt EHRs. As long as HVE doctors are adopting EHR systems at slower rates, the elderly patients treated by these doctors will be at a disadvantage with respect to potential benefits offered by this technology. © 2010 Blackwell Publishing Ltd.

EHRs in primary care practices: benefits, challenges, and successful strategies.

PubMed

Goetz Goldberg, Debora; Kuzel, Anton J; Feng, Lisa Bo; DeShazo, Jonathan P; Love, Linda E

2012-02-01

To understand the current use of electronic health records (EHRs) in small primary care practices and to explore experiences and perceptions of physicians and staff toward the benefits, challenges, and successful strategies for implementation and meaningful use of advanced EHR functions. Qualitative case study of 6 primary care practices in Virginia. We performed surveys and in-depth interviews with clinicians and administrative staff (N = 38) and observed interpersonal relations and use of EHR functions over a 16-month period. Practices with an established EHR were selected based on a maximum variation of quality activities, location, and ownership. Physicians and staff report increased efficiency in retrieving medical records, storing patient information, coordination of care, and office operations. Costs, lack of knowledge of EHR functions, and problems transforming office operations were barriers reported for meaningful use of EHRs. Major disruption to patient care during upgrades and difficulty utilizing performance tracking and quality functions were also reported. Facilitators for adopting and using advanced EHR functions include team-based care, adequate technical support, communication and training for employees and physicians, alternative strategies for patient care during transition, and development of new processes and work flow procedures. Small practices experience difficulty with implementation and utilization of advanced EHR functions. Federal and state policies should continue to support practices by providing technical assistance and financial incentives, grants, and/or loans. Small practices should consider using regional extension center services and reaching out to colleagues and other healthcare organizations with similar EHR systems for advice and guidance.

Privacy and Access Control for IHE-Based Systems

NASA Astrophysics Data System (ADS)

Katt, Basel; Breu, Ruth; Hafner, Micahel; Schabetsberger, Thomas; Mair, Richard; Wozak, Florian

Electronic Health Record (EHR) is the heart element of any e-health system, which aims at improving the quality and efficiency of healthcare through the use of information and communication technologies. The sensitivity of the data contained in the health record poses a great challenge to security. In this paper we propose a security architecture for EHR systems that are conform with IHE profiles. In this architecture we are tackling the problems of access control and privacy. Furthermore, a prototypical implementation of the proposed model is presented.

The Benefits and Challenges of an Interfaced Electronic Health Record and Laboratory Information System: Effects on Laboratory Processes.

PubMed

Petrides, Athena K; Bixho, Ida; Goonan, Ellen M; Bates, David W; Shaykevich, Shimon; Lipsitz, Stuart R; Landman, Adam B; Tanasijevic, Milenko J; Melanson, Stacy E F

2017-03-01

- A recent government regulation incentivizes implementation of an electronic health record (EHR) with computerized order entry and structured results display. Many institutions have also chosen to interface their EHR with their laboratory information system (LIS). - To determine the impact of an interfaced EHR-LIS on laboratory processes. - We analyzed several different processes before and after implementation of an interfaced EHR-LIS: the turnaround time, the number of stat specimens received, venipunctures per patient per day, preanalytic errors in phlebotomy, the number of add-on tests using a new electronic process, and the number of wrong test codes ordered. Data were gathered through the LIS and/or EHR. - The turnaround time for potassium and hematocrit decreased significantly (P = .047 and P = .004, respectively). The number of stat orders also decreased significantly, from 40% to 7% for potassium and hematocrit, respectively (P < .001 for both). Even though the average number of inpatient venipunctures per day increased from 1.38 to 1.62 (P < .001), the average number of preanalytic errors per month decreased from 2.24 to 0.16 per 1000 specimens (P < .001). Overall there was a 16% increase in add-on tests. The number of wrong test codes ordered was high and it was challenging for providers to correctly order some common tests. - An interfaced EHR-LIS significantly improved within-laboratory turnaround time and decreased stat requests and preanalytic phlebotomy errors. Despite increasing the number of add-on requests, an electronic add-on process increased efficiency and improved provider satisfaction. Laboratories implementing an interfaced EHR-LIS should be cautious of its effects on test ordering and patient venipunctures per day.

Distributed clinical data sharing via dynamic access-control policy transformation.

PubMed

Rezaeibagha, Fatemeh; Mu, Yi

2016-05-01

Data sharing in electronic health record (EHR) systems is important for improving the quality of healthcare delivery. Data sharing, however, has raised some security and privacy concerns because healthcare data could be potentially accessible by a variety of users, which could lead to privacy exposure of patients. Without addressing this issue, large-scale adoption and sharing of EHR data are impractical. The traditional solution to the problem is via encryption. Although encryption can be applied to access control, it is not applicable for complex EHR systems that require multiple domains (e.g. public and private clouds) with various access requirements. This study was carried out to address the security and privacy issues of EHR data sharing with our novel access-control mechanism, which captures the scenario of the hybrid clouds and need of access-control policy transformation, to provide secure and privacy-preserving data sharing among different healthcare enterprises. We introduce an access-control mechanism with some cryptographic building blocks and present a novel approach for secure EHR data sharing and access-control policy transformation in EHR systems for hybrid clouds. We propose a useful data sharing system for healthcare providers to handle various EHR users who have various access privileges in different cloud environments. A systematic study has been conducted on data sharing in EHR systems to provide a solution to the security and privacy issues. In conclusion, we introduce an access-control method for privacy protection of EHRs and EHR policy transformation that allows an EHR access-control policy to be transformed from a private cloud to a public cloud. This method has never been studied previously in the literature. Furthermore, we provide a protocol to demonstrate policy transformation as an application scenario. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Rate of electronic health record adoption in South Korea: A nation-wide survey.

PubMed

Kim, Young-Gun; Jung, Kyoungwon; Park, Young-Taek; Shin, Dahye; Cho, Soo Yeon; Yoon, Dukyong; Park, Rae Woong

2017-05-01

The adoption rate of electronic health record (EHR) systems in South Korea has continuously increased. However, in contrast to the situation in the United States (US), where there has been a national effort to improve and standardize EHR interoperability, no consensus has been established in South Korea. The goal of this study was to determine the current status of EHR adoption in South Korean hospitals compared to that in the US. All general and tertiary teaching hospitals in South Korea were surveyed regarding their EHR status in 2015 with the same questionnaire as used previously. The survey form estimated the level of adoption of EHR systems according to 24 core functions in four categories (clinical documentation, result view, computerized provider order entry, and decision supports). The adoption level was classified into comprehensive and basic EHR systems according to their functionalities. EHRs and computerized physician order entry systems were used in 58.1% and 86.0% of South Korean hospitals, respectively. Decision support systems and problem list documentation were the functions most frequently missing from comprehensive and basic EHR systems. The main barriers cited to adoption of EHR systems were the cost of purchasing (48%) and the ongoing cost of maintenance (11%). The EHR adoption rate in Korean hospitals (37.2%) was higher than that in US hospitals in 2010 (15.1%), but this trend was reversed in 2015 (58.1% vs. 75.2%). The evidence suggests that these trends were influenced by the level of financial and political support provided to US hospitals after the HITECH Act was passed in 2009. The EHR adoption rate in Korea has increased, albeit more slowly than in the US. It is logical to suggest that increased funding and support tied to the HITECH Act in the US partly explains the difference in the adoption rates of EHRs in both countries. Copyright © 2017 Elsevier B.V. All rights reserved.

Implementing a Social Knowledge Networking (SKN) system to enable meaningful use of an EHR medication reconciliation system.

PubMed

Rangachari, Pavani

2018-01-01

Despite the regulatory impetus toward meaningful use of electronic health record (EHR) Medication Reconciliation (MedRec) to prevent medication errors during care transitions, hospital adherence has lagged for one chief reason: low physician engagement, stemming from lack of consensus about which physician is responsible for managing a patient's medication list. In October 2016, Augusta University received a 2-year grant from the Agency for Healthcare Research and Quality to implement a Social Knowledge Networking (SKN) system for enabling its health system (AU Health) to progress from "limited use" of EHR MedRec technology to "meaningful use." The hypothesis is that SKN would bring together a diverse group of practitioners, to facilitate tacit knowledge exchange on issues related to EHR MedRec, which in turn is expected to increase practitioners' engagement in addressing those issues and enable meaningful use of EHR. The specific aims are to examine: 1) user-engagement in the SKN system, and 2) associations between "SKN use" and "meaningful use" of EHR. The 2-year project uses an exploratory mixed-method design and consists of three phases: 1) development; 2) SKN implementation; and 3) analysis. Phase 1, completed in May 2017, sought to identify a comprehensive set of issues related to EHR MedRec from practitioners directly involved in the MedRec process. This process facilitated development of a "Reporting Tool" on issues related to EHR MedRec, which, along with an existing "SKN/Discussion Tool," was integrated into the EHR at AU Health. Phase 2 (launched in June 2017) involves implementing the EHR-integrated SKN system over a 52-week period in inpatient and outpatient medicine units. The prospective implementation design is expected to generate context-sensitive strategies for meaningful use and successful implementation of EHR MedRec and thereby make substantial contributions to the patient safety and risk management literature. From a health care policy perspective, if the hypothesis holds, federal vendors could be encouraged to incorporate SKN features into EHR systems.

Impact of Homecare Electronic Health Record on Timeliness of Clinical Documentation, Reimbursement, and Patient Outcomes

PubMed Central

Bowles, K. H.; Adelsberger, M. C.; Chittams, J. L.; Liao, C.

2014-01-01

Summary Background Homecare is an important and effective way of managing chronic illnesses using skilled nursing care in the home. Unlike hospitals and ambulatory settings, clinicians visit patients at home at different times, independent of each other. Twenty-nine percent of 10,000 homecare agencies in the United States have adopted point-of-care EHRs. Yet, relatively little is known about the growing use of homecare EHRs. Objective Researchers compared workflow, financial billing, and patient outcomes before and after implementation to evaluate the impact of a homecare point-of-care EHR. Methods The design was a pre/post observational study embedded in a mixed methods study. The setting was a Philadelphia-based homecare agency with 137 clinicians. Data sources included: (1) clinician EHR documentation completion; (2) EHR usage data; (3) Medicare billing data; (4) an EHR Nurse Satisfaction survey; (5) clinician observations; (6) clinician interviews; and (7) patient outcomes. Results Clinicians were satisfied with documentation timeliness and team communication. Following EHR implementation, 90% of notes were completed within the 1-day compliance interval (n = 56,702) compared with 30% of notes completed within the 7-day compliance interval in the pre-implementation period (n = 14,563; OR 19, p <. 001). Productivity in the number of clinical notes documented post-implementation increased almost 10-fold compared to pre-implementation. Days to Medicare claims fell from 100 days pre-implementation to 30 days post-implementation, while the census rose. EHR implementation impact on patient outcomes was limited to some behavioral outcomes. Discussion Findings from this homecare EHR study indicated clinician EHR use enabled a sustained increase in productivity of note completion, as well as timeliness of documentation and billing for reimbursement with limited impact on improving patient outcomes. As EHR adoption increases to better meet the needs of the growing population of older people with chronic health conditions, these results can inform homecare EHR development and implementation. PMID:25024760

How to successfully select and implement electronic health records (EHR) in small ambulatory practice settings.

PubMed

Lorenzi, Nancy M; Kouroubali, Angelina; Detmer, Don E; Bloomrosen, Meryl

2009-02-23

Adoption of EHRs by U.S. ambulatory practices has been slow despite the perceived benefits of their use. Most evaluations of EHR implementations in the literature apply to large practice settings. While there are similarities relating to EHR implementation in large and small practice settings, the authors argue that scale is an important differentiator. Focusing on small ambulatory practices, this paper outlines the benefits and barriers to EHR use in this setting, and provides a "field guide" for these practices to facilitate successful EHR implementation. The benefits of EHRs in ambulatory practices include improved patient care and office efficiency, and potential financial benefits. Barriers to EHRs include costs; lack of standardization of EHR products and the design of vendor systems for large practice environments; resistance to change; initial difficulty of system use leading to productivity reduction; and perceived accrual of benefits to society and payers rather than providers. The authors stress the need for developing a flexible change management strategy when introducing EHRs that is relevant to the small practice environment; the strategy should acknowledge the importance of relationship management and the role of individual staff members in helping the entire staff to manage change. Practice staff must create an actionable vision outlining realistic goals for the implementation, and all staff must buy into the project. The authors detail the process of implementing EHRs through several stages: decision, selection, pre-implementation, implementation, and post-implementation. They stress the importance of identifying a champion to serve as an advocate of the value of EHRs and provide direction and encouragement for the project. Other key activities include assessing and redesigning workflow; understanding financial issues; conducting training that is well-timed and meets the needs of practice staff; and evaluating the implementation process. The EHR implementation experience depends on a variety of factors including the technology, training, leadership, the change management process, and the individual character of each ambulatory practice environment. Sound processes must support both technical and personnel-related organizational components. Additional research is needed to further refine recommendations for the small physician practice and the nuances of specific medical specialties.

Electronic Health Record Challenges, Workarounds, and Solutions Observed in Practices Integrating Behavioral Health and Primary Care.

PubMed

Cifuentes, Maribel; Davis, Melinda; Fernald, Doug; Gunn, Rose; Dickinson, Perry; Cohen, Deborah J

2015-01-01

This article describes the electronic health record (EHR)-related experiences of practices striving to integrate behavioral health and primary care using tailored, evidenced-based strategies from 2012 to 2014; and the challenges, workarounds and initial health information technology (HIT) solutions that emerged during implementation. This was an observational, cross-case comparative study of 11 diverse practices, including 8 primary care clinics and 3 community mental health centers focused on the implementation of integrated care. Practice characteristics (eg, practice ownership, federal designation, geographic area, provider composition, EHR system, and patient panel characteristics) were collected using a practice information survey and analyzed to report descriptive information. A multidisciplinary team used a grounded theory approach to analyze program documents, field notes from practice observation visits, online diaries, and semistructured interviews. Eight primary care practices used a single EHR and 3 practices used 2 different EHRs, 1 to document behavioral health and 1 to document primary care information. Practices experienced common challenges with their EHRs' capabilities to 1) document and track relevant behavioral health and physical health information, 2) support communication and coordination of care among integrated teams, and 3) exchange information with tablet devices and other EHRs. Practices developed workarounds in response to these challenges: double documentation and duplicate data entry, scanning and transporting documents, reliance on patient or clinician recall for inaccessible EHR information, and use of freestanding tracking systems. As practices gained experience with integration, they began to move beyond workarounds to more permanent HIT solutions ranging in complexity from customized EHR templates, EHR upgrades, and unified EHRs. Integrating behavioral health and primary care further burdens EHRs. Vendors, in cooperation with clinicians, should intentionally design EHR products that support integrated care delivery functions, such as data documentation and reporting to support tracking patients with emotional and behavioral problems over time and settings, integrated teams working from shared care plans, template-driven documentation for common behavioral health conditions such as depression, and improved registry functionality and interoperability. This work will require financial support and cooperative efforts among clinicians, EHR vendors, practice assistance organizations, regulators, standards setters, and workforce educators. © Copyright 2015 by the American Board of Family Medicine.

Reducing Parental Uncertainty Around Childhood Cancer: Implementation Decisions and Design Trade-Offs in Developing an Electronic Health Record-Linked Mobile App.

PubMed

Marsolo, Keith; Shuman, William; Nix, Jeremy; Morrison, Caroline F; Mullins, Larry L; Pai, Ahna Lh

2017-06-26

Parents of children newly diagnosed with cancer are confronted with multiple stressors that place them at risk for significant psychological distress. One strategy that has been shown to help reduce uncertainty is the provision of basic information; however, families of newly diagnosed cancer patients are often bombarded with educational material. Technology has the potential to help families manage their informational needs and move towards normalization. The aim of this study was to create a mobile app that pulls together data from both the electronic health record (EHR) and vetted external information resources to provide tailored information to parents of newly diagnosed children as one method to reduce the uncertainty around their child's illness. This app was developed to be used by families in a National Institutes of Health (NIH)-funded randomized controlled trial (RCT) aimed at decreasing uncertainty and the subsequent psychological distress. A 2-phase qualitative study was conducted to elicit the features and content of the mobile app based on the needs and experience of parents of children newly diagnosed with cancer and their providers. Example functions include the ability to view laboratory results, look up appointments, and to access educational material. Educational material was obtained from databases maintained by the National Cancer Institute (NCI) as well as from groups like the Children's Oncology Group (COG) and care teams within Cincinnati Children's Hospital Medical Center (CCHMC). The use of EHR-based Web services was explored to allow data like laboratory results to be retrieved in real-time. The ethnographic design process resulted in a framework that divided the content of the mobile app into the following 4 sections: (1) information about the patient's current treatment and other data from the EHR; (2) educational background material; (3) a calendar to view upcoming appointments at their medical center; and (4) a section where participants in the RCT document the study data. Integration with the NCI databases was straightforward; however, accessing the EHR Web services posed a challenge, though the roadblocks were not technical in nature. The lack of a formal, end-to-end institutional process for requesting Web service access and a mechanism to shepherd the request through all stages of implementation proved to be the biggest barrier. We successfully deployed a mobile app with a custom user interface that can integrate with the EHR to retrieve laboratory results and appointment information using vendor-provided Web services. Developers should expect to face hurdles when integrating with the EHR, but many of them can be addressed with frequent communication and thorough documentation. Executive sponsorship is also a key factor for success. ClinicalTrials.gov NCT02505165; https://clinicaltrials.gov/ct2/show/NCT02505165 (Archived by WebCite at http://www.Webcitation.org/6r9ZSUgoT). ©Keith Marsolo, William Shuman, Jeremy Nix, Caroline F Morrison, Larry L Mullins, Ahna LH Pai. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 26.06.2017.

Development of a Web-Based Registry to Support Diabetes Care in Free Medical Clinics

PubMed Central

McFadden, Norman; Daniel, Bryan; Hoyt, Robert; Snider, Dallas

2017-01-01

The United States has more than 1,000 free medical clinics. Because these clinics do not bill Medicare or Medicaid, they are not eligible for federal reimbursement for electronic health record (EHR) adoption. As a result, most do not have EHRs or electronic disease registries. A web-based diabetes registry was created with all open-source components for use in an urban free clinic to manage patients with type 2 diabetes and comorbidities. The registry was modeled after the Chronic Disease Electronic Management System and recommendations of the American Diabetes Association. The software was enhanced to include multiple other features, such as progress notes, so that it can function as a simple EHR. The configuration permits other free clinics to join securely, and the software can be shared. PMID:28566990

Electronic health record systems in ophthalmology: impact on clinical documentation.

