Applying semantic web technologies for phenome-wide scan using an electronic health record linked Biobank

PubMed Central

2012-01-01

Background The ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. However, historically GWAS have been limited by inadequate sample size due to associated costs for genotyping and phenotyping of study subjects. This has prompted several academic medical centers to form “biobanks” where biospecimens linked to personal health information, typically in electronic health records (EHRs), are collected and stored on a large number of subjects. This provides tremendous opportunities to discover novel genotype-phenotype associations and foster hypotheses generation. Results In this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical and genotype data stored at the Mayo Clinic Biobank to mine the phenotype data for genetic associations. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR diagnoses and procedure data, and enable federated querying via standardized Web protocols to identify subjects genotyped for Type 2 Diabetes and Hypothyroidism to discover gene-disease associations. Our study highlights the potential of Web-scale data federation techniques to execute complex queries. Conclusions This study demonstrates how Semantic Web technologies can be applied in conjunction with clinical data stored in EHRs to accurately identify subjects with specific diseases and phenotypes, and identify genotype-phenotype associations. PMID:23244446

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.

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

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.

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.

Grid-based implementation of XDS-I as part of image-enabled EHR for regional healthcare in Shanghai.

PubMed

Zhang, Jianguo; Zhang, Kai; Yang, Yuanyuan; Sun, Jianyong; Ling, Tonghui; Wang, Guangrong; Ling, Yun; Peng, Derong

2011-03-01

Due to the rapid growth of Shanghai city to 20 million residents, the balance between healthcare supply and demand has become an important issue. The local government hopes to ameliorate this problem by developing an image-enabled electronic healthcare record (EHR) sharing mechanism between certain hospitals. This system is designed to enable healthcare collaboration and reduce healthcare costs by allowing review of prior examination data obtained at other hospitals. Here, we present a design method and implementation solution of image-enabled EHRs (i-EHRs) and describe the implementation of i-EHRs in four hospitals and one regional healthcare information center, as well as their preliminary operating results. We designed the i-EHRs with service-oriented architecture (SOA) and combined the grid-based image management and distribution capability, which are compliant with IHE XDS-I integration profile. There are seven major components and common services included in the i-EHRs. In order to achieve quick response for image retrieving in low-bandwidth network environments, we use a JPEG2000 interactive protocol and progressive display technique to transmit images from a Grid Agent as Imaging Source Actor to the PACS workstation as Imaging Consumer Actor. The first phase of pilot testing of our image-enabled EHR was implemented in the Zhabei district of Shanghai for imaging document sharing and collaborative diagnostic purposes. The pilot testing began in October 2009; there have been more than 50 examinations daily transferred between the City North Hospital and the three community hospitals for collaborative diagnosis. The feedback from users at all hospitals is very positive, with respondents stating the system to be easy to use and reporting no interference with their normal radiology diagnostic operation. The i-EHR system can provide event-driven automatic image delivery for collaborative imaging diagnosis across multiple hospitals based on work flow requirements. This project demonstrated that the grid-based implementation of IHE XDS-I for image-enabled EHR could scale effectively to serve a regional healthcare solution with collaborative imaging services. The feedback from users of community hospitals and large hospital is very positive.

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.

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.

Health care transformation through collaboration on open-source informatics projects: integrating a medical applications platform, research data repository, and patient summarization.

PubMed

Klann, Jeffrey G; McCoy, Allison B; Wright, Adam; Wattanasin, Nich; Sittig, Dean F; Murphy, Shawn N