PubMed

Sanders, David S; Lattin, Daniel J; Read-Brown, Sarah; Tu, Daniel C; Wilson, David J; Hwang, Thomas S; Morrison, John C; Yackel, Thomas R; Chiang, Michael F

2013-09-01

To evaluate quantitative and qualitative differences in documentation of the ophthalmic examination between paper and electronic health record (EHR) systems. Comparative case series. One hundred fifty consecutive pairs of matched paper and EHR notes, documented by 3 attending ophthalmologist providers. An academic ophthalmology department implemented an EHR system in 2006. Database queries were performed to identify cases in which the same problems were documented by the same provider on different dates, using paper versus EHR methods. This was done for 50 consecutive pairs of examinations in 3 different diseases: age-related macular degeneration (AMD), glaucoma, and pigmented choroidal lesions (PCLs). Quantitative measures were used to compare completeness of documenting the complete ophthalmologic examination, as well as disease-specific critical findings using paper versus an EHR system. Qualitative differences in paper versus EHR documentation were illustrated by selecting representative paired examples. (1) Documentation score, defined as the number of examination elements recorded for the slit-lamp examination, fundus examination, and complete ophthalmologic examination and for critical clinical findings for each disease. (2) Paired comparison of qualitative differences in paper versus EHR documentation. For all 3 diseases (AMD, glaucoma, PCL), the number of complete examination findings recorded was significantly lower with paper than the EHR system (P ≤ 0.004). Among the 3 individual examination sections (general, slit lamp, fundus) for the 3 diseases, 5 of the 9 possible combinations had significantly lower mean documentation scores with paper than EHR notes. For 2 of the 3 diseases, the number of critical clinical findings recorded was significantly lower using paper versus EHR notes (P ≤ 0.022). All (150/150) paper notes relied on graphical representations using annotated hand-drawn sketches, whereas no (0/150) EHR notes contained drawings. Instead, the EHR systems documented clinical findings using textual descriptions and interpretations. There were quantitative and qualitative differences in the nature of paper versus EHR documentation of ophthalmic findings in this study. The EHR notes included more complete documentation of examination elements using structured textual descriptions and interpretations, whereas paper notes used graphical representations of findings. The author(s) have no proprietary or commercial interest in any materials discussed in this article. Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

The Impact of Physician EHR Usage on Patient Satisfaction.

PubMed

Marmor, Rebecca A; Clay, Brian; Millen, Marlene; Savides, Thomas J; Longhurst, Christopher A

2018-01-01

The increased emphasis on patient satisfaction has coincided with the growing adoption of electronic health records (EHRs) throughout the U.S. The 2001 Institute of Medicine Report, “Crossing the Quality Chasm,” identified patient-centered care as a key element of quality health care.[1] In response to this call, the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey was developed to assess patients' health care experiences in the inpatient setting. Simultaneously, financial incentives have facilitated the rapid adoption of EHR applications, with 84% of hospitals maintaining at least a basic EHR in 2015 (a ninefold increase since 2008).[2] Despite the concurrent deployment of patient satisfaction surveys and EHRs, there is a poor understanding of the relationship that may exist between physician usage of the EHR and patient satisfaction. Most prior research into the impact of the EHR on physician–patient communication has been observational, describing the behaviors of physicians and patients when the clinician accesses an EHR in the exam room. Past research has shown that encounters where physicians access the EHR are often filled with long pauses,[3] and that few clinicians attempt to engage patients by sharing what they are looking at on the screen.[4] A recent meta-analysis reviewing 53 papers found that only 7 studies attempted to correlate objective observations of physician communication behaviors with patient perceptions by eliciting feedback from the patients.[5] No study used a standardized assessment tool of patient satisfaction. The authors conclude that additional work is necessary to better understand the patient perspective of the presence of an EHR during a clinical encounter. Additionally, increasing EHR adoption and emphasis on patient satisfaction have also corresponded with rising physician burnout rates.[6] [7] Prior work suggests that EHR adoption may be contributing to this trend.[8] Burnout from the EHR may be due in part to the significant amount of time physicians spend logged into systems, documenting long after clinic has ended in effort to avoid disrupting the patient–physician relationship.[9] We used existing data sources to describe the relationship between the amount of time physicians spend logged in to the EHR—both during daytime hours as well after clinic hours—and performance on a validated patient satisfaction survey. Our null hypothesis is that there is no relationship between increased time logged in to the EHR and patient satisfaction.

Strategic Deployment of Clinical Models.

PubMed

Goossen, William

2016-01-01

The selection, implementation, and certification of electronic health records (EHR) could benefit from the required use of one of the established clinical model approaches. For the lifelong record of data about individuals, issues arise about the permanence and preservation of data during or even beyond a lifetime. Current EHR do not fully adhere to pertinent standards for clinical data, where it is known for some 20 plus years that standardization of health data is a cornerstone for patient safety, interoperability, data retrieval for various purposes and the lifelong preservation of such data. This paper briefly introduces the issues and gives a brief recommendation for future work in this area.

Electronic health record in the internal medicine clinic of a Brazilian university hospital: Expectations and satisfaction of physicians and patients.

PubMed

Duarte, Jurandir Godoy; Azevedo, Raymundo Soares

2017-06-01

To evaluate the satisfaction and expectations of patients and physicians before and after the implementation of an electronic health record (EHR) in the outpatient clinic of a university hospital. We conducted 389 interviews with patients and 151 with physicians before and after the implementation of a commercial EHR at the internal medicine clinic of Hospital das Clínicas of the Faculty of Medicine of the University of São Paulo (HC-FMUSP), Brazil. The physicians were identified by their connection to the outpatient clinic and categorized by their years since graduation: residents and preceptors (with 10 years or less of graduation) or assistants (with more than 10 years of graduation). The answers to the questionnaire given by the physicians were classified as favorable or against the use of EHR, before and after the implementation of this system in this clinic, receiving 1 or 0 points, respectively. The sum of these points generated a multiple regression score to determine which factors contribute to the acceptance of EHR by physicians. We also did a third survey, after the EHR was routinely established in the outpatient clinic. The degree of patient satisfaction was the same before and after implementation, with more than 90% positive evaluations. They noted the use of the computer during the consultation and valued such use. Resident (younger) physicians had more positive expectations than assistants (older physicians) before EHR implementation. This optimism was reduced after implementation. In the third evaluation the use of EHR was higher among resident physicians. Resident physicians perceived and valued the EHR more and used it more. In 28 of the 57 questions on performance of clinical tasks, resident physicians found it easier to use EHR than assistant physicians with significant differences (p<0.05). When questioned specifically about EHR satisfaction, resident physicians responded "good" and "excellent" to a greater extent than assistant physicians (p=0.002). Our results reinforce the idea that the EHR introduction in a clinical setting should be preceded by careful planning to improve physician's adherence to the use of EHR. Patients do not seem to notice much difference to the quality of the consultation done using paper or EHR. It became clear after the third evaluation with the physicians that the younger (residents and some preceptors) perceived the advantages of the EHR more than the older physicians. Resident physicians use the EHR more and are more satisfied with it. Copyright © 2017 Elsevier B.V. All rights reserved.

Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach

PubMed Central

Jagannatha, Abhyuday N; Fodeh, Samah J; Yu, Hong

2017-01-01

Background Medical terms are a major obstacle for patients to comprehend their electronic health record (EHR) notes. Clinical natural language processing (NLP) systems that link EHR terms to lay terms or definitions allow patients to easily access helpful information when reading through their EHR notes, and have shown to improve patient EHR comprehension. However, high-quality lay language resources for EHR terms are very limited in the public domain. Because expanding and curating such a resource is a costly process, it is beneficial and even necessary to identify terms important for patient EHR comprehension first. Objective We aimed to develop an NLP system, called adapted distant supervision (ADS), to rank candidate terms mined from EHR corpora. We will give EHR terms ranked as high by ADS a higher priority for lay language annotation—that is, creating lay definitions for these terms. Methods Adapted distant supervision uses distant supervision from consumer health vocabulary and transfer learning to adapt itself to solve the problem of ranking EHR terms in the target domain. We investigated 2 state-of-the-art transfer learning algorithms (ie, feature space augmentation and supervised distant supervision) and designed 5 types of learning features, including distributed word representations learned from large EHR data for ADS. For evaluating ADS, we asked domain experts to annotate 6038 candidate terms as important or nonimportant for EHR comprehension. We then randomly divided these data into the target-domain training data (1000 examples) and the evaluation data (5038 examples). We compared ADS with 2 strong baselines, including standard supervised learning, on the evaluation data. Results The ADS system using feature space augmentation achieved the best average precision, 0.850, on the evaluation set when using 1000 target-domain training examples. The ADS system using supervised distant supervision achieved the best average precision, 0.819, on the evaluation set when using only 100 target-domain training examples. The 2 ADS systems both performed significantly better than the baseline systems (P<.001 for all measures and all conditions). Using a rich set of learning features contributed to ADS’s performance substantially. Conclusions ADS can effectively rank terms mined from EHRs. Transfer learning improved ADS’s performance even with a small number of target-domain training examples. EHR terms prioritized by ADS were used to expand a lay language resource that supports patient EHR comprehension. The top 10,000 EHR terms ranked by ADS are available upon request. PMID:29089288

Executing Medical Guidelines on the Web: Towards Next Generation Healthcare

NASA Astrophysics Data System (ADS)

Argüello, M.; Des, J.; Fernandez-Prieto, M. J.; Perez, R.; Paniagua, H.

There is still a lack of full integration between current Electronic Health Records (EHRs) and medical guidelines that encapsulate evidence-based medicine. Thus, general practitioners (GPs) and specialised physicians still have to read document-based medical guidelines and decide among various options for managing common non-life-threatening conditions where the selection of the most appropriate therapeutic option for each individual patient can be a difficult task. This paper presents a simulation framework and computational test-bed, called V.A.F. Framework, for supporting simulations of clinical situations that boosted the integration between Health Level Seven (HL7) and Semantic Web technologies (OWL, SWRL, and OWL-S) to achieve content layer interoperability between online clinical cases and medical guidelines, and therefore, it proves that higher integration between EHRs and evidence-based medicine can be accomplished which could lead to a next generation of healthcare systems that provide more support to physicians and increase patients' safety.

The State of Open Source Electronic Health Record Projects: A Software Anthropology Study.

PubMed

Alsaffar, Mona; Yellowlees, Peter; Odor, Alberto; Hogarth, Michael

2017-02-24

Electronic health records (EHR) are a key tool in managing and storing patients' information. Currently, there are over 50 open source EHR systems available. Functionality and usability are important factors for determining the success of any system. These factors are often a direct reflection of the domain knowledge and developers' motivations. However, few published studies have focused on the characteristics of free and open source software (F/OSS) EHR systems and none to date have discussed the motivation, knowledge background, and demographic characteristics of the developers involved in open source EHR projects. This study analyzed the characteristics of prevailing F/OSS EHR systems and aimed to provide an understanding of the motivation, knowledge background, and characteristics of the developers. This study identified F/OSS EHR projects on SourceForge and other websites from May to July 2014. Projects were classified and characterized by license type, downloads, programming languages, spoken languages, project age, development status, supporting materials, top downloads by country, and whether they were "certified" EHRs. Health care F/OSS developers were also surveyed using an online survey. At the time of the assessment, we uncovered 54 open source EHR projects, but only four of them had been successfully certified under the Office of the National Coordinator for Health Information Technology (ONC Health IT) Certification Program. In the majority of cases, the open source EHR software was downloaded by users in the United States (64.07%, 148,666/232,034), underscoring that there is a significant interest in EHR open source applications in the United States. A survey of EHR open source developers was conducted and a total of 103 developers responded to the online questionnaire. The majority of EHR F/OSS developers (65.3%, 66/101) are participating in F/OSS projects as part of a paid activity and only 25.7% (26/101) of EHR F/OSS developers are, or have been, health care providers in their careers. In addition, 45% (45/99) of developers do not work in the health care field. The research presented in this study highlights some challenges that may be hindering the future of health care F/OSS. A minority of developers have been health care professionals, and only 55% (54/99) work in the health care field. This undoubtedly limits the ability of functional design of F/OSS EHR systems from being a competitive advantage over prevailing commercial EHR systems. Open source software seems to be a significant interest to many; however, given that only four F/OSS EHR systems are ONC-certified, this interest is unlikely to yield significant adoption of these systems in the United States. Although the Health Information Technology for Economic and Clinical Health (HITECH) act was responsible for a substantial infusion of capital into the EHR marketplace, the lack of a corporate entity in most F/OSS EHR projects translates to a marginal capacity to market the respective F/OSS system and to navigate certification. This likely has further disadvantaged F/OSS EHR adoption in the United States. ©Mona Alsaffar, Peter Yellowlees, Alberto Odor, Michael Hogarth. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 24.02.2017.

Ten tips for successful electronic health records deployment.

PubMed

Gasch, Art

2012-01-01

As healthcare providers are increasingly compelled to adopt electronic health records (EHRs) and paper records migrate to electronic files provided to dozens of healthcare intermediaries, breeches of protected health information are skyrocketing, and so are dissatisfaction rates with EHR solutions. This article provides 10 practical tips to ensure a successful EHR system deployment an circumvent EHR land mines.

Taming the EHR (Electronic Health Record) - There is Hope

PubMed Central

DiAngi, YT; Longhurst, CA; Payne, TH

2016-01-01

With increasing diffusion of EHR technology over the last half decade, clinician burnout is rising. As healthcare is a complex and highly regulated field, the rapid and mass adoption of EHR technology has created disruption for highly skilled workers such as clinicians. Although, much has been written about dissatisfaction with the EHR (electronic health record), a paucity of immediate solutions exists in the literature. This article suggests three actionable steps health systems and clinicians can make to expedite gains from and mitigate the effect of the EHR on clinical practice. PMID:27830215

An e-consent-based shared EHR system architecture for integrated healthcare networks.

PubMed

Bergmann, Joachim; Bott, Oliver J; Pretschner, Dietrich P; Haux, Reinhold

2007-01-01

Virtual integration of distributed patient data promises advantages over a consolidated health record, but raises questions mainly about practicability and authorization concepts. Our work aims on specification and development of a virtual shared health record architecture using a patient-centred integration and authorization model. A literature survey summarizes considerations of current architectural approaches. Complemented by a methodical analysis in two regional settings, a formal architecture model was specified and implemented. Results presented in this paper are a survey of architectural approaches for shared health records and an architecture model for a virtual shared EHR, which combines a patient-centred integration policy with provider-oriented document management. An electronic consent system assures, that access to the shared record remains under control of the patient. A corresponding system prototype has been developed and is currently being introduced and evaluated in a regional setting. The proposed architecture is capable of partly replacing message-based communications. Operating highly available provider repositories for the virtual shared EHR requires advanced technology and probably means additional costs for care providers. Acceptance of the proposed architecture depends on transparently embedding document validation and digital signature into the work processes. The paradigm shift from paper-based messaging to a "pull model" needs further evaluation.

Rapid EHR development and implementation using web and cloud-based architecture in a large home health and hospice organization.

PubMed

Weaver, Charlotte A; Teenier, Pamela

2014-01-01

Health care organizations have long been limited to a small number of major vendors in their selection of an electronic health record (EHR) system in the national and international marketplace. These major EHR vendors have in common base systems that are decades old, are built in antiquated programming languages, use outdated server architecture, and are based on inflexible data models [1,2]. The option to upgrade their technology to keep pace with the power of new web-based architecture, programming tools and cloud servers is not easily undertaken due to large client bases, development costs and risk [3]. This paper presents the decade-long efforts of a large national provider of home health and hospice care to select an EHR product, failing that to build their own and failing that initiative to go back into the market in 2012. The decade time delay had allowed new technologies and more nimble vendors to enter the market. Partnering with a new start-up company doing web and cloud based architecture for the home health and hospice market, made it possible to build, test and implement an operational and point of care system in 264 home health locations across 40 states and three time zones in the United States. This option of "starting over" with the new web and cloud technologies may be posing a next generation of new EHR vendors that retells the Blackberry replacement by iPhone story in healthcare.

Transaction-neutral implanted data collection interface as EMR driver: a model for emerging distributed medical technologies.

PubMed

Lorence, Daniel; Sivaramakrishnan, Anusha; Richards, Michael

2010-08-01

Electronic Medical Record (EMR) and Electronic Health Record (EHR) adoption continues to lag across the US. Cost, inconsistent formats, and concerns about control of patient information are among the most common reasons for non-adoption in physician practice settings. The emergence of wearable and implanted mobile technologies, employed in distributed environments, promises a fundamentally different information infrastructure, which could serve to minimize existing adoption resistance. Proposed here is one technology model for overcoming adoption inconsistency and high organization-specific implementation costs, using seamless, patient controlled data collection. While the conceptual applications employed in this technology set are provided by way of illustration, they may also serve as a transformative model for emerging EMR/EHR requirements.

The next step towards making use meaningful: electronic information exchange and care coordination across clinicians and delivery sites.

PubMed

Graetz, Ilana; Reed, Mary; Shortell, Stephen M; Rundall, Thomas G; Bellows, Jim; Hsu, John

2014-12-01

Care for patients with chronic conditions often requires coordination between multiple physicians and delivery sites. Electronic Health Record (EHR) use could improve care quality and efficiency in part by facilitating care coordination. We examined the association between EHR use and clinician perceptions of care coordination for patients transferred across clinicians and delivery sites. Repeated surveys of primary care clinicians during the staggered implementation of an outpatient EHR (2005-2008), followed by an integrated inpatient EHR (2006-2010). We measured the association between EHR use stages (no use, outpatient EHR only, and integrated inpatient-outpatient EHR) and care coordination using logistic regression, adjusting for clinician characteristics, study year, and medical center. Adult primary care clinicians in a large Integrated Delivery System. Three measures of clinician-reported care coordination for patient care transferred across clinicians (eg, from specialist to primary care team) and across delivery sites (eg, from the hospital to outpatient care). Outpatient EHR use was associated with higher reports of access to complete and timely clinical information and higher agreement on clinician roles and responsibilities for patients transferred across clinicians, but not for patients transferred across delivery sites. Use of the integrated outpatient-inpatient EHR was associated with higher reports of access to timely and complete clinical information, clinician agreement on the patient's treatment plan for patients transferred across delivery sites, and with all coordination measures for patients transferred across clinicians. Use of an integrated EHR with health information exchange across delivery settings improved patient care coordination.

Strategizing EHR use to achieve patient-centered care in exam rooms: a qualitative study on primary care providers

PubMed Central

Zhang, Jing; Ashfaq, Shazia; Bell, Kristin; Calvitti, Alan; Farber, Neil J; Gabuzda, Mark T; Gray, Barbara; Liu, Lin; Rick, Steven; Street, Richard L; Zheng, Kai; Zuest, Danielle; Agha, Zia

2016-01-01

Objective Electronic health records (EHRs) have great potential to improve quality of care. However, their use may diminish “patient-centeredness” in exam rooms by distracting the healthcare provider from focusing on direct patient interaction. The authors conducted a qualitative interview study to understand the magnitude of this issue, and the strategies that primary care providers devised to mitigate the unintended adverse effect associated with EHR use. Methods and Materials Semi-structured interviews were conducted with 21 healthcare providers at 4 Veterans Affairs (VAs) outpatient primary care clinics in San Diego County. Data analysis was performed using the grounded theory approach. Results The results show that providers face demands from both patients and the EHR system. To cope with these demands, and to provide patient-centered care, providers attempt to perform EHR work outside of patient encounters and create templates to streamline documentation work. Providers also attempt to use the EHR to engage patients, establish patient buy-in for EHR use, and multitask between communicating with patients and using the EHR. Discussion and Conclusion This study has uncovered the challenges that primary care providers face in integrating the EHR into their work practice, and the strategies they use to overcome these challenges in order to maintain patient-centered care. These findings illuminate the importance of developing “best” practices to improve patient-centered care in today’s highly “wired” health environment. These findings also show that more user-centered EHR design is needed to improve system usability. PMID:26568605

Taxonomic and Life History Bias in Herbicide Resistant Weeds: Implications for Deployment of Resistant Crops

PubMed Central

Holt, Jodie S.; Welles, Shana R.; Silvera, Katia; Heap, Ian M.; Heredia, Sylvia M.; Martinez-Berdeja, Alejandra; Palenscar, Kai T.; Sweet, Lynn C.; Ellstrand, Norman C.

2013-01-01

Evolved herbicide resistance (EHR) is an important agronomic problem and consequently a food security problem, as it jeopardizes herbicide effectiveness and increases the difficulty and cost of weed management. EHR in weeds was first reported in 1970 and the number of cases has accelerated dramatically over the last two decades. Despite 40 years of research on EHR, why some weeds evolve resistance and others do not is poorly understood. Here we ask whether weed species that have EHR are different from weeds in general. Comparing taxonomic and life history traits of weeds with EHR to a control group (“the world's worst weeds”), we found weeds with EHR significantly over-represented in certain plant families and having certain life history biases. In particular, resistance is overrepresented in Amaranthaceae, Brassicaceae and Poaceae relative to all weeds, and annuality is ca. 1.5 times as frequent in weeds with EHR as in the control group. Also, for perennial EHR weeds, vegetative reproduction is only 60% as frequent as in the control group. We found the same trends for subsets of weeds with EHR to acetolactate synthase (ALS), photosystem II (PSII), and 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase-inhibitor herbicides and with multiple resistance. As herbicide resistant crops (transgenic or not) are increasingly deployed in developing countries, the problems of EHR could increase in those countries as it has in the USA if the selecting herbicides are heavily applied and appropriate management strategies are not employed. Given our analysis, we make some predictions about additional species that might evolve resistance. PMID:24039727

Electronic Health Record Impacts on Family Medicine Teachers: Survey of Third-Year Medical Student Clerkship Preceptors at an Academic Medical Center.

PubMed

Curry, Elizabeth; Oser, Tamara K; Oser, Sean M

2017-10-01

Electronic Health Record (EHR) use in clinical practice has accelerated in recent years. While several aspects of EHR use have been extensively studied, there is little data on EHR impacts on medical student educators, especially those involved in outpatient family medicine. This study evaluated perceived impacts of EHR use on clinician teachers of outpatient family medicine. The study used a mixed methods survey of clinicians who teach third-year medical students during the required family and community medicine outpatient clerkship at a Mid-Atlantic medical school. Among 50 completed surveys, most respondents reported that the EHR had impacted their teaching (70% reported at least one negative effect; 84% reported at least one positive effect). Positive impacts included more easily viewing information, more effectively teaching evidence-based medicine, and teaching about EHR use itself. Negative impacts included less time teaching or interacting with students, and a perception that EHR use impedes development of students' critical thinking and clinical integration skills. Providers who have taught medical students both with and without EHR in place (>P=.024), those over 50 years old (>P=.019), and those with at least 5 years teaching experience (>P=.006) were more likely to report negative impacts. Most preceptors reported that EHR use had both positive and negative impacts on their teaching of medical students, though the negative effects were perceived by respondents as more substantial, consistent with a theme of decreased enthusiasm for teaching due to EHR use. These findings can be used to help inform faculty development and education initiatives.

Taxonomic and life history bias in herbicide resistant weeds: implications for deployment of resistant crops.

PubMed

Holt, Jodie S; Welles, Shana R; Silvera, Katia; Heap, Ian M; Heredia, Sylvia M; Martinez-Berdeja, Alejandra; Palenscar, Kai T; Sweet, Lynn C; Ellstrand, Norman C

2013-01-01

Evolved herbicide resistance (EHR) is an important agronomic problem and consequently a food security problem, as it jeopardizes herbicide effectiveness and increases the difficulty and cost of weed management. EHR in weeds was first reported in 1970 and the number of cases has accelerated dramatically over the last two decades. Despite 40 years of research on EHR, why some weeds evolve resistance and others do not is poorly understood. Here we ask whether weed species that have EHR are different from weeds in general. Comparing taxonomic and life history traits of weeds with EHR to a control group ("the world's worst weeds"), we found weeds with EHR significantly over-represented in certain plant families and having certain life history biases. In particular, resistance is overrepresented in Amaranthaceae, Brassicaceae and Poaceae relative to all weeds, and annuality is ca. 1.5 times as frequent in weeds with EHR as in the control group. Also, for perennial EHR weeds, vegetative reproduction is only 60% as frequent as in the control group. We found the same trends for subsets of weeds with EHR to acetolactate synthase (ALS), photosystem II (PSII), and 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase-inhibitor herbicides and with multiple resistance. As herbicide resistant crops (transgenic or not) are increasingly deployed in developing countries, the problems of EHR could increase in those countries as it has in the USA if the selecting herbicides are heavily applied and appropriate management strategies are not employed. Given our analysis, we make some predictions about additional species that might evolve resistance.

Workarounds and Test Results Follow-up in Electronic Health Record-Based Primary Care

PubMed Central

Menon, Shailaja; Murphy, Daniel R.; Singh, Hardeep; Meyer, Ashley N. D.

2016-01-01

Summary Background Electronic health records (EHRs) have potential to facilitate reliable communication and follow-up of test results. However, limitations in EHR functionality remain, leading practitioners to use workarounds while managing test results. Workarounds can lead to patient safety concerns and signify indications as to how to build better EHR systems that meet provider needs. Objective To understand why primary care practitioners (PCPs) use workarounds to manage test results by analyzing data from a previously conducted national cross-sectional survey on test result management. Methods We conducted a secondary data analysis of quantitative and qualitative data from a national survey of PCPs practicing in the Department of Veterans Affairs (VA) and explored the use of workarounds in test results management. We used multivariate logistic regression analysis to examine the association between key sociotechnical factors that could affect test results follow-up (e.g., both technology-related and those unrelated to technology, such as organizational support for patient notification) and workaround use. We conducted a qualitative content analysis of free text survey data to examine reasons for use of workarounds. Results Of 2554 survey respondents, 1104 (43%) reported using workarounds related to test results management. Of these 1028 (93%) described the type of workaround they were using; 719 (70%) reported paper-based methods, while 230 (22%) used a combination of paper- and computer-based workarounds. Primary care practitioners who self-reported limited administrative support to help them notify patients of test results or described an instance where they personally (or a colleague) missed results, were more likely to use workarounds (p=0.02 and p=0.001, respectively). Qualitative analysis identified three main reasons for workaround use: 1) as a memory aid, 2) for improved efficiency and 3) for facilitating internal and external care coordination. Conclusion Workarounds to manage EHR-based test results are common, and their use results from unmet provider information management needs. Future EHRs and the respective work systems around them need to evolve to meet these needs. PMID:27437060

Funding alternatives in EHR adoption: beyond HITECH incentives and traditional approaches.

PubMed

Wang, Tiankai; Wang, Yangmei; Biedermann, Sue

2013-05-01

The meaningful use incentives under HITECH may be inadequate to address the financial challenges many hospitals face in implementing electronic health records (EHRs). Hospitals can fill the capital gap between EHR costs and available funds by exploring other potential funding sources. These sources include additional grants, funding permissible under EHR regulations, vendor financing, and tax benefits under IRS Section 179.

Electronic Health Records: Applying Diffusion of Innovation Theory to the Relationship between Multifactor Authentication and EHR Adoption

ERIC Educational Resources Information Center

Lockett, Daeron C.

2014-01-01

Electronic Health Record (EHR) systems are increasingly becoming accepted as future direction of medical record management systems. Programs such as the American Recovery and Reinvestment Act have provided incentives to hospitals that adopt EHR systems. In spite of these incentives, the perception of EHR adoption is that is has not achieved the…

The Pediatric Emergency Care Applied Research Network Registry: A Multicenter Electronic Health Record Registry of Pediatric Emergency Care.

PubMed

Deakyne Davies, Sara J; Grundmeier, Robert W; Campos, Diego A; Hayes, Katie L; Bell, Jamie; Alessandrini, Evaline A; Bajaj, Lalit; Chamberlain, James M; Gorelick, Marc H; Enriquez, Rene; Casper, T Charles; Scheid, Beth; Kittick, Marlena; Dean, J Michael; Alpern, Elizabeth R

2018-04-01

 Electronic health record (EHR)-based registries allow for robust data to be derived directly from the patient clinical record and can provide important information about processes of care delivery and patient health outcomes.  A data dictionary, and subsequent data model, were developed describing EHR data sources to include all processes of care within the emergency department (ED). ED visit data were deidentified and XML files were created and submitted to a central data coordinating center for inclusion in the registry. Automated data quality control occurred prior to submission through an application created for this project. Data quality reports were created for manual data quality review.  The Pediatric Emergency Care Applied Research Network (PECARN) Registry, representing four hospital systems and seven EDs, demonstrates that ED data from disparate health systems and EHR vendors can be harmonized for use in a single registry with a common data model. The current PECARN Registry represents data from 2,019,461 pediatric ED visits, 894,503 distinct patients, more than 12.5 million narrative reports, and 12,469,754 laboratory tests and continues to accrue data monthly.  The Registry is a robust harmonized clinical registry that includes data from diverse patients, sites, and EHR vendors derived via data extraction, deidentification, and secure submission to a central data coordinating center. The data provided may be used for benchmarking, clinical quality improvement, and comparative effectiveness research. Schattauer.

The readmission risk flag: using the electronic health record to automatically identify patients at risk for 30-day readmission.

PubMed

Baillie, Charles A; VanZandbergen, Christine; Tait, Gordon; Hanish, Asaf; Leas, Brian; French, Benjamin; Hanson, C William; Behta, Maryam; Umscheid, Craig A

2013-12-01

Identification of patients at high risk for readmission is a crucial step toward improving care and reducing readmissions. The adoption of electronic health records (EHR) may prove important to strategies designed to risk stratify patients and introduce targeted interventions. To develop and implement an automated prediction model integrated into our health system's EHR that identifies on admission patients at high risk for readmission within 30 days of discharge. Retrospective and prospective cohort. Healthcare system consisting of 3 hospitals. All adult patients admitted from August 2009 to September 2012. An automated readmission risk flag integrated into the EHR. Thirty-day all-cause and 7-day unplanned healthcare system readmissions. Using retrospective data, a single risk factor, ≥ 2 inpatient admissions in the past 12 months, was found to have the best balance of sensitivity (40%), positive predictive value (31%), and proportion of patients flagged (18%), with a C statistic of 0.62. Sensitivity (39%), positive predictive value (30%), proportion of patients flagged (18%), and C statistic (0.61) during the 12-month period after implementation of the risk flag were similar. There was no evidence for an effect of the intervention on 30-day all-cause and 7-day unplanned readmission rates in the 12-month period after implementation. An automated prediction model was effectively integrated into an existing EHR and identified patients on admission who were at risk for readmission within 30 days of discharge. © 2013 Society of Hospital Medicine.

Developing Analytical Inspection Criteria for Health IT Personnel with Minimum Training in Cognitive Ergonomics: A Practical Solution to EHR Improving EHR Usability

PubMed Central

Zhang, Zhen; Franklin, Amy; Walji, Muhammad; Zhang, Jiajie; Gong, Yang

2014-01-01

EHR usability has been identified as a major barrier to care quality optimization. One major challenge of improving EHR usability is the lack of systematic training in usability or cognitive ergonomics for EHR designers/developers in the vendor community and EHR analysts making significant configurations in healthcare organizations. A practical solution is to provide usability inspection tools that can be easily operationalized by EHR analysts. This project is aimed at developing a set of usability tools with demonstrated validity and reliability. We present a preliminary study of a metric for cognitive transparency and an exploratory experiment testing its validity in predicting the effectiveness of action-effect mapping. Despite the pilot nature of both, we found high sensitivity and specificity of the metric and higher response accuracy within a shorter time for users to determine action-effect mappings in transparent user interface controls. We plan to expand the sample size in our empirical study. PMID:25954439

Requirements for Workflow-Based EHR Systems - Results of a Qualitative Study.

PubMed

Schweitzer, Marco; Lasierra, Nelia; Hoerbst, Alexander

2016-01-01

Today's high quality healthcare delivery strongly relies on efficient electronic health records (EHR). These EHR systems or in general healthcare IT-systems are usually developed in a static manner according to a given workflow. Hence, they are not flexible enough to enable access to EHR data and to execute individual actions within a consultation. This paper reports on requirements pointed by experts in the domain of diabetes mellitus to design a system for supporting dynamic workflows to serve personalization within a medical activity. Requirements were collected by means of expert interviews. These interviews completed a conducted triangulation approach, aimed to gather requirements for workflow-based EHR interactions. The data from the interviews was analyzed through a qualitative approach resulting in a set of requirements enhancing EHR functionality from the user's perspective. Requirements were classified according to four different categorizations: (1) process-related requirements, (2) information needs, (3) required functions, (4) non-functional requirements. Workflow related requirements were identified which should be considered when developing and deploying EHR systems.

Development and evaluation of an electronic health record configuration and customization laboratory course for clinical informatics students.

PubMed

Mohan, Vishnu; Hersh, William R

2013-01-01

There is a need for informatics educational programs to develop laboratory courses that facilitate hands-on access to an EHR, and allow students to learn and evaluate functionality and configuration options. This is particularly relevant given the diversity of backgrounds of informatics students. We implemented an EHR laboratory course that allowed students to explore an EHR in both inpatient and outpatient clinical environments. The course focused on specific elements of the EHR including order set development, customization, clinical decision support, ancillary services, and billing and coding functionality. Students were surveyed at the end of the course for their satisfaction with the learning experience. We detailed challenges as well as lessons learned after analyzing student evaluations of this course. Features that promote the successful offering of an online EHR course, include (1) using more than one EHR to allow students to compare functionalities, (2) ensuring appropriate course calibration, (3) countering issues specific to EHR usability, and (4) fostering a fertile environment for rich online conversations are discussed.

Predicting all-cause risk of 30-day hospital readmission using artificial neural networks.

PubMed

Jamei, Mehdi; Nisnevich, Aleksandr; Wetchler, Everett; Sudat, Sylvia; Liu, Eric

2017-01-01

Avoidable hospital readmissions not only contribute to the high costs of healthcare in the US, but also have an impact on the quality of care for patients. Large scale adoption of Electronic Health Records (EHR) has created the opportunity to proactively identify patients with high risk of hospital readmission, and apply effective interventions to mitigate that risk. To that end, in the past, numerous machine-learning models have been employed to predict the risk of 30-day hospital readmission. However, the need for an accurate and real-time predictive model, suitable for hospital setting applications still exists. Here, using data from more than 300,000 hospital stays in California from Sutter Health's EHR system, we built and tested an artificial neural network (NN) model based on Google's TensorFlow library. Through comparison with other traditional and non-traditional models, we demonstrated that neural networks are great candidates to capture the complexity and interdependency of various data fields in EHRs. LACE, the current industry standard, showed a precision (PPV) of 0.20 in identifying high-risk patients in our database. In contrast, our NN model yielded a PPV of 0.24, which is a 20% improvement over LACE. Additionally, we discussed the predictive power of Social Determinants of Health (SDoH) data, and presented a simple cost analysis to assist hospitalists in implementing helpful and cost-effective post-discharge interventions.

Predicting all-cause risk of 30-day hospital readmission using artificial neural networks

PubMed Central

2017-01-01

Avoidable hospital readmissions not only contribute to the high costs of healthcare in the US, but also have an impact on the quality of care for patients. Large scale adoption of Electronic Health Records (EHR) has created the opportunity to proactively identify patients with high risk of hospital readmission, and apply effective interventions to mitigate that risk. To that end, in the past, numerous machine-learning models have been employed to predict the risk of 30-day hospital readmission. However, the need for an accurate and real-time predictive model, suitable for hospital setting applications still exists. Here, using data from more than 300,000 hospital stays in California from Sutter Health’s EHR system, we built and tested an artificial neural network (NN) model based on Google’s TensorFlow library. Through comparison with other traditional and non-traditional models, we demonstrated that neural networks are great candidates to capture the complexity and interdependency of various data fields in EHRs. LACE, the current industry standard, showed a precision (PPV) of 0.20 in identifying high-risk patients in our database. In contrast, our NN model yielded a PPV of 0.24, which is a 20% improvement over LACE. Additionally, we discussed the predictive power of Social Determinants of Health (SDoH) data, and presented a simple cost analysis to assist hospitalists in implementing helpful and cost-effective post-discharge interventions. PMID:28708848

Mapping communication spaces: The development and use of a tool for analyzing the impact of EHRs on interprofessional collaborative practice.

PubMed

Rashotte, Judy; Varpio, Lara; Day, Kathy; Kuziemsky, Craig; Parush, Avi; Elliott-Miller, Pat; King, James W; Roffey, Tyson

2016-09-01

Members of the healthcare team must access and share patient information to coordinate interprofessional collaborative practice (ICP). Although some evidence suggests that electronic health records (EHRs) contribute to in-team communication breakdowns, EHRs are still widely hailed as tools that support ICP. If EHRs are expected to promote ICP, researchers must be able to longitudinally study the impact of EHRs on ICP across communication types, users, and physical locations. This paper presents a data collection and analysis tool, named the Map of the Clinical Interprofessional Communication Spaces (MCICS), which supports examining how EHRs impact ICP over time, and across communication types, users, and physical locations. The tool's development evolved during a large prospective longitudinal study conducted at a Canadian pediatric academic tertiary-care hospital. This two-phased study [i.e., pre-implementation (phase 1) and post implementation (phase 2)] of an EHR employed a constructivist grounded theory approach and triangulated data collection strategies (i.e., non-participant observations, interviews, think-alouds, and document analysis). The MCICS was created through a five-step process: (i) preliminary structural development based on the use of the paper-based chart (phase 1); (ii) confirmatory review and modification process (phase 1); (iii) ongoing data collection and analysis facilitated by the map (phase 1); (iv) data collection and modification of map based on impact of EHR (phase 2); and (v) confirmatory review and modification process (phase 2). Creating and using the MCICS enabled our research team to locate, observe, and analyze the impact of the EHR on ICP, (a) across oral, electronic, and paper communications, (b) through a patient's passage across different units in the hospital, (c) across the duration of the patient's stay in hospital, and (d) across multiple healthcare providers. By using the MCICS, we captured a comprehensive, detailed picture of the clinical milieu in which the EHR was implemented, and of the intended and unintended consequences of the EHR's deployment. The map supported our observations and analysis of ICP communication spaces, and of the role of the patient chart in these spaces. If EHRs are expected to help resolve ICP challenges, it is important that researchers be able to longitudinally assess the impact of EHRs on ICP across multiple modes of communication, users, and physical locations. Mapping the clinical communication spaces can help EHR designers, clinicians, educators and researchers understand these spaces, appreciate their complexity, and navigate their way towards effective use of EHRs as means for supporting ICP. We propose that the MCICS can be used "as is" in other academic tertiary-care pediatric hospitals, and can be tailored for use in other healthcare institutions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach.