2013-05-30

The Strategic Health IT Advanced Research Projects (SHARP) program seeks to conquer well-understood challenges in medical informatics through breakthrough research. Two SHARP centers have found alignment in their methodological needs: (1) members of the National Center for Cognitive Informatics and Decision-making (NCCD) have developed knowledge bases to support problem-oriented summarizations of patient data, and (2) Substitutable Medical Apps, Reusable Technologies (SMART), which is a platform for reusable medical apps that can run on participating platforms connected to various electronic health records (EHR). Combining the work of these two centers will ensure wide dissemination of new methods for synthesized views of patient data. Informatics for Integrating Biology and the Bedside (i2b2) is an NIH-funded clinical research data repository platform in use at over 100 sites worldwide. By also working with a co-occurring initiative to SMART-enabling i2b2, we can confidently write one app that can be used extremely broadly. Our goal was to facilitate development of intuitive, problem-oriented views of the patient record using NCCD knowledge bases that would run in any EHR. To do this, we developed a collaboration between the two SHARPs and an NIH center, i2b2. First, we implemented collaborative tools to connect researchers at three institutions. Next, we developed a patient summarization app using the SMART platform and a previously validated NCCD problem-medication linkage knowledge base derived from the National Drug File-Reference Terminology (NDF-RT). Finally, to SMART-enable i2b2, we implemented two new Web service "cells" that expose the SMART application programming interface (API), and we made changes to the Web interface of i2b2 to host a "carousel" of SMART apps. We deployed our SMART-based, NDF-RT-derived patient summarization app in this SMART-i2b2 container. It displays a problem-oriented view of medications and presents a line-graph display of laboratory results. This summarization app can be run in any EHR environment that either supports SMART or runs SMART-enabled i2b2. This i2b2 "clinical bridge" demonstrates a pathway for reusable app development that does not require EHR vendors to immediately adopt the SMART API. Apps can be developed in SMART and run by clinicians in the i2b2 repository, reusing clinical data extracted from EHRs. This may encourage the adoption of SMART by supporting SMART app development until EHRs adopt the platform. It also allows a new variety of clinical SMART apps, fueled by the broad aggregation of data types available in research repositories. The app (including its knowledge base) and SMART-i2b2 are open-source and freely available for download.

Analysis of the process of representing clinical statements for decision-support applications: a comparison of openEHR archetypes and HL7 virtual medical record.

PubMed

González-Ferrer, A; Peleg, M; Marcos, M; Maldonado, J A

2016-07-01

Delivering patient-specific decision-support based on computer-interpretable guidelines (CIGs) requires mapping CIG clinical statements (data items, clinical recommendations) into patients' data. This is most effectively done via intermediate data schemas, which enable querying the data according to the semantics of a shared standard intermediate schema. This study aims to evaluate the use of HL7 virtual medical record (vMR) and openEHR archetypes as intermediate schemas for capturing clinical statements from CIGs that are mappable to electronic health records (EHRs) containing patient data and patient-specific recommendations. Using qualitative research methods, we analyzed the encoding of ten representative clinical statements taken from two CIGs used in real decision-support systems into two health information models (openEHR archetypes and HL7 vMR instances) by four experienced informaticians. Discussion among the modelers about each case study example greatly increased our understanding of the capabilities of these standards, which we share in this educational paper. Differing in content and structure, the openEHR archetypes were found to contain a greater level of representational detail and structure while the vMR representations took fewer steps to complete. The use of openEHR in the encoding of CIG clinical statements could potentially facilitate applications other than decision-support, including intelligent data analysis and integration of additional properties of data items from existing EHRs. On the other hand, due to their smaller size and fewer details, the use of vMR potentially supports quicker mapping of EHR data into clinical statements.

Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility.

PubMed

Marcos, Mar; Maldonado, Jose A; Martínez-Salvador, Begoña; Boscá, Diego; Robles, Montserrat

2013-08-01

Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support patient recruitment in the framework of a clinical trial for colorectal cancer screening. The utilisation of archetypes not only has proved satisfactory to achieve interoperability between CDSSs and EHRs but also offers various advantages, in particular from a data model perspective. First, the VHR/data models we work with are of a high level of abstraction and can incorporate semantic descriptions. Second, archetypes can potentially deal with different EHR architectures, due to their deliberate independence of the reference model. Third, the archetype instances we obtain are valid instances of the underlying reference model, which would enable e.g. feeding back the EHR with data derived by abstraction mechanisms. Lastly, the medical and technical validity of archetype models would be assured, since in principle clinicians should be the main actors in their development. Copyright © 2013 Elsevier Inc. All rights reserved.