PubMed

Chen, Jinying; Jagannatha, Abhyuday N; Fodeh, Samah J; Yu, Hong

2017-10-31

Medical terms are a major obstacle for patients to comprehend their electronic health record (EHR) notes. Clinical natural language processing (NLP) systems that link EHR terms to lay terms or definitions allow patients to easily access helpful information when reading through their EHR notes, and have shown to improve patient EHR comprehension. However, high-quality lay language resources for EHR terms are very limited in the public domain. Because expanding and curating such a resource is a costly process, it is beneficial and even necessary to identify terms important for patient EHR comprehension first. We aimed to develop an NLP system, called adapted distant supervision (ADS), to rank candidate terms mined from EHR corpora. We will give EHR terms ranked as high by ADS a higher priority for lay language annotation-that is, creating lay definitions for these terms. Adapted distant supervision uses distant supervision from consumer health vocabulary and transfer learning to adapt itself to solve the problem of ranking EHR terms in the target domain. We investigated 2 state-of-the-art transfer learning algorithms (ie, feature space augmentation and supervised distant supervision) and designed 5 types of learning features, including distributed word representations learned from large EHR data for ADS. For evaluating ADS, we asked domain experts to annotate 6038 candidate terms as important or nonimportant for EHR comprehension. We then randomly divided these data into the target-domain training data (1000 examples) and the evaluation data (5038 examples). We compared ADS with 2 strong baselines, including standard supervised learning, on the evaluation data. The ADS system using feature space augmentation achieved the best average precision, 0.850, on the evaluation set when using 1000 target-domain training examples. The ADS system using supervised distant supervision achieved the best average precision, 0.819, on the evaluation set when using only 100 target-domain training examples. The 2 ADS systems both performed significantly better than the baseline systems (P<.001 for all measures and all conditions). Using a rich set of learning features contributed to ADS's performance substantially. ADS can effectively rank terms mined from EHRs. Transfer learning improved ADS's performance even with a small number of target-domain training examples. EHR terms prioritized by ADS were used to expand a lay language resource that supports patient EHR comprehension. The top 10,000 EHR terms ranked by ADS are available upon request. ©Jinying Chen, Abhyuday N Jagannatha, Samah J Fodeh, Hong Yu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 31.10.2017.

Development and evaluation of a de-identification procedure for a case register sourced from mental health electronic records.

PubMed

Fernandes, Andrea C; Cloete, Danielle; Broadbent, Matthew T M; Hayes, Richard D; Chang, Chin-Kuo; Jackson, Richard G; Roberts, Angus; Tsang, Jason; Soncul, Murat; Liebscher, Jennifer; Stewart, Robert; Callard, Felicity

2013-07-11

Electronic health records (EHRs) provide enormous potential for health research but also present data governance challenges. Ensuring de-identification is a pre-requisite for use of EHR data without prior consent. The South London and Maudsley NHS Trust (SLaM), one of the largest secondary mental healthcare providers in Europe, has developed, from its EHRs, a de-identified psychiatric case register, the Clinical Record Interactive Search (CRIS), for secondary research. We describe development, implementation and evaluation of a bespoke de-identification algorithm used to create the register. It is designed to create dictionaries using patient identifiers (PIs) entered into dedicated source fields and then identify, match and mask them (with ZZZZZ) when they appear in medical texts. We deemed this approach would be effective, given high coverage of PI in the dedicated fields and the effectiveness of the masking combined with elements of a security model. We conducted two separate performance tests i) to test performance of the algorithm in masking individual true PIs entered in dedicated fields and then found in text (using 500 patient notes) and ii) to compare the performance of the CRIS pattern matching algorithm with a machine learning algorithm, called the MITRE Identification Scrubber Toolkit - MIST (using 70 patient notes - 50 notes to train, 20 notes to test on). We also report any incidences of potential breaches, defined by occurrences of 3 or more true or apparent PIs in the same patient's notes (and in an additional set of longitudinal notes for 50 patients); and we consider the possibility of inferring information despite de-identification. True PIs were masked with 98.8% precision and 97.6% recall. As anticipated, potential PIs did appear, owing to misspellings entered within the EHRs. We found one potential breach. In a separate performance test, with a different set of notes, CRIS yielded 100% precision and 88.5% recall, while MIST yielded a 95.1% and 78.1%, respectively. We discuss how we overcome the realistic possibility - albeit of low probability - of potential breaches through implementation of the security model. CRIS is a de-identified psychiatric database sourced from EHRs, which protects patient anonymity and maximises data available for research. CRIS demonstrates the advantage of combining an effective de-identification algorithm with a carefully designed security model. The paper advances much needed discussion of EHR de-identification - particularly in relation to criteria to assess de-identification, and considering the contexts of de-identified research databases when assessing the risk of breaches of confidential patient information.

Public and physician's expectations and ethical concerns about electronic health record: Benefits outweigh risks except for information security.

PubMed

Entzeridou, Eleni; Markopoulou, Evgenia; Mollaki, Vasiliki

2018-02-01

Electronic Health Record systems (EHRs) offer numerous benefits in health care but also pose certain risks. As we progress toward the implementation of EHRs, a more in-depth understanding of attitudes that influence overall levels of EHR support is required. To record public and physicians' awareness, expectations for, and ethical concerns about the use of EHRs. A convenience sample was surveyed for both the public and physicians. The Public's Questionnaire was distributed to the public in a printed and an online version. The Physicians' Questionnaire was distributed to physicians in an online version. The questionnaires requested demographic characteristics followed by close-ended questions enquiring about awareness, perceived impact, perceived risks, and ethical issues raised by EHR use. In total, 46% of the public and 91% of physicians were aware of EHRs. Physicians' and public opinions were comparable concerning the positive impact of EHRs on better, more effective, and faster decisions on the patients' health, on better coordination between hospitals/clinics and on quality and reduced cost of health care. However, physicians were concerned that an EHR system would be a burden for their finances, for their time concerning training on the system, for their everyday workload and workflow. The majority of the public generally agreed that they would worry about the possibility that a non-authorized, third party might gain access to their personal health information (48.8%), and that they would worry about future discriminations due to possible disclosure of their health information (48.8%). Most physicians disagreed that EHRs will disrupt the doctor-patient relationship (58.1%) but they would worry about the safety of their patients' information (53.1%). Overall, both the public and physicians were in favor of the implementation of an EHR system, evaluating that possible benefits are more important than possible risks. The majority of the public believed that physicians should have full access to an EHR (90.9%), whereas nursing staff, pharmacists, laboratory staff, and other healthcare professional should have partial access. The factors identified in the present study present actionable insights that may increase awareness about EHRs. The survey illustrates that both the public and physicians acknowledge the benefits and support EHRs on the condition that sufficient guarantees are provided about privacy and security. Copyright © 2017 Elsevier B.V. All rights reserved.

Dealing with the archetypes development process for a regional EHR system.

PubMed

Santos, M R; Bax, M P; Kalra, D

2012-01-01

This paper aims to present the archetype modelling process used for the Health Department of Minas Gerais State, Brazil (SES/MG), to support building its regional EHR system, and the lessons learned during this process. This study was undertaken within the Minas Gerais project. The EHR system architecture was built assuming the reference model from the ISO 13606 norm. The whole archetype development process took about ten months, coordinated by a clinical team co-ordinated by three health professionals and one systems analyst from the SES/MG. They were supported by around 30 health professionals from the internal SES/MG areas, and 5 systems analysts from the PRODEMGE. Based on a bottom-up approach, the project team used technical interviews and brainstorming sessions to conduct the modelling process. The main steps of the archetype modelling process were identified and described, and 20 archetypes were created. -The set of principles established during the selection of PCS elements helped the clinical team to keep the focus in their objectives;-The initial focus on the archetype structural organization aspects was important;-The data elements identified were subjected to a rigorous analysis aimed at determining the most suitable clinical domain;-Levelling the concepts to accommodate them within the hierarchical levels in the reference model was definitely no easy task, and the use of a mind mapping tool facilitated the modelling process;-Part of the difficulty experienced by the clinical team was related to a view focused on the original forms previously used;-The use of worksheets facilitated the modelling process by health professionals;-It was important to have a health professional that knew about the domain tables and health classifications from the Brazilian Federal Government as member in the clinical team. The archetypes (referencing terminology, domain tables and term lists) provided a favorable condition for the use of a controlled vocabulary between the central repository and the EMR systems and, probably, will increase the chances of preserving the semantics from the knowledge domain. Finally, the reference model from the ISO 13606 norm, along with the archetypes, proved sufficient to meet the specificities for the creation of an EHR system for basic healthcare in a Brazilian state.

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit.

PubMed

Pendergrass, Sarah A; Verma, Shefali S; Holzinger, Emily R; Moore, Carrie B; Wallace, John; Dudek, Scott M; Huggins, Wayne; Kitchner, Terrie; Waudby, Carol; Berg, Richard; McCarty, Catherine A; Ritchie, Marylyn D

2013-01-01

Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, 2580 cataract cases and 1367 controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) Biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 529,431 single nucleotide polymorphisms (SNPs) with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using the Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 5 statistically significant models with an interaction term with p-value < 0.05, as well as an overall model with p-value < 0.05 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use; these environmental factors have been previously associated with the formation of cataracts. We found a total of 288 models that exhibit an interaction term with a p-value ≤ 1×10(-4) associated with cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.

Regional differences in population-based cancer survival between six prefectures in Japan: application of relative survival models with funnel plots.

PubMed

Ito, Yuri; Ioka, Akiko; Tsukuma, Hideaki; Ajiki, Wakiko; Sugimoto, Tomoyuki; Rachet, Bernard; Coleman, Michel P

2009-07-01

We used new methods to examine differences in population-based cancer survival between six prefectures in Japan, after adjustment for age and stage at diagnosis. We applied regression models for relative survival to data from population-based cancer registries covering each prefecture for patients diagnosed with stomach, lung, or breast cancer during 1993-1996. Funnel plots were used to display the excess hazard ratio (EHR) for each prefecture, defined as the excess hazard of death from each cancer within 5 years of diagnosis relative to the mean excess hazard (in excess of national background mortality by age and sex) in all six prefectures combined. The contribution of age and stage to the EHR in each prefecture was assessed from differences in deviance-based R(2) between the various models. No significant differences were seen between prefectures in 5-year survival from breast cancer. For cancers of the stomach and lung, EHR in Osaka prefecture were above the upper 95% control limits. For stomach cancer, the age- and stage-adjusted EHR in Osaka were 1.29 for men and 1.43 for women, compared with Fukui and Yamagata. Differences in the stage at diagnosis of stomach cancer appeared to explain most of this excess hazard (61.3% for men, 56.8% for women), whereas differences in age at diagnosis explained very little (0.8%, 1.3%). This approach offers the potential to quantify the impact of differences in stage at diagnosis on time trends and regional differences in cancer survival. It underlines the utility of population-based cancer registries for improving cancer control.

Desiderata for computable representations of electronic health records-driven phenotype algorithms.

PubMed

Mo, Huan; Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Jiang, Guoqian; Kiefer, Richard; Zhu, Qian; Xu, Jie; Montague, Enid; Carrell, David S; Lingren, Todd; Mentch, Frank D; Ni, Yizhao; Wehbe, Firas H; Peissig, Peggy L; Tromp, Gerard; Larson, Eric B; Chute, Christopher G; Pathak, Jyotishman; Denny, Joshua C; Speltz, Peter; Kho, Abel N; Jarvik, Gail P; Bejan, Cosmin A; Williams, Marc S; Borthwick, Kenneth; Kitchner, Terrie E; Roden, Dan M; Harris, Paul A

2015-11-01

Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM). A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms. We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility. A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Archetype relational mapping - a practical openEHR persistence solution.

PubMed

Wang, Li; Min, Lingtong; Wang, Rui; Lu, Xudong; Duan, Huilong

2015-11-05

One of the primary obstacles to the widespread adoption of openEHR methodology is the lack of practical persistence solutions for future-proof electronic health record (EHR) systems as described by the openEHR specifications. This paper presents an archetype relational mapping (ARM) persistence solution for the archetype-based EHR systems to support healthcare delivery in the clinical environment. First, the data requirements of the EHR systems are analysed and organized into archetype-friendly concepts. The Clinical Knowledge Manager (CKM) is queried for matching archetypes; when necessary, new archetypes are developed to reflect concepts that are not encompassed by existing archetypes. Next, a template is designed for each archetype to apply constraints related to the local EHR context. Finally, a set of rules is designed to map the archetypes to data tables and provide data persistence based on the relational database. A comparison study was conducted to investigate the differences among the conventional database of an EHR system from a tertiary Class A hospital in China, the generated ARM database, and the Node + Path database. Five data-retrieving tests were designed based on clinical workflow to retrieve exams and laboratory tests. Additionally, two patient-searching tests were designed to identify patients who satisfy certain criteria. The ARM database achieved better performance than the conventional database in three of the five data-retrieving tests, but was less efficient in the remaining two tests. The time difference of query executions conducted by the ARM database and the conventional database is less than 130 %. The ARM database was approximately 6-50 times more efficient than the conventional database in the patient-searching tests, while the Node + Path database requires far more time than the other two databases to execute both the data-retrieving and the patient-searching tests. The ARM approach is capable of generating relational databases using archetypes and templates for archetype-based EHR systems, thus successfully adapting to changes in data requirements. ARM performance is similar to that of conventionally-designed EHR systems, and can be applied in a practical clinical environment. System components such as ARM can greatly facilitate the adoption of openEHR architecture within EHR systems.

Implementing a Social Knowledge Networking (SKN) system to enable meaningful use of an EHR medication reconciliation system

PubMed Central

Rangachari, Pavani

2018-01-01

Background Despite the regulatory impetus toward meaningful use of electronic health record (EHR) Medication Reconciliation (MedRec) to prevent medication errors during care transitions, hospital adherence has lagged for one chief reason: low physician engagement, stemming from lack of consensus about which physician is responsible for managing a patient’s medication list. In October 2016, Augusta University received a 2-year grant from the Agency for Healthcare Research and Quality to implement a Social Knowledge Networking (SKN) system for enabling its health system (AU Health) to progress from “limited use” of EHR MedRec technology to “meaningful use.” The hypothesis is that SKN would bring together a diverse group of practitioners, to facilitate tacit knowledge exchange on issues related to EHR MedRec, which in turn is expected to increase practitioners’ engagement in addressing those issues and enable meaningful use of EHR. The specific aims are to examine: 1) user-engagement in the SKN system, and 2) associations between “SKN use” and “meaningful use” of EHR. Methods The 2-year project uses an exploratory mixed-method design and consists of three phases: 1) development; 2) SKN implementation; and 3) analysis. Phase 1, completed in May 2017, sought to identify a comprehensive set of issues related to EHR MedRec from practitioners directly involved in the MedRec process. This process facilitated development of a “Reporting Tool” on issues related to EHR MedRec, which, along with an existing “SKN/Discussion Tool,” was integrated into the EHR at AU Health. Phase 2 (launched in June 2017) involves implementing the EHR-integrated SKN system over a 52-week period in inpatient and outpatient medicine units. Discussion The prospective implementation design is expected to generate context-sensitive strategies for meaningful use and successful implementation of EHR MedRec and thereby make substantial contributions to the patient safety and risk management literature. From a health care policy perspective, if the hypothesis holds, federal vendors could be encouraged to incorporate SKN features into EHR systems. PMID:29618941

Impact of Electronic Health Records on Long-Term Care Facilities: Systematic Review

PubMed Central

Mileski, Michael; Vijaykumar, Alekhya Ganta; Viswanathan, Sneha Vishnampet; Suskandla, Ujwala; Chidambaram, Yazhini

2017-01-01

Background Long-term care (LTC) facilities are an important part of the health care industry, providing care to the fastest-growing group of the population. However, the adoption of electronic health records (EHRs) in LTC facilities lags behind other areas of the health care industry. One of the reasons for the lack of widespread adoption in the United States is that LTC facilities are not eligible for incentives under the Meaningful Use program. Implementation of an EHR system in an LTC facility can potentially enhance the quality of care, provided it is appropriately implemented, used, and maintained. Unfortunately, the lag in adoption of the EHR in LTC creates a paucity of literature on the benefits of EHR implementation in LTC facilities. Objective The objective of this systematic review was to identify the potential benefits of implementing an EHR system in LTC facilities. The study also aims to identify the common conditions and EHR features that received favorable remarks from providers and the discrepancies that needed improvement to build up momentum across LTC settings in adopting this technology. Methods The authors conducted a systematic search of PubMed, Cumulative Index of Nursing and Allied Health (CINAHL), and MEDLINE databases. Papers were analyzed by multiple referees to filter out studies not germane to our research objective. A final sample of 28 papers was selected to be included in the systematic review. Results Results of this systematic review conclude that EHRs show significant improvement in the management of documentation in LTC facilities and enhanced quality outcomes. Approximately 43% (12/28) of the papers reported a mixed impact of EHRs on the management of documentation, and 33% (9/28) of papers reported positive quality outcomes using EHRs. Surprisingly, very few papers demonstrated an impact on patient satisfaction, physician satisfaction, the length of stay, and productivity using EHRs. Conclusions Overall, implementation of EHRs has been found to be effective in the few LTC facilities that have implemented them. Implementation of EHRs in LTC facilities caused improved management of clinical documentation that enabled better decision making. PMID:28963091

Annual survey on the level and extent of usage of electronic health records in government-related hospitals in Eastern Province, Saudi Arabia.

PubMed

Bah, Sulaiman; Alharthi, Hana; El Mahalli, Azza Ali; Jabali, Abdelkaream; Al-Qahtani, Mona; Al-kahtani, Nouf

2011-01-01

This study aims to determine the level and extent of usage of electronic health records (EHRs) in government-related hospitals in Eastern Province, Saudi Arabia. Another aim is to develop a Web site to serve as a forum of exchange on the development of EHRs in Saudi Arabia. All government hospitals (n = 19) in the province were included. The information technology (IT) managers in those hospitals made up the target population. An online questionnaire was developed, and the IT managers in all 19 government hospitals were invited to participate in the survey. The responses from the online survey were downloaded and analyzed using descriptive statistics. Of the 19 hospitals, only three (15.8 percent) use EHRs. These hospitals were established in 1984, 1995, and 2005. All three of these hospitals have implemented the same EHR software and were using it successfully, and all three were using the three core features of laboratory, radiology, and pharmacy electronic modules. Some modules were present in the EHR system but were underutilized. Some of the main challenges faced by the IT managers in implementing EHRs in their hospitals were related to the uncooperative attitudes of some physicians and nurses toward EHRs. In fulfillment of the second aim of the study, a Web site, http://ehr2011.weebly.com, was developed to serve as a forum for exchange of information on the development of EHRs in Saudi Arabia. The government of Saudi Arabia has prioritized the development of eHealth (health information technology) and allocated committed funding for it during 2008-2011. During this period, some sectors of government made highly commendable efforts in developing eHealth services. Along these lines, we had hoped to see higher uptake of EHRs than the 15.8 percent found in this study. The rate of implementing EHRs in government hospitals should be accelerated. The aim should be on achieving some basic EHR functionality in these hospitals, and once this has been achieved, additional functionality can be pursued in stages.

A student-centred electronic health record system for clinical education.

PubMed

Elliott, Kristine; Judd, Terry; McColl, Geoff

2011-01-01

Electronic Health Record (EHR) systems are an increasingly important feature of the national healthcare system [1]. However, little research has investigated the impact this will have on medical students' learning. As part of an innovative technology platform for a new masters level program in medicine, we are developing a student-centred EHR system for clinical education. A prototype was trialed with medical students over several weeks during 2010. This paper reports on the findings of the trial, which had the overall aim of assisting our understanding of how trainee doctors might use an EHR system for learning and communication in a clinical setting. In primary care and hospital settings, EHR systems offer potential benefits to medical students' learning: Longitudinal tracking of clinical progress towards established learning objectives [2]; Capacity to search across a substantial body of records [3]; Integration with online medical databases [3]; Development of expertise in creating, accessing and managing high quality EHRs [4]. While concerns have been raised that EHR systems may alter the interaction between teachers and students [3], and may negatively influence physician-patient communication [6], there is general consensus that the EHR is changing the current practice environment and teaching practice needs to respond. Final year medical students on clinical placement at a large university teaching hospital were recruited for the trial. Following a four-week period of use, semi-structured interviews were conducted with 10 participants. Audio-recorded interviews were transcribed and data analysed for emerging themes. Study participants were also surveyed about the importance of EHR systems in general, their familiarity with them, and general perceptions of sharing patient records. Medical students in this pilot study identified a number of educational, practical and administrative advantages that the student-centred EHR system offered over their existing ad-hoc procedures for recording patient encounters. Findings from this preliminary study point to the need to introduce and instruct students' on the use of EHR systems from their earliest clinical encounters, and to closely integrate learning activities based on the EHR system with established learning objectives. Further research is required to evaluate the impact of student-centred EHR systems on learning outcomes.

A Decade of Experience in Creating and Maintaining Data Elements for Structured Clinical Documentation in EHRs

PubMed Central

Zhou, Li; Collins, Sarah; Morgan, Stephen J.; Zafar, Neelam; Gesner, Emily J.; Fehrenbach, Martin; Rocha, Roberto A.

2016-01-01

Structured clinical documentation is an important component of electronic health records (EHRs) and plays an important role in clinical care, administrative functions, and research activities. Clinical data elements serve as basic building blocks for composing the templates used for generating clinical documents (such as notes and forms). We present our experience in creating and maintaining data elements for three different EHRs (one home-grown and two commercial systems) across different clinical settings, using flowsheet data elements as examples in our case studies. We identified basic but important challenges (including naming convention, links to standard terminologies, and versioning and change management) and possible solutions to address them. We also discussed more complicated challenges regarding governance, documentation vs. structured data capture, pre-coordination vs. post-coordination, reference information models, as well as monitoring, communication and training. PMID:28269927

A platform for exploration into chaining of web services for clinical data transformation and reasoning.

PubMed

Maldonado, José Alberto; Marcos, Mar; Fernández-Breis, Jesualdo Tomás; Parcero, Estíbaliz; Boscá, Diego; Legaz-García, María Del Carmen; Martínez-Salvador, Begoña; Robles, Montserrat

2016-01-01

The heterogeneity of clinical data is a key problem in the sharing and reuse of Electronic Health Record (EHR) data. We approach this problem through the combined use of EHR standards and semantic web technologies, concretely by means of clinical data transformation applications that convert EHR data in proprietary format, first into clinical information models based on archetypes, and then into RDF/OWL extracts which can be used for automated reasoning. In this paper we describe a proof-of-concept platform to facilitate the (re)configuration of such clinical data transformation applications. The platform is built upon a number of web services dealing with transformations at different levels (such as normalization or abstraction), and relies on a collection of reusable mappings designed to solve specific transformation steps in a particular clinical domain. The platform has been used in the development of two different data transformation applications in the area of colorectal cancer.

Utilizing electronic health records to predict acute kidney injury risk and outcomes: workgroup statements from the 15(th) ADQI Consensus Conference.

PubMed

Sutherland, Scott M; Chawla, Lakhmir S; Kane-Gill, Sandra L; Hsu, Raymond K; Kramer, Andrew A; Goldstein, Stuart L; Kellum, John A; Ronco, Claudio; Bagshaw, Sean M

2016-01-01

The data contained within the electronic health record (EHR) is "big" from the standpoint of volume, velocity, and variety. These circumstances and the pervasive trend towards EHR adoption have sparked interest in applying big data predictive analytic techniques to EHR data. Acute kidney injury (AKI) is a condition well suited to prediction and risk forecasting; not only does the consensus definition for AKI allow temporal anchoring of events, but no treatments exist once AKI develops, underscoring the importance of early identification and prevention. The Acute Dialysis Quality Initiative (ADQI) convened a group of key opinion leaders and stakeholders to consider how best to approach AKI research and care in the "Big Data" era. This manuscript addresses the core elements of AKI risk prediction and outlines potential pathways and processes. We describe AKI prediction targets, feature selection, model development, and data display.

Identification of Patient Safety Risks Associated with Electronic Health Records: A Software Quality Perspective.

PubMed

Virginio, Luiz A; Ricarte, Ivan Luiz Marques

2015-01-01

Although Electronic Health Records (EHR) can offer benefits to the health care process, there is a growing body of evidence that these systems can also incur risks to patient safety when developed or used improperly. This work is a literature review to identify these risks from a software quality perspective. Therefore, the risks were classified based on the ISO/IEC 25010 software quality model. The risks identified were related mainly to the characteristics of "functional suitability" (i.e., software bugs) and "usability" (i.e., interface prone to user error). This work elucidates the fact that EHR quality problems can adversely affect patient safety, resulting in errors such as incorrect patient identification, incorrect calculation of medication dosages, and lack of access to patient data. Therefore, the risks presented here provide the basis for developers and EHR regulating bodies to pay attention to the quality aspects of these systems that can result in patient harm.

Technological and Organizational Context around Immunization Reporting and Interoperability in Minnesota

PubMed Central

Rajamani, Sripriya; Roche, Erin; Soderberg, Karen; Bieringer, Aaron

2014-01-01

Background: Immunization information systems (IIS) operate in an evolving health care landscape with technology changes driven by initiatives such as the Centers for Medicare and Medicaid Services EHR incentive program, promoting adoption and use of electronic health record (EHR) systems, including standards-based public health reporting. There is flux in organizational affiliations to support models such as accountable care organizations (ACO). These impact institutional structure of how reporting of immunizations occurs and the methods adopted. Objectives: To evaluate the technical and organizational characteristics of healthcare provider reporting of immunizations to public health in Minnesota and to assess the adoption of standardized codes, formats and transport. Methods: Data on organizations and reporting status was obtained from Minnesota IIS (Minnesota Immunization Information Connection: MIIC) by collating information from existing lists, specialized queries and review of annual reports. EHR adoption data of clinics was obtained in collaboration with informatics office supporting the Minnesota e-Health Initiative. These data from various sources were merged, checked for quality to create a current state assessment of immunization reporting and results validated with subject matter experts. Results: Standards-based reporting of immunizations to MIIC increased to 708 sites over the last 3 years. A growth in automated real-time reporting occurred in 2013 with 143 new sites adopting the method. Though the uptake of message standards (HL7) has increased, the adoption of current version of HL7 and web services transport remains low. The EHR landscape is dominated by a single vendor (used by 40% of clinics) in the state. There is trend towards centralized reporting of immunizations with an organizational unit reporting for many sites ranging from 4 to 140 sites. Conclusion: High EHR adoption in Minnesota, predominance of a vendor in the market, and centralized reporting models present opportunities for better interoperability and also adaptation of strategies to fit this landscape. It is essential for IIS managers to have a good understanding of their constituent landscape for technical assistance and program planning purposes. PMID:25598866

Comparison of electronic health record system functionalities to support the patient recruitment process in clinical trials.

PubMed

Schreiweis, Björn; Trinczek, Benjamin; Köpcke, Felix; Leusch, Thomas; Majeed, Raphael W; Wenk, Joachim; Bergh, Björn; Ohmann, Christian; Röhrig, Rainer; Dugas, Martin; Prokosch, Hans-Ulrich

2014-11-01

Reusing data from electronic health records for clinical and translational research and especially for patient recruitment has been tackled in a broader manner since about a decade. Most projects found in the literature however focus on standalone systems and proprietary implementations at one particular institution often for only one singular trial and no generic evaluation of EHR systems for their applicability to support the patient recruitment process does yet exist. Thus we sought to assess whether the current generation of EHR systems in Germany provides modules/tools, which can readily be applied for IT-supported patient recruitment scenarios. We first analysed the EHR portfolio implemented at German University Hospitals and then selected 5 sites with five different EHR implementations covering all major commercial systems applied in German University Hospitals. Further, major functionalities required for patient recruitment support have been defined and the five sample EHRs and their standard tools have been compared to the major functionalities. In our analysis of the site's hospital information system environments (with four commercial EHR systems and one self-developed system) we found that - even though no dedicated module for patient recruitment has been provided - most EHR products comprise generic tools such as workflow engines, querying capabilities, report generators and direct SQL-based database access which can be applied as query modules, screening lists and notification components for patient recruitment support. A major limitation of all current EHR products however is that they provide no dedicated data structures and functionalities for implementing and maintaining a local trial registry. At the five sites with standard EHR tools the typical functionalities of the patient recruitment process could be mostly implemented. However, no EHR component is yet directly dedicated to support research requirements such as patient recruitment. We recommend for future developments that EHR customers and vendors focus much more on the provision of dedicated patient recruitment modules. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Provider responses to patients controlling access to their electronic health records: a prospective cohort study in primary care.

PubMed

Tierney, William M; Alpert, Sheri A; Byrket, Amy; Caine, Kelly; Leventhal, Jeremy C; Meslin, Eric M; Schwartz, Peter H

2015-01-01

Applying Fair Information Practice principles to electronic health records (EHRs) requires allowing patient control over who views their data. We designed a program that captures patients' preferences for provider access to an urban health system's EHR. Patients could allow or restrict providers' access to all data (diagnoses, medications, test results, reports, etc.) or only highly sensitive data (sexually transmitted infections, HIV/AIDS, drugs/alcohol, mental or reproductive health). Except for information in free-text reports, we redacted EHR data shown to providers according to patients' preferences. Providers could "break the glass" to display redacted information. We prospectively studied this system in one primary care clinic, noting redactions and when users "broke the glass," and surveyed providers about their experiences and opinions. Eight of nine eligible clinic physicians and all 23 clinic staff participated. All 105 patients who enrolled completed the preference program. Providers did not know which of their patients were enrolled, nor their preferences for accessing their EHRs. During the 6-month prospective study, 92 study patients (88 %) returned 261 times, during which providers viewed their EHRs 126 times (48 %). Providers "broke the glass" 102 times, 92 times for patients not in the study and ten times for six returning study patients, all of whom had restricted EHR access. Providers "broke the glass" for six (14 %) of 43 returning study patients with redacted data vs. zero among 49 study patients without redactions (p = 0.01). Although 54 % of providers agreed that patients should have control over who sees their EHR information, 58 % believed restricting EHR access could harm provider-patient relationships and 71 % felt quality of care would suffer. Patients frequently preferred restricting provider access to their EHRs. Providers infrequently overrode patients' preferences to view hidden data. Providers believed that restricting EHR access would adversely impact patient care. Applying Fair Information Practice principles to EHRs will require balancing patient preferences, providers' needs, and health care quality.

Missing clinical and behavioral health data in a large electronic health record (EHR) system.

PubMed

Madden, Jeanne M; Lakoma, Matthew D; Rusinak, Donna; Lu, Christine Y; Soumerai, Stephen B

2016-11-01

Recent massive investment in electronic health records (EHRs) was predicated on the assumption of improved patient safety, research capacity, and cost savings. However, most US health systems and health records are fragmented and do not share patient information. Our study compared information available in a typical EHR with more complete data from insurance claims, focusing on diagnoses, visits, and hospital care for depression and bipolar disorder. We included insurance plan members aged 12 and over, assigned throughout 2009 to a large multispecialty medical practice in Massachusetts, with diagnoses of depression (N = 5140) or bipolar disorder (N = 462). We extracted insurance claims and EHR data from the primary care site and compared diagnoses of interest, outpatient visits, and acute hospital events (overall and behavioral) between the 2 sources. Patients with depression and bipolar disorder, respectively, averaged 8.4 and 14.0 days of outpatient behavioral care per year; 60% and 54% of these, respectively, were missing from the EHR because they occurred offsite. Total outpatient care days were 20.5 for those with depression and 25.0 for those with bipolar disorder, with 45% and 46% missing, respectively, from the EHR. The EHR missed 89% of acute psychiatric services. Study diagnoses were missing from the EHR's structured event data for 27.3% and 27.7% of patients. EHRs inadequately capture mental health diagnoses, visits, specialty care, hospitalizations, and medications. Missing clinical information raises concerns about medical errors and research integrity. Given the fragmentation of health care and poor EHR interoperability, information exchange, and usability, priorities for further investment in health IT will need thoughtful reconsideration. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Readiness of the Belgian network of sentinel general practitioners to deliver electronic health record data for surveillance purposes: results of survey study.

PubMed

Boffin, Nicole; Bossuyt, Nathalie; Vanthomme, Katrien; Van Casteren, Viviane

2010-06-25

In order to proceed from a paper based registration to a surveillance system that is based on extraction of electronic health records (EHR), knowledge is needed on the number and representativeness of sentinel GPs using a government-certified EHR system and the quality of EHR data for research, expressed in the compliance rate with three criteria: recording of home visits, use of prescription module and diagnostic subject headings. Data were collected by annual postal surveys between 2005 and 2009 among all sentinel GPs. We tested relations between four key GP characteristics (age, gender, language community, practice organisation) and use of a certified EHR system by multivariable logistic regression. The relation between EHR software package, GP characteristics and compliance with three quality criteria was equally measured by multivariable logistic regression. A response rate of 99% was obtained. Of 221 sentinel GPs, 55% participated in the surveillance without interruption from 2005 onwards, i.e. all five years, and 78% were participants in 2009. Sixteen certified EHR systems were used among 91% of the Dutch and 63% of the French speaking sentinel GPs. The EHR software package was strongly related to the community and only one EHR system was used by a comparable number of sentinel GPs in both communities. Overall, the prescription module was always used and home visits were usually recorded. Uniform subject headings were only sometimes used and the compliance with this quality criterion was almost exclusively related to the EHR software package in use. The challenge is to progress towards a sentinel network of GPs delivering care-based data that are (partly) extracted from well performing EHR systems and still representative for Belgian general practice.

The double-edged sword of electronic health records: implications for patient disclosure.

PubMed

Campos-Castillo, Celeste; Anthony, Denise L

2015-04-01

Electronic health record (EHR) systems are linked to improvements in quality of care, yet also privacy and security risks. Results from research studies are mixed about whether patients withhold personal information from their providers to protect against the perceived EHR privacy and security risks. This study seeks to reconcile the mixed findings by focusing on whether accounting for patients' global ratings of care reveals a relationship between EHR provider-use and patient non-disclosure. A nationally representative sample from the 2012 Health Information National Trends Survey was analyzed using bivariate and multivariable logit regressions to examine whether global ratings of care suppress the relationship between EHR provider-use and patient non-disclosure. 13% of respondents reported having ever withheld information from a provider because of privacy/security concerns. Bivariate analysis showed that withholding information was unrelated to whether respondents' providers used an EHR. Multivariable analysis showed that accounting for respondents' global ratings of care revealed a positive relationship between having a provider who uses an EHR and withholding information. After accounting for global ratings of care, findings suggest that patients may non-disclose to providers to protect against the perceived EHR privacy and security risks. Despite evidence that EHRs inhibit patient disclosure, their advantages for promoting quality of care may outweigh the drawbacks. Clinicians should leverage the EHR's value in quality of care and discuss patients' privacy concerns during clinic visits, while policy makers should consider how to address the real and perceived privacy and security risks of EHRs. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Predictors of Success for Electronic Health Record Implementation in Small Physician Practices

PubMed Central

Ancker, J.S.; Singh, M.P.; Thomas, R.; Edwards, A.; Snyder, A.; Kashyap, A.; Kaushal, R.

2013-01-01

Background The federal government is promoting adoption of electronic health records (EHRs) through financial incentives for EHR use and implementation support provided by regional extension centers. Small practices have been slow to adopt EHRs. Objectives Our objective was to measure time to EHR implementation and identify factors associated with successful implementation in small practices receiving financial incentives and implementation support. This study is unique in exploiting quantitative implementation time data collected prospectively as part of routine project management. Methods This mixed-methods study includes interviews of key informants and a cohort study of 544 practices that had worked with the Primary Care Information Project (PCIP), a publicly funded organization that since 2007 has subsidized EHRs and provided implementation support similar to that supplied by the new regional extension centers. Data from a project management database were used for a cohort study to assess time to implementation and predictors of implementation success. Results Four hundred and thirty practices (79%) implemented EHRs within the analysis period, with a median project time of 24.7 weeks (95% CI: 23.3 – 26.4). Factors associated with implementation success were: fewer providers, practice sites, and patients; fewer Medicaid and uninsured patients; having previous experience with scheduling software; enrolling in 2010 rather than earlier; and selecting an integrated EHR plus practice management product rather than two products. Interviews identified positive attitude toward EHRs, resources, and centralized leadership as additional practice-level predictors of success. Conclusions A local initiative similar to current federal programs successfully implemented EHRs in primary care practices by offsetting software costs and providing implementation assistance. Nevertheless, implementation success was affected by practice size and other characteristics, suggesting that the federal programs can reduce barriers to EHR implementation but may not eliminate them. PMID:23650484

Applied nursing informatics research - state-of-the-art methodologies using electronic health record data.

PubMed

Park, Jung In; Pruinelli, Lisiane; Westra, Bonnie L; Delaney, Connie W

2014-01-01

With the pervasive implementation of electronic health records (EHR), new opportunities arise for nursing research through use of EHR data. Increasingly, comparative effectiveness research within and across health systems is conducted to identify the impact of nursing for improving health, health care, and lowering costs of care. Use of EHR data for this type of research requires use of national and internationally recognized nursing terminologies to normalize data. Research methods are evolving as large data sets become available through EHRs. Little is known about the types of research and analytic methods for applied to nursing research using EHR data normalized with nursing terminologies. The purpose of this paper is to report on a subset of a systematic review of peer reviewed studies related to applied nursing informatics research involving EHR data using standardized nursing terminologies.

Electronic health records in four community physician practices: impact on quality and cost of care.