Implementation of an Electronic Health Records System in a Small Clinic: The Viewpoint of Clinic Staff

ERIC Educational Resources Information Center

Carayon, Pascale; Smith, Paul; Hundt, Ann Schoofs; Kuruchittham, Vipat; Li, Qian

2009-01-01

In this study, we examined the implementation of an electronic health records (EHR) system in a small family practice clinic. We used three data collection instruments to evaluate user experience, work pattern changes, and organisational changes related to the implementation and use of the EHR system: (1) an EHR user survey, (2) interviews with…

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

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

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.

Common data elements for substance use disorders in electronic health records: the NIDA Clinical Trials Network experience.

PubMed

Ghitza, Udi E; Gore-Langton, Robert E; Lindblad, Robert; Shide, David; Subramaniam, Geetha; Tai, Betty

2013-01-01

Electronic health records (EHRs) are essential in improving quality and enhancing efficiency of health-care delivery. By 2015, medical care receiving service reimbursement from US Centers for Medicare and Medicaid Services (CMS) must show 'meaningful use' of EHRs. Substance use disorders (SUD) are grossly under-detected and under-treated in current US medical care settings. Hence, an urgent need exists for improved identification of and clinical intervention for SUD in medical settings. The National Institute on Drug Abuse Clinical Trials Network (NIDA CTN) has leveraged its infrastructure and expertise and brought relevant stakeholders together to develop consensus on brief screening and initial assessment tools for SUD in general medical settings, with the objective of incorporation into US EHRs. Stakeholders were identified and queried for input and consensus on validated screening and assessment for SUD in general medical settings to develop common data elements to serve as shared resources for EHRs on screening, brief intervention and referral to treatment (SBIRT), with the intent of supporting interoperability and data exchange in a developing Nationwide Health Information Network. Through consensus of input from stakeholders, a validated screening and brief assessment instrument, supported by Clinical Decision Support tools, was chosen to be used at out-patient general medical settings. The creation and adoption of a core set of validated common data elements and the inclusion of such consensus-based data elements for general medical settings will enable the integration of SUD treatment within mainstream health care, and support the adoption and 'meaningful use' of the US Office of the National Coordinator for Health Information Technology (ONC)-certified EHRs, as well as CMS reimbursement. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Mining the Human Phenome using Semantic Web Technologies: A Case Study for Type 2 Diabetes

PubMed Central

Pathak, Jyotishman; Kiefer, Richard C.; Bielinski, Suzette J.; Chute, Christopher G.

2012-01-01

The ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. However, historically GWAS have been limited by inadequate sample size due to associated costs for genotyping and phenotyping of study subjects. This has prompted several academic medical centers to form “biobanks” where biospecimens linked to personal health information, typically in electronic health records (EHRs), are collected and stored on large number of subjects. This provides tremendous opportunities to discover novel genotype-phenotype associations and foster hypothesis generation. In this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical and genotype data stored at the Mayo Clinic Biobank to mine the phenotype data for genetic associations. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR diagnoses and procedure data, and enable federated querying via standardized Web protocols to identify subjects genotyped with Type 2 Diabetes for discovering gene-disease associations. Our study highlights the potential of Web-scale data federation techniques to execute complex queries. PMID:23304343

Mining the human phenome using semantic web technologies: a case study for Type 2 Diabetes.

PubMed

Pathak, Jyotishman; Kiefer, Richard C; Bielinski, Suzette J; Chute, Christopher G

2012-01-01

The ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. However, historically GWAS have been limited by inadequate sample size due to associated costs for genotyping and phenotyping of study subjects. This has prompted several academic medical centers to form "biobanks" where biospecimens linked to personal health information, typically in electronic health records (EHRs), are collected and stored on large number of subjects. This provides tremendous opportunities to discover novel genotype-phenotype associations and foster hypothesis generation. In this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical and genotype data stored at the Mayo Clinic Biobank to mine the phenotype data for genetic associations. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR diagnoses and procedure data, and enable federated querying via standardized Web protocols to identify subjects genotyped with Type 2 Diabetes for discovering gene-disease associations. Our study highlights the potential of Web-scale data federation techniques to execute complex queries.

Physicians' perceptions of the impact of the EHR on the collection and retrieval of psychosocial information in outpatient diabetes care.

PubMed

Senteio, Charles; Veinot, Tiffany; Adler-Milstein, Julia; Richardson, Caroline

2018-05-01

Psychosocial information informs clinical decisions by providing crucial context for patients' barriers to recommended self-care; this is especially important in outpatient diabetes care because outcomes are largely dependent upon self-care behavior. Little is known about provider perceptions of use of psychosocial information. Further, while EHRs have dramatically changed how providers interact with patient health information, the EHRs' role in collection and retrieval of psychosocial information is not understood. We designed a qualitative study. We used semi-structured interviews to investigate physicians' (N = 17) perspectives on the impact of EHR for psychosocial information use for outpatient Type II diabetes care decisions. We selected the constant comparative method to analyze the data. Psychosocial information is perceived as dissimilar from other clinical information such as HbA1c and prescribed medications. Its narrative form conveys the patient's story, which elucidates barriers to following self-care recommendations. The narrative is abstract, and requires interpretation of patterns. Psychosocial information is also circumstantial; hence, the patients' context determines influence on self-care. Furthermore, EHRs can impair the collection of psychosocial information because the designs of EHR tools make it difficult to document, search for, and retrieve it. Templates do not enable users from collecting the patient's 'story', and using free text fields is time consuming. Providers therefore had low use of, and confidence in, the accuracy of psychosocial information in the EHR. Workflows and EHR tools should be re-designed to better support psychosocial information collection and retrieval. Tools should enable recording and summarization of the patient's story, and the rationale for treatment decisions. Copyright © 2018 Elsevier B.V. All rights reserved.

Toward a Learning Health-care System – Knowledge Delivery at the Point of Care Empowered by Big Data and NLP

PubMed Central

Kaggal, Vinod C.; Elayavilli, Ravikumar Komandur; Mehrabi, Saeed; Pankratz, Joshua J.; Sohn, Sunghwan; Wang, Yanshan; Li, Dingcheng; Rastegar, Majid Mojarad; Murphy, Sean P.; Ross, Jason L.; Chaudhry, Rajeev; Buntrock, James D.; Liu, Hongfang

2016-01-01

The concept of optimizing health care by understanding and generating knowledge from previous evidence, ie, the Learning Health-care System (LHS), has gained momentum and now has national prominence. Meanwhile, the rapid adoption of electronic health records (EHRs) enables the data collection required to form the basis for facilitating LHS. A prerequisite for using EHR data within the LHS is an infrastructure that enables access to EHR data longitudinally for health-care analytics and real time for knowledge delivery. Additionally, significant clinical information is embedded in the free text, making natural language processing (NLP) an essential component in implementing an LHS. Herein, we share our institutional implementation of a big data-empowered clinical NLP infrastructure, which not only enables health-care analytics but also has real-time NLP processing capability. The infrastructure has been utilized for multiple institutional projects including the MayoExpertAdvisor, an individualized care recommendation solution for clinical care. We compared the advantages of big data over two other environments. Big data infrastructure significantly outperformed other infrastructure in terms of computing speed, demonstrating its value in making the LHS a possibility in the near future. PMID:27385912

Toward a Learning Health-care System - Knowledge Delivery at the Point of Care Empowered by Big Data and NLP.

PubMed

Kaggal, Vinod C; Elayavilli, Ravikumar Komandur; Mehrabi, Saeed; Pankratz, Joshua J; Sohn, Sunghwan; Wang, Yanshan; Li, Dingcheng; Rastegar, Majid Mojarad; Murphy, Sean P; Ross, Jason L; Chaudhry, Rajeev; Buntrock, James D; Liu, Hongfang

2016-01-01

The concept of optimizing health care by understanding and generating knowledge from previous evidence, ie, the Learning Health-care System (LHS), has gained momentum and now has national prominence. Meanwhile, the rapid adoption of electronic health records (EHRs) enables the data collection required to form the basis for facilitating LHS. A prerequisite for using EHR data within the LHS is an infrastructure that enables access to EHR data longitudinally for health-care analytics and real time for knowledge delivery. Additionally, significant clinical information is embedded in the free text, making natural language processing (NLP) an essential component in implementing an LHS. Herein, we share our institutional implementation of a big data-empowered clinical NLP infrastructure, which not only enables health-care analytics but also has real-time NLP processing capability. The infrastructure has been utilized for multiple institutional projects including the MayoExpertAdvisor, an individualized care recommendation solution for clinical care. We compared the advantages of big data over two other environments. Big data infrastructure significantly outperformed other infrastructure in terms of computing speed, demonstrating its value in making the LHS a possibility in the near future.