PubMed

Welch, W Pete; Bazarko, Dawn; Ritten, Kimberly; Burgess, Yo; Harmon, Robert; Sandy, Lewis G

2007-01-01

To assess the impact of the electronic health record (EHR) on cost (i.e., payments to providers) and process measures of quality of care. Retrospective before-after-study-control. From the database of a large managed care organization (MCO), we obtained the claims of patients from four community physician practices that implemented the EHR and from about 50 comparison practices without the EHR in the same counties. The diverse patient and practice populations were chosen to be a sample more representative of typical private practices than has previously been studied. For four chronic conditions, we used commercially-available software to analyze cost per episode over a year and the rate of adherence to clinical guidelines as a measure of quality. The implementation of the EHR had a modest positive impact on the quality measure of guideline adherence for hypertension and hyperlipidemia, but no significant impact for diabetes and coronary artery disease. No measurable impact on the short-term cost per episode was found. Discussions with the study practices revealed that the timing and comprehensiveness of EHR implementation varied across practices, creating an intervention variable that was heterogeneous. Guideline adherence increased across practices without EHRs and slightly faster in practices with EHRs. Measuring the impact of EHRs on cost per episode was challenging, because of the difficulty of completely capturing the long-term episodic costs of a chronic condition. Few practices associated with the study MCO had implemented EHRs in any form, much less utilizing standardized protocols.

Technology versus humanism: how patients perceive the use of electronic health records in physicians' offices--a qualitative study.

PubMed

Mwachofi, Ari K; Khaliq, Amir A; Carrillo, Estevan R; Winfree, William

2016-01-01

Electronic Health Records (EHRs) have the potential to improve the quality of care. In view of the accelerated adoption of EHRs, there is a need to understand conditions necessary for their effective use. Patients are the focus of healthcare and their perceptions and expectations need to be included in developing and implementing EHRs. The purpose of this study was to gather exploratory qualitative information from patients about their experiences and perceptions regarding the effects of EHRs on healthcare quality in physicians' offices. We conducted five focus groups with patients representing a random mix of diverse socio-demographic backgrounds in Oklahoma. Related to EHRs, patients reported improvements on the technical side of care but no change on the human side. They expressed concerns about the potential for breach of confidentiality and security of medical records. They were also concerned about the possibility of governmental agencies or insurance companies having unauthorized access to patient records. Patients differentiated between the human and technical sides of care and reported no change or improvement in the doctor-patient interaction. Patients have an important perspective on the use of EHRs and their perceptions and experiences should be considered in the development, adoption and implementation of EHRs. Otherwise, the use of EHRs may not be fully effective. There is also a need to educate patients about the potential benefits and risks of EHRs and the steps being taken to mitigate such risks.

The long-term financial impact of electronic health record implementation.

PubMed

Howley, Michael J; Chou, Edgar Y; Hansen, Nancy; Dalrymple, Prudence W

2015-03-01

To examine the financial impact of electronic health record (EHR) implementation on ambulatory practices. We tracked the practice productivity (ie, number of patient visits) and reimbursement of 30 ambulatory practices for 2 years after EHR implementation and compared each practice to their pre-EHR implementation baseline. Reimbursements significantly increased after EHR implementation even though practice productivity (ie, the number of patient visits) decreased over the 2-year observation period. We saw no evidence of upcoding or increased reimbursement rates to explain the increased revenues. Instead, they were associated with an increase in ancillary office procedures (eg, drawing blood, immunizations, wound care, ultrasounds). The bottom line result-that EHR implementation is associated with increased revenues-is reassuring and offers a basis for further EHR investment. While the productivity losses are consistent with field reports, they also reflect a type of efficiency-the practices are receiving more reimbursement for fewer seeing patients. For the practices still seeing fewer patients after 2 years, the solution likely involves advancing their EHR functionality to include analytics. Although they may still see fewer patients, with EHR analytics, they can focus on seeing the right patients. Practice reimbursements increased after EHR implementation, but there was a long-term decrease in the number of patient visits seen in this ambulatory practice context. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Catch to Confidentiality: The Use of Electronic Health Records in Adolescent Health Care.

PubMed

Stablein, Timothy; Loud, Keith J; DiCapua, Christopher; Anthony, Denise L

2018-05-01

This study aims to understand pediatric health-care providers' expectations and the practices they employ to protect confidentiality in electronic health records (EHRs) and subsequently how EHRs affect the documentation and dissemination of information in the course of health-care delivery to adolescent minors. Twenty-six pediatric health-care providers participated in in-depth interviews about their experiences using EHRs to understand a broad spectrum of expectations and practices guiding the documentation and dissemination of information in the EHR. A thematic analysis of interviews was conducted to draw findings and conclusions. Two themes and several subthemes emerged centering on how EHRs affected confidentiality expectations and practices. Participants expressed confidentiality concerns due to the EHR's longevity as a legacy record, its multidimensional uses, and increased access by users (theme 1). These concerns affected practices for protecting adolescent confidentiality within the EHR (theme 2). Practices included selectively omitting or concealing information and utilizing sets of personal and collective codes designed to alert providers or teams of providers to confidential information within a patient's record. EHRs create new and unresolved challenges for pediatric health care as they alter expectations of confidentiality and the documentation and dissemination of information within the record. This is particularly relevant in the course of care to adolescent minors as EHRs may compromise the tenuous balance providers maintain between protecting confidentiality and effective documentation within the record. Copyright © 2017 The Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

An HL7/CDA Framework for the Design and Deployment of Telemedicine Services

DTIC Science & Technology

2001-10-25

schemes and prescription databases. Furthermore, interoperability with the Electronic Health Re- cord ( EHR ) facilitates automatic retrieval of relevant...local EHR system or the integrated electronic health record (I- EHR ) [9], which indexes all medical contacts of a patient in the regional net- work...suspected medical problem. Interoperability with middleware services of the HII and other data sources such as the local EHR sys- tem affects

Organization, management, implementation and value of ehr implementation in a solo pediatric practice.

PubMed

Cooper, Jeffrey D

2004-01-01

This case study-based on this practice's application for the 2003 HIMSS Davies Award for Primary Care-describes the processes, costs and benefits of the implementation of an EHR in a solo practice. The organization, management and value of an EHR implementation is described, as well as a description of the physician's 15 business objectives, which shows how each objective was met and to what degree and gives specific financial data. An EHR that is implemented in a small practice improves quality of patient care, office efficiency and patient safety. A small practice can realize significant ROI from an EHR.

Usability problems do not heal by themselves: National survey on physicians' experiences with EHRs in Finland.

PubMed

Kaipio, Johanna; Lääveri, Tinja; Hyppönen, Hannele; Vainiomäki, Suvi; Reponen, Jarmo; Kushniruk, Andre; Borycki, Elizabeth; Vänskä, Jukka

2017-01-01

Survey studies of health information systems use tend to focus on availability of functionalities, adoption and intensity of use. Usability surveys have not been systematically conducted by any healthcare professional groups on a national scale on a repeated basis. This paper presents results from two cross-sectional surveys of physicians' experiences with the usability of currently used EHR systems in Finland. The research questions were: To what extent has the overall situation improved between 2010 and 2014? What differences are there between healthcare sectors? In the spring of 2014, a survey was conducted in Finland using a questionnaire that measures usability and respondents' user experiences with electronic health record (EHR) systems. The survey was targeted to physicians who were actively doing clinical work. Twenty-four usability-related statements, that were identical in 2010 and 2014, were analysed from the survey. The respondents were also asked to give an overall rating of the EHR system they used. The study data comprised responses from 3081 physicians from the year 2014 and from 3223 physicians in the year 2010, who were using the nine most commonly used EHR system brands in Finland. Physicians' assessments of the usability of their EHR system remain as critical as they were in 2010. On a scale from 1 ('fail') to 7 ('excellent') the average of overall ratings of their principally used EHR systems varied from 3.2 to 4.4 in 2014 (and in 2010 from 2.5 to 4.3). The results show some improvements in the following EHR functionalities and characteristics: summary view of patient's health status, prevention of errors associated with medication ordering, patient's medication list as well as support for collaboration and information exchange between the physician and the nurses. Even so, support for cross-organizational collaboration between physicians and for physician-patient collaboration were still considered inadequate. Satisfaction with technical features had not improved in four years. The results show marked differences between the EHR system brands as well as between healthcare sectors (private sector, public hospitals, primary healthcare). Compared to responses from the public sector, physicians working in the private sector were more satisfied with their EHR systems with regards to statements about user interface characteristics and support for routine tasks. Overall, the study findings are similar to our previous study conducted in 2010. Surveys about the usability of EHR systems are needed to monitor their development at regional and national levels. To our knowledge, this study is the first national eHealth observatory questionnaire that focuses on usability and is used to monitor the long-term development of EHRs. The results do not show notable improvements in physician's ratings for their EHRs between the years 2010 and 2014 in Finland. Instead, the results indicate the existence of serious problems and deficiencies which considerably hinder the efficiency of EHR use and physician's routine work. The survey results call for considerable amount of development work in order to achieve the expected benefits of EHR systems and to avoid technology-induced errors which may endanger patient safety. The findings of repeated surveys can be used to inform healthcare providers, decision makers and politicians about the current state of EHR usability and differences between brands as well as for improvements of EHR usability. This survey will be repeated in 2017 and there is a plan to include other healthcare professional groups in future surveys. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

HITECH spurs EHR vendor competition and innovation, resulting in increased adoption.

PubMed

Joseph, Seth; Sow, Max; Furukawa, Michael F; Posnack, Steven; Chaffee, Mary Ann

2014-09-01

The Health Information Technology for Economic and Clinical Health (HITECH) Act was enacted to increase electronic health record (EHR) adoption by providers and hospitals. Experts expressed skepticism about whether the program would indeed hasten adoption and could be implemented in time for the initial reporting period. Could EHR vendors meet the certification requirements, and could the industry innovate to meet small-practice needs? This study, in addition to documenting increased provider adoption, provides the first evidence of increased competitiveness and innovation in the EHR industry spurred by HITECH. For example, the number of EHR vendors certified for e-prescribing with Surescripts increased from 96 to 229 over the program's first 3 years. We also find that prescribers in small practices increasingly adopted lower-cost, Web-based e-prescribing and EHR applications at significantly higher rates (15%-35%) than did large practices (3%-4%), which generally have more human and capital resources to make significant investments. These findings suggest that EHR vendors were highly responsive to HITECH requirements and have been adapting their strategies to meet nuanced market needs, providing reason to be optimistic about the Programs' future.

Building a portable data and information interoperability infrastructure-framework for a standard Taiwan Electronic Medical Record Template.

PubMed

Jian, Wen-Shan; Hsu, Chien-Yeh; Hao, Te-Hui; Wen, Hsyien-Chia; Hsu, Min-Huei; Lee, Yen-Liang; Li, Yu-Chuan; Chang, Polun

2007-11-01

Traditional electronic health record (EHR) data are produced from various hospital information systems. They could not have existed independently without an information system until the incarnation of XML technology. The interoperability of a healthcare system can be divided into two dimensions: functional interoperability and semantic interoperability. Currently, no single EHR standard exists that provides complete EHR interoperability. In order to establish a national EHR standard, we developed a set of local EHR templates. The Taiwan Electronic Medical Record Template (TMT) is a standard that aims to achieve semantic interoperability in EHR exchanges nationally. The TMT architecture is basically composed of forms, components, sections, and elements. Data stored in the elements which can be referenced by the code set, data type, and narrative block. The TMT was established with the following requirements in mind: (1) transformable to international standards; (2) having a minimal impact on the existing healthcare system; (3) easy to implement and deploy, and (4) compliant with Taiwan's current laws and regulations. The TMT provides a basis for building a portable, interoperable information infrastructure for EHR exchange in Taiwan.

Archetype-based data warehouse environment to enable the reuse of electronic health record data.

PubMed

Marco-Ruiz, Luis; Moner, David; Maldonado, José A; Kolstrup, Nils; Bellika, Johan G

2015-09-01

The reuse of data captured during health care delivery is essential to satisfy the demands of clinical research and clinical decision support systems. A main barrier for the reuse is the existence of legacy formats of data and the high granularity of it when stored in an electronic health record (EHR) system. Thus, we need mechanisms to standardize, aggregate, and query data concealed in the EHRs, to allow their reuse whenever they are needed. To create a data warehouse infrastructure using archetype-based technologies, standards and query languages to enable the interoperability needed for data reuse. The work presented makes use of best of breed archetype-based data transformation and storage technologies to create a workflow for the modeling, extraction, transformation and load of EHR proprietary data into standardized data repositories. We converted legacy data and performed patient-centered aggregations via archetype-based transformations. Later, specific purpose aggregations were performed at a query level for particular use cases. Laboratory test results of a population of 230,000 patients belonging to Troms and Finnmark counties in Norway requested between January 2013 and November 2014 have been standardized. Test records normalization has been performed by defining transformation and aggregation functions between the laboratory records and an archetype. These mappings were used to automatically generate open EHR compliant data. These data were loaded into an archetype-based data warehouse. Once loaded, we defined indicators linked to the data in the warehouse to monitor test activity of Salmonella and Pertussis using the archetype query language. Archetype-based standards and technologies can be used to create a data warehouse environment that enables data from EHR systems to be reused in clinical research and decision support systems. With this approach, existing EHR data becomes available in a standardized and interoperable format, thus opening a world of possibilities toward semantic or concept-based reuse, query and communication of clinical data. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Building a house on shifting sand: methodological considerations when evaluating the implementation and adoption of national electronic health record systems

PubMed Central

2012-01-01

Background A commitment to Electronic Health Record (EHR) systems now constitutes a core part of many governments’ healthcare reform strategies. The resulting politically-initiated large-scale or national EHR endeavors are challenging because of their ambitious agendas of change, the scale of resources needed to make them work, the (relatively) short timescales set, and the large number of stakeholders involved, all of whom pursue somewhat different interests. These initiatives need to be evaluated to establish if they improve care and represent value for money. Methods Critical reflections on these complexities in the light of experience of undertaking the first national, longitudinal, and sociotechnical evaluation of the implementation and adoption of England’s National Health Service’s Care Records Service (NHS CRS). Results/discussion We advance two key arguments. First, national programs for EHR implementations are likely to take place in the shifting sands of evolving sociopolitical and sociotechnical and contexts, which are likely to shape them in significant ways. This poses challenges to conventional evaluation approaches which draw on a model of baseline operations → intervention → changed operations (outcome). Second, evaluation of such programs must account for this changing context by adapting to it. This requires careful and creative choice of ontological, epistemological and methodological assumptions. Summary New and significant challenges are faced in evaluating national EHR implementation endeavors. Based on experiences from this national evaluation of the implementation and adoption of the NHS CRS in England, we argue for an approach to these evaluations which moves away from seeing EHR systems as Information and Communication Technologies (ICT) projects requiring an essentially outcome-centred assessment towards a more interpretive approach that reflects the situated and evolving nature of EHR seen within multiple specific settings and reflecting a constantly changing milieu of policies, strategies and software, with constant interactions across such boundaries. PMID:22545646

The intention to use an electronic health record and its antecedents among three different categories of clinical staff.

PubMed

Vitari, Claudio; Ologeanu-Taddei, Roxana

2018-03-21

Like other sectors, the healthcare sector has to deal with the issue of users' acceptance of IT. In healthcare, different factors affecting healthcare professionals' acceptance of software applications have been investigated. Unfortunately, inconsistent results have been found, maybe because the different studies focused on different IT and occupational groups. Consequently, more studies are needed to investigate these implications for recent technology, such as Electronic Health Records (EHR). Given these findings in the existing literature, we pose the following research question: "To what extent do the different categories of clinical staff (physicians, paraprofessionals and administrative personnel) influence the intention to use an EHR and its antecedents?" To answer this research question we develop a research model that we empirically tested via a survey, including the following variables: intention to use, ease of use, usefulness, anxiety, self-efficacy, trust, misfit and data security. Our purpose is to clarify the possible differences existing between different staff categories. For the entire personnel, all the hypotheses are confirmed: anxiety, self-efficacy, trust influence ease of use; ease of use, misfit, self-efficacy, data security impact usefulness; usefulness and ease of use contribute to intention to use the EHR. They are also all confirmed for physicians, residents, carers and nurses but not for secretaries and assistants. Secretaries' and assistants' perception of the ease of use of EHR does not influence their intention to use it and they could not be influenced by self-efficacy in the development of their perception of the ease of use of EHR. These results may be explained by the fact that secretaries, unlike physicians and nurses, have to follow rules and procedures for their work, including working with EHR. They have less professional autonomy than healthcare professionals and no medical responsibility. This result is also in line with previous literature highlighting that administrators are more motivated by the use of IT in healthcare.

Building a house on shifting sand: methodological considerations when evaluating the implementation and adoption of national electronic health record systems.

PubMed

Takian, Amirhossein; Petrakaki, Dimitra; Cornford, Tony; Sheikh, Aziz; Barber, Nicholas

2012-04-30

A commitment to Electronic Health Record (EHR) systems now constitutes a core part of many governments' healthcare reform strategies. The resulting politically-initiated large-scale or national EHR endeavors are challenging because of their ambitious agendas of change, the scale of resources needed to make them work, the (relatively) short timescales set, and the large number of stakeholders involved, all of whom pursue somewhat different interests. These initiatives need to be evaluated to establish if they improve care and represent value for money. Critical reflections on these complexities in the light of experience of undertaking the first national, longitudinal, and sociotechnical evaluation of the implementation and adoption of England's National Health Service's Care Records Service (NHS CRS). We advance two key arguments. First, national programs for EHR implementations are likely to take place in the shifting sands of evolving sociopolitical and sociotechnical and contexts, which are likely to shape them in significant ways. This poses challenges to conventional evaluation approaches which draw on a model of baseline operations → intervention → changed operations (outcome). Second, evaluation of such programs must account for this changing context by adapting to it. This requires careful and creative choice of ontological, epistemological and methodological assumptions. New and significant challenges are faced in evaluating national EHR implementation endeavors. Based on experiences from this national evaluation of the implementation and adoption of the NHS CRS in England, we argue for an approach to these evaluations which moves away from seeing EHR systems as Information and Communication Technologies (ICT) projects requiring an essentially outcome-centred assessment towards a more interpretive approach that reflects the situated and evolving nature of EHR seen within multiple specific settings and reflecting a constantly changing milieu of policies, strategies and software, with constant interactions across such boundaries.

Evolution of an Implementation-Ready Interprofessional Pain Assessment Reference Model

PubMed Central

Collins, Sarah A; Bavuso, Karen; Swenson, Mary; Suchecki, Christine; Mar, Perry; Rocha, Roberto A.

2017-01-01

Standards to increase consistency of comprehensive pain assessments are important for safety, quality, and analytics activities, including meeting Joint Commission requirements and learning the best management strategies and interventions for the current prescription Opioid epidemic. In this study we describe the development and validation of a Pain Assessment Reference Model ready for implementation on EHR forms and flowsheets. Our process resulted in 5 successive revisions of the reference model, which more than doubled the number of data elements to 47. The organization of the model evolved during validation sessions with panels totaling 48 subject matter experts (SMEs) to include 9 sets of data elements, with one set recommended as a minimal data set. The reference model also evolved when implemented into EHR forms and flowsheets, indicating specifications such as cascading logic that are important to inform secondary use of data. PMID:29854125

Hospital Characteristics are Associated With Readiness to Attain Stage 2 Meaningful Use of Electronic Health Records.