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.

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.

Allocation of Physician Time in Ambulatory Practice: A Time and Motion Study in 4 Specialties.

PubMed

Sinsky, Christine; Colligan, Lacey; Li, Ling; Prgomet, Mirela; Reynolds, Sam; Goeders, Lindsey; Westbrook, Johanna; Tutty, Michael; Blike, George

2016-12-06

Little is known about how physician time is allocated in ambulatory care. To describe how physician time is spent in ambulatory practice. Quantitative direct observational time and motion study (during office hours) and self-reported diary (after hours). U.S. ambulatory care in 4 specialties in 4 states (Illinois, New Hampshire, Virginia, and Washington). 57 U.S. physicians in family medicine, internal medicine, cardiology, and orthopedics who were observed for 430 hours, 21 of whom also completed after-hours diaries. Proportions of time spent on 4 activities (direct clinical face time, electronic health record [EHR] and desk work, administrative tasks, and other tasks) and self-reported after-hours work. During the office day, physicians spent 27.0% of their total time on direct clinical face time with patients and 49.2% of their time on EHR and desk work. While in the examination room with patients, physicians spent 52.9% of the time on direct clinical face time and 37.0% on EHR and desk work. The 21 physicians who completed after-hours diaries reported 1 to 2 hours of after-hours work each night, devoted mostly to EHR tasks. Data were gathered in self-selected, high-performing practices and may not be generalizable to other settings. The descriptive study design did not support formal statistical comparisons by physician and practice characteristics. For every hour physicians provide direct clinical face time to patients, nearly 2 additional hours is spent on EHR and desk work within the clinic day. Outside office hours, physicians spend another 1 to 2 hours of personal time each night doing additional computer and other clerical work. American Medical Association.

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.

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

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

Informatics and operations--let's get integrated.

PubMed

Marsolo, Keith

2013-01-01

The widespread adoption of commercial electronic health records (EHRs) presents a significant challenge to the field of informatics. In their current form, EHRs function as a walled garden and prevent the integration of outside tools and services. This impedes the widespread adoption and diffusion of research interventions into the clinic. In most institutions, EHRs are supported by clinical operations staff who are largely separate from their informatics counterparts. This relationship needs to change. Research informatics and clinical operations need to work more closely on the implementation and configuration of EHRs to ensure that they are used to collect high-quality data for research and improvement at the point of care. At the same time, the informatics community needs to lobby commercial EHR vendors to open their systems and design new architectures that allow for the integration of external applications and services.

Evaluation of Electronic Health Record Implementation in Ophthalmology at an Academic Medical Center (An American Ophthalmological Society Thesis)

PubMed Central

Chiang, Michael F.; Read-Brown, Sarah; Tu, Daniel C.; Choi, Dongseok; Sanders, David S.; Hwang, Thomas S.; Bailey, Steven; Karr, Daniel J.; Cottle, Elizabeth; Morrison, John C.; Wilson, David J.; Yackel, Thomas R.

2013-01-01

Purpose: To evaluate three measures related to electronic health record (EHR) implementation: clinical volume, time requirements, and nature of clinical documentation. Comparison is made to baseline paper documentation. Methods: An academic ophthalmology department implemented an EHR in 2006. A study population was defined of faculty providers who worked the 5 months before and after implementation. Clinical volumes, as well as time length for each patient encounter, were collected from the EHR reporting system. To directly compare time requirements, two faculty providers who utilized both paper and EHR systems completed time-motion logs to record the number of patients, clinic time, and nonclinic time to complete documentation. Faculty providers and databases were queried to identify patient records containing both paper and EHR notes, from which three cases were identified to illustrate representative documentation differences. Results: Twenty-three faculty providers completed 120,490 clinical encounters during a 3-year study period. Compared to baseline clinical volume from 3 months pre-implementation, the post-implementation volume was 88% in quarter 1, 93% in year 1, 97% in year 2, and 97% in year 3. Among all encounters, 75% were completed within 1.7 days after beginning documentation. The mean total time per patient was 6.8 minutes longer with EHR than paper (P<.01). EHR documentation involved greater reliance on textual interpretation of clinical findings, whereas paper notes used more graphical representations, and EHR notes were longer and included automatically generated text. Conclusion: This EHR implementation was associated with increased documentation time, little or no increase in clinical volume, and changes in the nature of ophthalmic documentation. PMID:24167326

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.

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.

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.

The Influence of Big (Clinical) Data and Genomics on Precision Medicine and Drug Development.

PubMed

Denny, Joshua C; Van Driest, Sara L; Wei, Wei-Qi; Roden, Dan M

2018-03-01

Drug development continues to be costly and slow, with medications failing due to lack of efficacy or presence of toxicity. The promise of pharmacogenomic discovery includes tailoring therapeutics based on an individual's genetic makeup, rational drug development, and repurposing medications. Rapid growth of large research cohorts, linked to electronic health record (EHR) data, fuels discovery of new genetic variants predicting drug action, supports Mendelian randomization experiments to show drug efficacy, and suggests new indications for existing medications. New biomedical informatics and machine-learning approaches advance the ability to interpret clinical information, enabling identification of complex phenotypes and subpopulations of patients. We review the recent history of use of "big data" from EHR-based cohorts and biobanks supporting these activities. Future studies using EHR data, other information sources, and new methods will promote a foundation for discovery to more rapidly advance precision medicine. © 2017 American Society for Clinical Pharmacology and Therapeutics.

Prototype of a Standards-Based EHR and Genetic Test Reporting Tool Coupled with HL7-Compliant Infobuttons

PubMed Central

Crump, Jacob K.; Del Fiol, Guilherme; Williams, Marc S.; Freimuth, Robert R.

2018-01-01

Integration of genetic information is becoming increasingly important in clinical practice. However, genetic information is often ambiguous and difficult to understand, and clinicians have reported low-self-efficacy in integrating genetics into their care routine. The Health Level Seven (HL7) Infobutton standard helps to integrate online knowledge resources within Electronic Health Records (EHRs) and is required for EHR certification in the US. We implemented a prototype of a standards-based genetic reporting application coupled with infobuttons leveraging the Infobutton and Fast Healthcare Interoperability Resources (FHIR) Standards. Infobutton capabilities were provided by Open Infobutton, an open source package compliant with the HL7 Infobutton Standard. The resulting prototype demonstrates how standards-based reporting of genetic results, coupled with curated knowledge resources, can provide dynamic access to clinical knowledge on demand at the point of care. The proposed functionality can be enabled within any EHR system that has been certified through the US Meaningful Use program.

Automated integration of continuous glucose monitor data in the electronic health record using consumer technology

PubMed Central

Kumar, Rajiv B; Goren, Nira D; Stark, David E; Wall, Dennis P; Longhurst, Christopher A

2016-01-01

The diabetes healthcare provider plays a key role in interpreting blood glucose trends, but few institutions have successfully integrated patient home glucose data in the electronic health record (EHR). Published implementations to date have required custom interfaces, which limit wide-scale replication. We piloted automated integration of continuous glucose monitor data in the EHR using widely available consumer technology for 10 pediatric patients with insulin-dependent diabetes. Establishment of a passive data communication bridge via a patient’s/parent’s smartphone enabled automated integration and analytics of patient device data within the EHR between scheduled clinic visits. It is feasible to utilize available consumer technology to assess and triage home diabetes device data within the EHR, and to engage patients/parents and improve healthcare provider workflow. PMID:27018263

Electronic workflow for imaging in clinical research.