PubMed

Kim, Jungyeon; Ohsfeldt, Robert L; Gamm, Larry D; Radcliff, Tiffany A; Jiang, Luohua

2017-06-01

To examine the difference between rural and urban hospitals as to their overall level of readiness for stage 2 meaningful use of electronic health records (EHRs) and to identify other key factors that affect their readiness for stage 2 meaningful use. A conceptual framework based on the theory of organizational readiness for change was used in a cross-sectional multivariate analysis using 2,083 samples drawn from the HIMSS Analytics survey conducted with US hospitals in 2013. Rural hospitals were less likely to be ready for stage 2 meaningful use compared to urban hospitals in the United States (OR = 0.49) in our final model. Hospitals' past experience with an information exchange initiative, staff size in the information system department, and the Chief Information Officer (CIO)'s responsibility for health information management were identified as the most critical organizational contextual factors that were associated with hospitals' readiness for stage 2. Rural hospitals lag behind urban hospitals in EHR adoption, which will hinder the interoperability of EHRs among providers across the nation. The identification of critical factors that relate to the adoption of EHR systems provides insights into possible organizational change efforts that can help hospitals to succeed in attaining meaningful use requirements. Rural hospitals have increasingly limited resources, which have resulted in a struggle for these facilities to attain meaningful use. Given increasing closures among rural hospitals, it is all the more important that EHR development focus on advancing rural hospital quality of care and linkages with patients and other organizations supporting the care of their patients. © 2016 National Rural Health Association.

Teamwork and Electronic Health Record Implementation: A Case Study of Preserving Effective Communication and Mutual Trust in a Changing Environment.

PubMed

Gross, Anne H; Leib, Ryan K; Tonachel, Anne; Tonachel, Richard; Bowers, Danielle M; Burnard, Rachel A; Rhinehart, Catherine A; Valentim, Rahila; Bunnell, Craig A

2016-11-01

This article describes how trust among team members and in the technology supporting them was eroded during implementation of an electronic health record (EHR) in an adult outpatient oncology practice at a comprehensive cancer center. Delays in care of a 38-year-old woman with high-risk breast cancer occurred because of ineffective team communication and are illustrated in a case study. The case explores how the patient's trust and mutual trust between team members were disrupted because of inaccurate assumptions about the functionality of the EHR's communication tool, resultant miscommunications between team members and the patient, and the eventual recognition that care was not being effectively coordinated, as it had been previously. Despite a well-established, team-based culture and significant preparation for the EHR implementation, the challenges that occurred point to underlying human and system failures from which other organizations going through a similar process may learn. Through an analysis and evaluation of events that transpired before and during the EHR rollout, suggested interventions for preventing this experience are offered, which include: a thorough crosswalk between old and new communication mechanisms before implementation; understanding and mitigation of gaps in the communication tool's functionality; more robust training for staff, clinicians, and patients; greater consideration given to the pace of change expected of individuals; and development of models of collaboration between EHR users and vendors in developing products that support high-quality, team-based care in the oncology setting. These interventions are transferable to any organizational or system change that threatens mutual trust and effective communication.

Locating relevant patient information in electronic health record data using representations of clinical concepts and database structures.

PubMed

Pan, Xuequn; Cimino, James J

2014-01-01

Clinicians and clinical researchers often seek information in electronic health records (EHRs) that are relevant to some concept of interest, such as a disease or finding. The heterogeneous nature of EHRs can complicate retrieval, risking incomplete results. We frame this problem as the presence of two gaps: 1) a gap between clinical concepts and their representations in EHR data and 2) a gap between data representations and their locations within EHR data structures. We bridge these gaps with a knowledge structure that comprises relationships among clinical concepts (including concepts of interest and concepts that may be instantiated in EHR data) and relationships between clinical concepts and the database structures. We make use of available knowledge resources to develop a reproducible, scalable process for creating a knowledge base that can support automated query expansion from a clinical concept to all relevant EHR data.

Generation of ELGA-compatible radiology reports from the Vienna Hospital Association's EHR system.

PubMed

Haider, Jasmin; Hölzl, Konrad; Toth, Herlinde; Duftschmid, Georg

2014-01-01

In the course of setting up the upcoming Austrian national shared EHR system ELGA, adaptors will have to be implemented for the local EHR systems of all participating healthcare providers. These adaptors must be able to transform EHR data from the internal format of the particular local EHR system to the specified format of the ELGA document types and vice versa. In the course of an ongoing diploma thesis we are currently developing a transformation application that shall allow the generation of ELGA-compatible radiology reports from the local EHR system of the Vienna Hospital Association. Up to now a first prototype has been developed that was tested with six radiology reports. It generates technically valid ELGA radiology reports apart from two errors yielded by the ELGA online validator that rather seem to be bugs of the validator. A medical validation of the reports remains to be done.

Supporting openEHR Java desktop application developers.

PubMed

Kashfi, Hajar; Torgersson, Olof

2011-01-01

The openEHR community suggests that an appropriate approach for creating a graphical user interface for an openEHR-based application is to generate forms from the underlying archetypes and templates. However, current generation techniques are not mature enough to be able to produce high quality interfaces with good usability. Therefore, developing efficient ways to combine manually designed and developed interfaces to openEHR backends is an interesting alternative. In this study, a framework for binding a pre-designed graphical user interface to an openEHR-based backend is proposed. The proposed framework contributes to the set of options available for developers. In particular we believe that the approach of combining user interface components with an openEHR backend in the proposed way might be useful in situations where the quality of the user interface is essential and for creating small scale and experimental systems.

Enabling Cross-Platform Clinical Decision Support through Web-Based Decision Support in Commercial Electronic Health Record Systems: Proposal and Evaluation of Initial Prototype Implementations

PubMed Central

Zhang, Mingyuan; Velasco, Ferdinand T.; Musser, R. Clayton; Kawamoto, Kensaku

2013-01-01

Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426

Electronic Immunization Alerts and Spillover Effects on Other Preventive Care.

PubMed

Kim, Julia M; Rivera, Maria; Persing, Nichole; Bundy, David G; Psoter, Kevin J; Ghazarian, Sharon R; Miller, Marlene R; Solomon, Barry S

2017-08-01

The impact of electronic health record (EHR) immunization clinical alert systems on the delivery of other preventive services remains unknown. We assessed for spillover effects of an EHR immunization alert on delivery of 6 other preventive services, in children 18 to 30 months of age needing immunizations. We conducted a secondary data analysis, with additional primary data collection, of a randomized, historically controlled trial to improve immunization rates with EHR alerts, in an urban, primary care clinic. No significant differences were found in screening for anemia, lead, development, nutrition, and injury prevention counseling in children prompting EHR immunization alerts (n = 129), compared with controls (n = 135). Significant increases in oral health screening in patients prompting EHR alerts (odds ratio = 4.8, 95% CI = 1.8-13.0) were likely due to practice changes over time. An EHR clinical alert system targeting immunizations did not have a spillover effect on the delivery of other preventive services.

Effect of an Electronic Health Record on the Culture of an Outpatient Medical Oncology Practice in a Four-Hospital Integrated Health Care System: 5-Year Experience

PubMed Central

Brockstein, Bruce; Hensing, Thomas; Carro, George W.; Obel, Jennifer; Khandekar, Janardan; Kaminer, Lynne; Van De Wege, Christine; de Wilton Marsh, Robert

2011-01-01

The electronic health record (EHR) was adopted into the NorthShore University HealthSystem, a four-hospital integrated health system located in suburban Chicago, in 2003. By 2005, all chemotherapy and medicine order entry was conducted through the EHR, completing the incorporation of a fully paperless EHR in our hospital-based oncology practice in both the inpatient and outpatient settings. The use of the EHR has dramatically changed our practice environment by improving efficiency, patient safety, research productivity, and operations, while allowing evaluation of adherence to established quality measures and incorporation of new quality improvement initiatives. The reach of the EHR has been substantial and has influenced every aspect of care at our institution over the short period since its implementation. In this article, we describe subjective and objective measures, outcomes, and achievements of our 5-year EHR experience. PMID:22043197

Improving Service Coordination and Reducing Mental Health Disparities Through Adoption of Electronic Health Records.

PubMed

McGregor, Brian; Mack, Dominic; Wrenn, Glenda; Shim, Ruth S; Holden, Kisha; Satcher, David

2015-09-01

Despite widespread support for removing barriers to the use of electronic health records (EHRs) in behavioral health care, adoption of EHRs in behavioral health settings lags behind adoption in other areas of health care. The authors discuss barriers to use of EHRs among behavioral health care practitioners, suggest solutions to overcome these barriers, and describe the potential benefits of EHRs to reduce behavioral health care disparities. Thoughtful and comprehensive strategies will be needed to design EHR systems that address concerns about policy, practice, costs, and stigma and that protect patients' privacy and confidentiality. However, these goals must not detract from continuing to challenge the notion that behavioral health and general medical health should be treated as separate and distinct. Ultimately, utilization of EHRs among behavioral health care providers will improve the coordination of services and overall patient care, which is essential to reducing mental health disparities.

Patient and Public Views on Electronic Health Records and Their Uses in the United Kingdom: Cross-Sectional Survey

PubMed Central

Luchenski, Serena A; Reed, Julie E; Marston, Cicely; Papoutsi, Chrysanthi; Majeed, Azeem

2013-01-01

Background The development and implementation of electronic health records (EHRs) remains an international challenge. Better understanding of patient and public attitudes and the factors that influence overall levels of support toward EHRs is needed to inform policy. Objective To explore patient and public attitudes toward integrated EHRs used simultaneously for health care provision, planning and policy, and health research. Methods Cross-sectional questionnaire survey administered to patients and members of the public who were recruited from a stratified cluster random sample of 8 outpatient clinics of a major teaching hospital and 8 general practices in London (United Kingdom). Results 5331 patients and members of the public responded to the survey, with 2857 providing complete data for the analysis presented here. There were moderately high levels of support for integrated EHRs used simultaneously for health care provision, planning and policy, and health research (1785/2857, 62.47%), while 27.93% (798/2857) of participants reported being undecided about whether or not they would support EHR use. There were higher levels of support for specific uses of EHRs. Most participants were in favor of EHRs for personal health care provision (2563/2857, 89.71%), with 66.75% (1907/2857) stating that they would prefer their complete, rather than limited, medical history to be included. Of those “undecided” about integrated EHRs, 87.2% (696/798) were nevertheless in favor of sharing their full (373/798, 46.7%) or limited (323/798, 40.5%) records for health provision purposes. There were similar high levels of support for use of EHRs in health services policy and planning (2274/2857, 79.59%) and research (2325/2857, 81.38%), although 59.75% (1707/2857) and 67.10% (1917/2857) of respondents respectively would prefer their personal identifiers to be removed. Multivariable analysis showed levels of overall support for EHRs decreasing with age. Respondents self-identifying as Black British were more likely to report being undecided or unsupportive of national EHRs. Frequent health services users were more likely to report being supportive than undecided. Conclusions Despite previous difficulties with National Health Service (NHS) technology projects, patients and the public generally support the development of integrated EHRs for health care provision, planning and policy, and health research. This support, however, varies between social groups and is not unqualified; relevant safeguards must be in place and patients should be guided in their decision-making process, including increased awareness about the benefits of EHRs for secondary uses. PMID:23975239

Patient and public views on electronic health records and their uses in the United kingdom: cross-sectional survey.

PubMed

Luchenski, Serena A; Reed, Julie E; Marston, Cicely; Papoutsi, Chrysanthi; Majeed, Azeem; Bell, Derek

2013-08-23

The development and implementation of electronic health records (EHRs) remains an international challenge. Better understanding of patient and public attitudes and the factors that influence overall levels of support toward EHRs is needed to inform policy. To explore patient and public attitudes toward integrated EHRs used simultaneously for health care provision, planning and policy, and health research. Cross-sectional questionnaire survey administered to patients and members of the public who were recruited from a stratified cluster random sample of 8 outpatient clinics of a major teaching hospital and 8 general practices in London (United Kingdom). 5331 patients and members of the public responded to the survey, with 2857 providing complete data for the analysis presented here. There were moderately high levels of support for integrated EHRs used simultaneously for health care provision, planning and policy, and health research (1785/2857, 62.47%), while 27.93% (798/2857) of participants reported being undecided about whether or not they would support EHR use. There were higher levels of support for specific uses of EHRs. Most participants were in favor of EHRs for personal health care provision (2563/2857, 89.71%), with 66.75% (1907/2857) stating that they would prefer their complete, rather than limited, medical history to be included. Of those "undecided" about integrated EHRs, 87.2% (696/798) were nevertheless in favor of sharing their full (373/798, 46.7%) or limited (323/798, 40.5%) records for health provision purposes. There were similar high levels of support for use of EHRs in health services policy and planning (2274/2857, 79.59%) and research (2325/2857, 81.38%), although 59.75% (1707/2857) and 67.10% (1917/2857) of respondents respectively would prefer their personal identifiers to be removed. Multivariable analysis showed levels of overall support for EHRs decreasing with age. Respondents self-identifying as Black British were more likely to report being undecided or unsupportive of national EHRs. Frequent health services users were more likely to report being supportive than undecided. Despite previous difficulties with National Health Service (NHS) technology projects, patients and the public generally support the development of integrated EHRs for health care provision, planning and policy, and health research. This support, however, varies between social groups and is not unqualified; relevant safeguards must be in place and patients should be guided in their decision-making process, including increased awareness about the benefits of EHRs for secondary uses.

Lessons Learned for Collaborative Clinical Content Development

PubMed Central

Collins, S.A.; Bavuso, K.; Zuccotti, G.; Rocha, R.A.

2013-01-01

Background Site-specific content configuration of vendor-based Electronic Health Records (EHRs) is a vital step in the development of standardized and interoperable content that can be used for clinical decision-support, reporting, care coordination, and information exchange. The multi-site, multi-stakeholder Acute Care Documentation (ACD) project at Partners Healthcare Systems (PHS) aimed to develop highly structured clinical content with adequate breadth and depth to meet the needs of all types of acute care clinicians at two academic medical centers. The Knowledge Management (KM) team at PHS led the informatics and knowledge management effort for the project. Objectives We aimed to evaluate the role, governance, and project management processes and resources for the KM team’s effort as part of the standardized clinical content creation. Methods We employed the Center for Disease Control’s six step Program Evaluation Framework to guide our evaluation steps. We administered a forty-four question, open-ended, semi-structured voluntary survey to gather focused, credible evidence from members of the KM team. Qualitative open-coding was performed to identify themes for lessons learned and concluding recommendations. Results Six surveys were completed. Qualitative data analysis informed five lessons learned and thirty specific recommendations associated with the lessons learned. The five lessons learned are: 1) Assess and meet knowledge needs and set expectations at the start of the project; 2) Define an accountable decision-making process; 3) Increase team meeting moderation skills; 4) Ensure adequate resources and competency training with online asynchronous collaboration tools; 5) Develop focused, goal-oriented teams and supportive, consultative service based teams. Conclusions Knowledge management requirements for the development of standardized clinical content within a vendor-based EHR among multi-stakeholder teams and sites include: 1) assessing and meeting informatics knowledge needs, 2) setting expectations and standardizing the process for decision-making, and 3) ensuring the availability of adequate resources and competency training. PMID:23874366

Diabetes and Hypertension Quality Measurement in Four Safety-Net Sites

PubMed Central

Benkert, R.; Dennehy, P.; White, J.; Hamilton, A.; Tanner, C.

2014-01-01

Summary Background In this new era after the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, the literature on lessons learned with electronic health record (EHR) implementation needs to be revisited. Objectives Our objective was to describe what implementation of a commercially available EHR with built-in quality query algorithms showed us about our care for diabetes and hypertension populations in four safety net clinics, specifically feasibility of data retrieval, measurements over time, quality of data, and how our teams used this data. Methods A cross-sectional study was conducted from October 2008 to October 2012 in four safety-net clinics located in the Midwest and Western United States. A data warehouse that stores data from across the U.S was utilized for data extraction from patients with diabetes or hypertension diagnoses and at least two office visits per year. Standard quality measures were collected over a period of two to four years. All sites were engaged in a partnership model with the IT staff and a shared learning process to enhance the use of the quality metrics. Results While use of the algorithms was feasible across sites, challenges occurred when attempting to use the query results for research purposes. There was wide variation of both process and outcome results by individual centers. Composite calculations balanced out the differences seen in the individual measures. Despite using consistent quality definitions, the differences across centers had an impact on numerators and denominators. All sites agreed to a partnership model of EHR implementation, and each center utilized the available resources of the partnership for Center-specific quality initiatives. Conclusions Utilizing a shared EHR, a Regional Extension Center-like partnership model, and similar quality query algorithms allowed safety-net clinics to benchmark and improve the quality of care across differing patient populations and health care delivery models. PMID:25298815

Association between Electronic Health Records and Health Care Utilization

PubMed Central

Edwards, A.; Kern, L.M.

2015-01-01

Summary Background The federal government is investing approximately $20 billion in electronic health records (EHRs), in part to address escalating health care costs. However, empirical evidence that provider use of EHRs decreases health care costs is limited. Objective To determine any association between EHRs and health care utilization. Methods We conducted a cohort study (2008–2009) in the Hudson Valley, a multi-payer, multiprovider community in New York State. We included 328 primary care physicians in predominantly small practices (median practice size four primary care physicians), who were caring for 223,772 patients. Data from an independent practice association was used to determine adoption of EHRs. Claims data aggregated across five commercial health plans was used to characterize seven types of health care utilization: primary care visits, specialist visits, radiology tests, laboratory tests, emergency department visits, hospital admissions, and readmissions. We used negative binomial regression to determine associations between EHR adoption and each utilization outcome, adjusting for ten physician characteristics. Results Approximately half (48%) of the physicians were using paper records and half (52%) were using EHRs. For every 100 patients seen by physicians using EHRs, there were 14 fewer specialist visits (adjusted p < 0.01) and 9 fewer radiology tests (adjusted p = 0.01). There were no significant differences in rates of primary care visits, laboratory tests, emergency department visits, hospitalizations or readmissions. Conclusions Patients of primary care providers who used EHRs were less likely to have specialist visits and radiology tests than patients of primary care providers who did not use EHRs. PMID:25848412

Electronic health record usage behaviors in primary care medical practices: A survey of family physicians in Canada.

PubMed

Paré, Guy; Raymond, Louis; Guinea, Ana Ortiz de; Poba-Nzaou, Placide; Trudel, Marie-Claude; Marsan, Josianne; Micheneau, Thomas

2015-10-01

The importance and potential value of office-based electronic health record (EHR) systems is being recognized internationally. We thus sought to better understand how EHRs are actually being used by family physicians and what they perceive to be the main performance outcomes for themselves and their medical practices. We conducted a survey of family physicians practicing in medical practices in Quebec, Canada (n =331). Bivariate and multivariate statistical analyses were conducted to characterize EHR usage behaviors and assess the perceived performance outcomes of these systems. EHR systems "as-used" vary substantively from one family physician to another in terms of the capabilities that are actually mobilized by them. Significant differences between "basic" and "advanced" users were observed in terms of the EHR system's characteristics and perceived performance outcomes. Physicians were also clustered under three profiles that could be clearly distinguished from one another, in terms of the extent to which their performance and their practice's performance was impacted by their EHR usage. Physicians that are "highly impacted" by their EHR system are those who have the longest usage experience and make the most extended use of their system's capabilities. Our study indicates that only a minority of family physicians in our sample use most of the features available in their EHR system. Consequently, few physicians perceive gaining significant performance improvements from such systems. Future research must identify the factors that motivate primary care physicians to assimilate EHR systems in a more extensive manner. Copyright © 2015. Published by Elsevier Ireland Ltd.