PubMed

Hedges, Rebecca A; Goodman, Danielle; Sachs, Peter B

2014-08-01

In the transition from paper to electronic workflow, the University of Colorado Health System's implementation of a new electronic health record system (EHR) forced all clinical groups to reevaluate their practices including the infrastructure surrounding clinical trials. Radiological imaging is an important piece of many clinical trials and requires a high level of consistency and standardization. With EHR implementation, paper orders were manually transcribed into the EHR, digitizing an inefficient work flow. A team of schedulers, radiologists, technologists, research personnel, and EHR analysts worked together to optimize the EHR to accommodate the needs of research imaging protocols. The transition to electronic workflow posed several problems: (1) there needed to be effective communication throughout the imaging process from scheduling to radiologist interpretation. (2) The exam ordering process needed to be automated to allow scheduling of specific research studies on specific equipment. (3) The billing process needed to be controlled to accommodate radiologists already supported by grants. (4) There needed to be functionality allowing exams to finalize automatically skipping the PACS and interpretation process. (5) There needed to be a way to alert radiologists that a specialized research interpretation was needed on a given exam. These issues were resolved through the optimization of the "visit type," allowing a high-level control of an exam at the time of scheduling. Additionally, we added columns and fields to work queues displaying grant identification numbers. The build solutions we implemented reduced the mistakes made and increased imaging quality and compliance.

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.

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

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.

A population-based approach for implementing change from opt-out to opt-in research permissions

PubMed Central

Oates, Jim C.; Shoaibi, Azza; Obeid, Jihad S.; Habrat, Melissa L.; Warren, Robert W.; Brady, Kathleen T.; Lenert, Leslie A.

2017-01-01

Due to recently proposed changes in the Common Rule regarding the collection of research preferences, there is an increased need for efficient methods to document opt-in research preferences at a population level. Previously, our institution developed an opt-out paper-based workflow that could not be utilized for research in a scalable fashion. This project was designed to demonstrate the feasibility of implementing an electronic health record (EHR)-based active opt-in research preferences program. The first phase of implementation required creating and disseminating a patient questionnaire through the EHR portal to populate discreet fields within the EHR indicating patients’ preferences for future research study contact (contact) and their willingness to allow anonymised use of excess tissue and fluid specimens (biobank). In the second phase, the questionnaire was presented within a clinic nurse intake workflow in an obstetrical clinic. These permissions were tabulated in registries for use by investigators for feasibility studies and recruitment. The registry was also used for research patient contact management using a new EHR encounter type to differentiate research from clinical encounters. The research permissions questionnaire was sent to 59,670 patients via the EHR portal. Within four months, 21,814 responses (75% willing to participate in biobanking, and 72% willing to be contacted for future research) were received. Each response was recorded within a patient portal encounter to enable longitudinal analysis of responses. We obtained a significantly lower positive response from the 264 females who completed the questionnaire in the obstetrical clinic (55% volunteers for biobank and 52% for contact). We demonstrate that it is possible to establish a research permissions registry using the EHR portal and clinic-based workflows. This patient-centric, population-based, opt-in approach documents preferences in the EHR, allowing linkage of these preferences to health record information. PMID:28441388

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.

You and me and the computer makes three: variations in exam room use of the electronic health record

PubMed Central

Saleem, Jason J; Flanagan, Mindy E; Russ, Alissa L; McMullen, Carmit K; Elli, Leora; Russell, Scott A; Bennett, Katelyn J; Matthias, Marianne S; Rehman, Shakaib U; Schwartz, Mark D; Frankel, Richard M

2014-01-01

Challenges persist on how to effectively integrate the electronic health record (EHR) into patient visits and clinical workflow, while maintaining patient-centered care. Our goal was to identify variations in, barriers to, and facilitators of the use of the US Department of Veterans Affairs (VA) EHR in ambulatory care workflow in order better to understand how to integrate the EHR into clinical work. We observed and interviewed 20 ambulatory care providers across three geographically distinct VA medical centers. Analysis revealed several variations in, associated barriers to, and facilitators of EHR use corresponding to different units of analysis: computer interface, team coordination/workflow, and organizational. We discuss our findings in the context of different units of analysis and connect variations in EHR use to various barriers and facilitators. Findings from this study may help inform the design of the next generation of EHRs for the VA and other healthcare systems. PMID:24001517

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.