Why sub-Saharan Africa lags in electronic health record adoption and possible strategies to increase its adoption in this region

PubMed Central

Odekunle, Florence Femi; Odekunle, Raphael Oluseun; Shankar, Srinivasan

2017-01-01

Poor health information system has been identified as a major challenge in the health-care system in many developing countries including sub-Saharan African countries. Electronic health record (EHR) has been shown as an important tool to improve access to patient information with attendance improved quality of care. However, EHR has not been widely implemented/adopted in sub-Saharan Africa. This study sought to identify factors that affect the adoption of an EHR in sub-Saharan Africa and strategies to improve its adoption in this region. A comprehensive literature search was conducted on three electronic databases: PubMed, Medline, and Google Scholar. Articles of interest were those published in English that contained information on factors that limit the adoption of an EHR as well as strategies that improve its adoption in sub-Saharan African countries. The available evidence indicated that there were many factors that hindered the widespread adoption of an EHR in sub-Saharan Africa. These were high costs of procurement and maintenance of the EHR system, lack of financial incentives and priorities, poor electricity supply and internet connectivity, and primary user’s limited computer skills. However, strategies such as implementation planning, financial supports, appropriate EHR system selection, training of primary users, and the adoption of the phased implementation process have been identified to facilitate the use of an EHR. Wide adoption of an EHR in sub-Saharan Africa region requires a lot more effort than what is assumed because of the current poor level of technological development, lack of required computer skills, and limited resources. PMID:29085270

Creating an Oversight Infrastructure for Electronic Health Record-Related Patient Safety Hazards

PubMed Central

Singh, Hardeep; Classen, David C.; Sittig, Dean F.

2013-01-01

Electronic health records (EHRs) have potential quality and safety benefits. However, reports of EHR-related safety hazards are now emerging. The Office of the National Coordinator (ONC) for Health Information Technology (HIT) recently sponsored an Institute of Medicine committee to evaluate how HIT use affects patient safety. In this paper, we propose the creation of a national EHR oversight program to provide dedicated surveillance of EHR-related safety hazards and to promote learning from identified errors, close calls, and adverse events. The program calls for data gathering, investigation/analysis and regulatory components. The first two functions will depend on institution-level EHR safety committees that will investigate all known EHR-related adverse events and near-misses and report them nationally using standardized methods. These committees should also perform routine safety self-assessments to proactively identify new risks. Nationally, we propose the long-term creation of a centralized, non-partisan board with an appropriate legal and regulatory infrastructure to ensure the safety of EHRs. We discuss the rationale of the proposed oversight program and its potential organizational components and functions. These include mechanisms for robust data collection and analyses of all safety concerns using multiple methods that extend beyond reporting; multidisciplinary investigation of selected high-risk safety events; and enhanced coordination with other national agencies in order to facilitate broad dissemination of hazards information. Implementation of this proposed infrastructure can facilitate identification of EHR-related adverse events and errors and potentially create a safer and more effective EHR-based health care delivery system. PMID:22080284

Electronic Health Record-Related Safety Concerns: A Cross-Sectional Survey of Electronic Health Record Users

PubMed Central

Pajunen, Tuuli; Saranto, Kaija; Lehtonen, Lasse

2016-01-01

Background The rapid expansion in the use of electronic health records (EHR) has increased the number of medical errors originating in health information systems (HIS). The sociotechnical approach helps in understanding risks in the development, implementation, and use of EHR and health information technology (HIT) while accounting for complex interactions of technology within the health care system. Objective This study addresses two important questions: (1) “which of the common EHR error types are associated with perceived high- and extreme-risk severity ratings among EHR users?”, and (2) “which variables are associated with high- and extreme-risk severity ratings?” Methods This study was a quantitative, non-experimental, descriptive study of EHR users. We conducted a cross-sectional web-based questionnaire study at the largest hospital district in Finland. Statistical tests included the reliability of the summative scales tested with Cronbach’s alpha. Logistic regression served to assess the association of the independent variables to each of the eight risk factors examined. Results A total of 2864 eligible respondents provided the final data. Almost half of the respondents reported a high level of risk related to the error type “extended EHR unavailability”. The lowest overall risk level was associated with “selecting incorrectly from a list of items”. In multivariate analyses, profession and clinical unit proved to be the strongest predictors for high perceived risk. Physicians perceived risk levels to be the highest (P<.001 in six of eight error types), while emergency departments, operating rooms, and procedure units were associated with higher perceived risk levels (P<.001 in four of eight error types). Previous participation in eLearning courses on EHR-use was associated with lower risk for some of the risk factors. Conclusions Based on a large number of Finnish EHR users in hospitals, this study indicates that HIT safety hazards should be taken very seriously, particularly in operating rooms, procedure units, emergency departments, and intensive care units/critical care units. Health care organizations should use proactive and systematic assessments of EHR risks before harmful events occur. An EHR training program should be compulsory for all EHR users in order to address EHR safety concerns resulting from the failure to use HIT appropriately. PMID:27154599

Impact of Electronic Health Records on Long-Term Care Facilities: Systematic Review.

PubMed

Kruse, Clemens Scott; Mileski, Michael; Vijaykumar, Alekhya Ganta; Viswanathan, Sneha Vishnampet; Suskandla, Ujwala; Chidambaram, Yazhini

2017-09-29

Long-term care (LTC) facilities are an important part of the health care industry, providing care to the fastest-growing group of the population. However, the adoption of electronic health records (EHRs) in LTC facilities lags behind other areas of the health care industry. One of the reasons for the lack of widespread adoption in the United States is that LTC facilities are not eligible for incentives under the Meaningful Use program. Implementation of an EHR system in an LTC facility can potentially enhance the quality of care, provided it is appropriately implemented, used, and maintained. Unfortunately, the lag in adoption of the EHR in LTC creates a paucity of literature on the benefits of EHR implementation in LTC facilities. The objective of this systematic review was to identify the potential benefits of implementing an EHR system in LTC facilities. The study also aims to identify the common conditions and EHR features that received favorable remarks from providers and the discrepancies that needed improvement to build up momentum across LTC settings in adopting this technology. The authors conducted a systematic search of PubMed, Cumulative Index of Nursing and Allied Health (CINAHL), and MEDLINE databases. Papers were analyzed by multiple referees to filter out studies not germane to our research objective. A final sample of 28 papers was selected to be included in the systematic review. Results of this systematic review conclude that EHRs show significant improvement in the management of documentation in LTC facilities and enhanced quality outcomes. Approximately 43% (12/28) of the papers reported a mixed impact of EHRs on the management of documentation, and 33% (9/28) of papers reported positive quality outcomes using EHRs. Surprisingly, very few papers demonstrated an impact on patient satisfaction, physician satisfaction, the length of stay, and productivity using EHRs. Overall, implementation of EHRs has been found to be effective in the few LTC facilities that have implemented them. Implementation of EHRs in LTC facilities caused improved management of clinical documentation that enabled better decision making. ©Clemens Scott Kruse, Michael Mileski, Alekhya Ganta Vijaykumar, Sneha Vishnampet Viswanathan, Ujwala Suskandla, Yazhini Chidambaram. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 29.09.2017.

A qualitative evaluation of the crucial attributes of contextual information necessary in EHR design to support patient-centered medical home care.

PubMed

Weir, Charlene R; Staggers, Nancy; Gibson, Bryan; Doing-Harris, Kristina; Barrus, Robyn; Dunlea, Robert

2015-04-16

Effective implementation of a Primary Care Medical Home model of care (PCMH) requires integration of patients' contextual information (physical, mental, social and financial status) into an easily retrievable information source for the healthcare team and clinical decision-making. This project explored clinicians' perceptions about important attributes of contextual information for clinical decision-making, how contextual information is expressed in CPRS clinical documentation as well as how clinicians in a highly computerized environment manage information flow related to these areas. A qualitative design using Cognitive Task Analyses and a modified Critical Incident Technique were used. The study was conducted in a large VA with a fully implemented EHR located in the western United States. Seventeen providers working in a PCMH model of care in Primary Care, Home Based Care and Geriatrics reported on a recent difficult transition requiring contextual information for decision-making. The transcribed interviews were qualitatively analyzed for thematic development related to contextual information using an iterative process and multiple reviewers with ATLAS@ti software. Six overarching themes emerged as attributes of contextual information: Informativeness, goal language, temporality, source attribution, retrieval effort, and information quality. These results indicate that specific attributes are needed to in order for contextual information to fully support clinical decision-making in a Medical Home care delivery environment. Improved EHR designs are needed for ease of contextual information access, displaying linkages across time and settings, and explicit linkages to both clinician and patient goals. Implications relevant to providers' information needs, team functioning and EHR design are discussed.

The Readmission Risk Flag: Using the Electronic Health Record to Automatically Identify Patients at Risk for 30-day Readmission

PubMed Central

Baillie, Charles A.; VanZandbergen, Christine; Tait, Gordon; Hanish, Asaf; Leas, Brian; French, Benjamin; Hanson, C. William; Behta, Maryam; Umscheid, Craig A.

2015-01-01

Background Identification of patients at high risk for readmission is a crucial step toward improving care and reducing readmissions. The adoption of electronic health records (EHR) may prove important to strategies designed to risk stratify patients and introduce targeted interventions. Objective To develop and implement an automated prediction model integrated into our health system’s EHR that identifies on admission patients at high risk for readmission within 30 days of discharge. Design Retrospective and prospective cohort. Setting Healthcare system consisting of three hospitals. Patients All adult patients admitted from August 2009 to September 2012. Interventions An automated readmission risk flag integrated into the EHR. Measures Thirty-day all-cause and 7-day unplanned healthcare system readmissions. Results Using retrospective data, a single risk factor, ≥2 inpatient admissions in the past 12 months, was found to have the best balance of sensitivity (40%), positive predictive value (31%), and proportion of patients flagged (18%), with a c-statistic of 0.62. Sensitivity (39%), positive predictive value (30%), proportion of patients flagged (18%) and c-statistic (0.61) during the 12-month period after implementation of the risk flag were similar. There was no evidence for an effect of the intervention on 30-day all-cause and 7-day unplanned readmission rates in the 12-month period after implementation. Conclusions An automated prediction model was effectively integrated into an existing EHR and identified patients on admission who were at risk for readmission within 30 days of discharge. PMID:24227707

Deep Learning from EEG Reports for Inferring Underspecified Information

PubMed Central

Goodwin, Travis R.; Harabagiu, Sanda M.

2017-01-01

Secondary use1of electronic health records (EHRs) often relies on the ability to automatically identify and extract information from EHRs. Unfortunately, EHRs are known to suffer from a variety of idiosyncrasies – most prevalently, they have been shown to often omit or underspecify information. Adapting traditional machine learning methods for inferring underspecified information relies on manually specifying features characterizing the specific information to recover (e.g. particular findings, test results, or physician’s impressions). By contrast, in this paper, we present a method for jointly (1) automatically extracting word- and report-level features and (2) inferring underspecified information from EHRs. Our approach accomplishes these two tasks jointly by combining recent advances in deep neural learning with access to textual data in electroencephalogram (EEG) reports. We evaluate the performance of our model on the problem of inferring the neurologist’s over-all impression (normal or abnormal) from electroencephalogram (EEG) reports and report an accuracy of 91.4% precision of 94.4% recall of 91.2% and F1 measure of 92.8% (a 40% improvement over the performance obtained using Doc2Vec). These promising results demonstrate the power of our approach, while error analysis reveals remaining obstacles as well as areas for future improvement. PMID:28815118

Improving Care Transitions Management: Examining the Role of Accountable Care Organization Participation and Expanded Electronic Health Record Functionality.

PubMed

Huber, Thomas P; Shortell, Stephen M; Rodriguez, Hector P

2017-08-01

Examine the extent to which physician organization participation in an accountable care organization (ACO) and electronic health record (EHR) functionality are associated with greater adoption of care transition management (CTM) processes. A total of 1,398 physician organizations from the third National Study of Physician Organization survey (NSPO3), a nationally representative sample of medical practices in the United States (January 2012-May 2013). We used data from the third National Study of Physician Organization survey (NSPO3) to assess medical practice characteristics, including CTM processes, ACO participation, EHR functionality, practice type, organization size, ownership, public reporting, and pay-for-performance participation. Multivariate linear regression models estimated the extent to which ACO participation and EHR functionality were associated with greater CTM capabilities, controlling for practice size, ownership, public reporting, and pay-for-performance participation. Approximately half (52.4 percent) of medical practices had a formal program for managing care transitions in place. In adjusted analyses, ACO participation (p < .001) and EHR functionality (p < .001) were independently associated with greater use of CTM processes among medical practices. The growth of ACOs and similar provider risk-bearing arrangements across the country may improve the management of care transitions by physician organizations. © Health Research and Educational Trust.

Reasons (Not) to Spend a Few Billions More on EHRs: How Human Factors Research Can Help

PubMed Central

Aimé, X.

2014-01-01

Summary Objectives To select best medical informatics research works published in 2013 on electronic health record (EHR) adoption, design, and impact, from the perspective of human factors and organizational issues (HFOI). Methods We selected 2,764 papers by querying PubMed (Mesh and TIAB) as well as using a manual search. Papers were evaluated based on pre-defined exclusion and inclusion criteria from their title, keywords, and abstract to select 15 candidate best papers, finally reviewed by 4 external reviewers using a standard evaluation grid. Results Five papers were selected as best papers to illustrate how human factors approaches can improve EHR adoption and design. Among other contributions, these works: (i) make use of the observational and analysis methodologies of social and cognitive sciences to understand clinicians’ attitudes towards EHRs, EHR use patterns, and impact on care processes, workflows, information exchange, and coordination of care; (ii) take into account macro- (environmental) and meso- (organizational) level factors to analyze EHR adoption or lack thereof; (iii) highlight the need for qualitative studies to analyze the unexpected side effects of EHRs on cognitive and work processes as well as the persistent use of paper. Conclusion Selected papers tend to demonstrate that HFOI approaches and methodologies are essential to bridge the gap between EHR systems and end users, and to reduce regularly reported adoption failures and unexpected consequences. PMID:25123727

Leveraging electronic health records for clinical research.

PubMed

Raman, Sudha R; Curtis, Lesley H; Temple, Robert; Andersson, Tomas; Ezekowitz, Justin; Ford, Ian; James, Stefan; Marsolo, Keith; Mirhaji, Parsa; Rocca, Mitra; Rothman, Russell L; Sethuraman, Barathi; Stockbridge, Norman; Terry, Sharon; Wasserman, Scott M; Peterson, Eric D; Hernandez, Adrian F

2018-04-30

Electronic health records (EHRs) can be a major tool in the quest to decrease costs and timelines of clinical trial research, generate better evidence for clinical decision making, and advance health care. Over the past decade, EHRs have increasingly offered opportunities to speed up, streamline, and enhance clinical research. EHRs offer a wide range of possible uses in clinical trials, including assisting with prestudy feasibility assessment, patient recruitment, and data capture in care delivery. To fully appreciate these opportunities, health care stakeholders must come together to face critical challenges in leveraging EHR data, including data quality/completeness, information security, stakeholder engagement, and increasing the scale of research infrastructure and related governance. Leaders from academia, government, industry, and professional societies representing patient, provider, researcher, industry, and regulator perspectives convened the Leveraging EHR for Clinical Research Now! Think Tank in Washington, DC (February 18-19, 2016), to identify barriers to using EHRs in clinical research and to generate potential solutions. Think tank members identified a broad range of issues surrounding the use of EHRs in research and proposed a variety of solutions. Recognizing the challenges, the participants identified the urgent need to look more deeply at previous efforts to use these data, share lessons learned, and develop a multidisciplinary agenda for best practices for using EHRs in clinical research. We report the proceedings from this think tank meeting in the following paper. Copyright © 2018 Elsevier, Inc. All rights reserved.

Reasons (not) to Spend a Few Billions More on EHRs: How Human Factors Research Can Help.

PubMed

Declerck, G; Aimé, X

2014-08-15

To select best medical informatics research works published in 2013 on electronic health record (EHR) adoption, design, and impact, from the perspective of human factors and organizational issues (HFOI). We selected 2,764 papers by querying PubMed (Mesh and TIAB) as well as using a manual search. Papers were evaluated based on pre-defined exclusion and inclusion criteria from their title, keywords, and abstract to select 15 candidate best papers, finally reviewed by 4 external reviewers using a standard evaluation grid. Five papers were selected as best papers to illustrate how human factors approaches can improve EHR adoption and design. Among other contributions, these works: (i) make use of the observational and analysis methodologies of social and cognitive sciences to understand clinicians' attitudes towards EHRs, EHR use patterns, and impact on care processes, workflows, information exchange, and coordination of care; (ii) take into account macro- (environmental) and meso- (organizational) level factors to analyze EHR adoption or lack thereof; (iii) highlight the need for qualitative studies to analyze the unexpected side effects of EHRs on cognitive and work processes as well as the persistent use of paper. Selected papers tend to demonstrate that HFOI approaches and methodologies are essential to bridge the gap between EHR systems and end users, and to reduce regularly reported adoption failures and unexpected consequences.

The Borg scale as an important tool of self-monitoring and self-regulation of exercise prescription in heart failure patients during hydrotherapy. A randomized blinded controlled trial.

PubMed

Carvalho, Vitor Oliveira; Bocchi, Edimar Alcides; Guimarães, Guilherme Veiga

2009-10-01

The Borg Scale may be a useful tool for heart failure patients to self-monitor and self-regulate exercise on land or in water (hydrotherapy) by maintaining the heart rate (HR) between the anaerobic threshold and respiratory compensation point. Patients performed a cardiopulmonary exercise test to determine their anaerobic threshold/respiratory compensation points. The percentage of the mean HR during the exercise session in relation to the anaerobic threshold HR (%EHR-AT), in relation to the respiratory compensation point (%EHR-RCP), in relation to the peak HR by the exercise test (%EHR-Peak) and in relation to the maximum predicted HR (%EHR-Predicted) was calculated. Next, patients were randomized into the land or water exercise group. One blinded investigator instructed the patients in each group to exercise at a level between "relatively easy and slightly tiring". The mean HR throughout the 30-min exercise session was recorded. The %EHR-AT and %EHR-predicted did not differ between the land and water exercise groups, but they differed in the %EHR-RCP (95 +/-7 to 86 +/-7, P<0.001) and in the %EHR-Peak (85 +/-8 to 78 +/-9, P=0.007). Exercise guided by the Borg scale maintains the patient's HR between the anaerobic threshold and respiratory compensation point (ie, in the exercise training zone).