Taking a quality assurance program from paper to electronic health records: one dental school's experience.

PubMed

Filker, Phyllis J; Muckey, Erin Joy; Kelner, Steven M; Kodish-Stav, Jodi

2009-09-01

The Obama administration is seeking to increase access to and improve the efficiency of the health care system in the United States. One aspect of those efforts is a push towards the utilization of electronic health records (EHRs) by health care providers. Nova Southeastern University College of Dental Medicine (NSU-CDM) opened its doors in 1997 and began its evolution from paper charts to EHRs in 2006. AxiUm, a computer-run patient record and clinical management system, has become an integral part of the college's quality assurance program and its students' clinical education. Since the introduction of axiUm, the school has already noticed an increase in the quality of patient care due to improved oversight of patient management and the ability to more efficiently track treatment outcomes. Over time, the system will enable data collected by students providing care in the clinics to be quantified. Opposition to EHRs tends to stem primarily from the amount of time required for users to gain proficiency in the new technology, as well as from the initial cost to the provider. But there is no better place to begin this learning process regarding the importance and utilization of EHR systems than universities, where health professions students can acquire a comfort level with EHRs in an academic environment that they may then implement in their future practice.

Text Mining for Precision Medicine: Bringing structure to EHRs and biomedical literature to understand genes and health

PubMed Central

Simmons, Michael; Singhal, Ayush; Lu, Zhiyong

2018-01-01

The key question of precision medicine is whether it is possible to find clinically actionable granularity in diagnosing disease and classifying patient risk. The advent of next generation sequencing and the widespread adoption of electronic health records (EHRs) have provided clinicians and researchers a wealth of data and made possible the precise characterization of individual patient genotypes and phenotypes. Unstructured text — found in biomedical publications and clinical notes — is an important component of genotype and phenotype knowledge. Publications in the biomedical literature provide essential information for interpreting genetic data. Likewise, clinical notes contain the richest source of phenotype information in EHRs. Text mining can render these texts computationally accessible and support information extraction and hypothesis generation. This chapter reviews the mechanics of text mining in precision medicine and discusses several specific use cases, including database curation for personalized cancer medicine, patient outcome prediction from EHR-derived cohorts, and pharmacogenomic research. Taken as a whole, these use cases demonstrate how text mining enables effective utilization of existing knowledge sources and thus promotes increased value for patients and healthcare systems. Text mining is an indispensable tool for translating genotype-phenotype data into effective clinical care that will undoubtedly play an important role in the eventual realization of precision medicine. PMID:27807747

Text Mining for Precision Medicine: Bringing Structure to EHRs and Biomedical Literature to Understand Genes and Health.

PubMed

Simmons, Michael; Singhal, Ayush; Lu, Zhiyong

2016-01-01

The key question of precision medicine is whether it is possible to find clinically actionable granularity in diagnosing disease and classifying patient risk. The advent of next-generation sequencing and the widespread adoption of electronic health records (EHRs) have provided clinicians and researchers a wealth of data and made possible the precise characterization of individual patient genotypes and phenotypes. Unstructured text-found in biomedical publications and clinical notes-is an important component of genotype and phenotype knowledge. Publications in the biomedical literature provide essential information for interpreting genetic data. Likewise, clinical notes contain the richest source of phenotype information in EHRs. Text mining can render these texts computationally accessible and support information extraction and hypothesis generation. This chapter reviews the mechanics of text mining in precision medicine and discusses several specific use cases, including database curation for personalized cancer medicine, patient outcome prediction from EHR-derived cohorts, and pharmacogenomic research. Taken as a whole, these use cases demonstrate how text mining enables effective utilization of existing knowledge sources and thus promotes increased value for patients and healthcare systems. Text mining is an indispensable tool for translating genotype-phenotype data into effective clinical care that will undoubtedly play an important role in the eventual realization of precision medicine.

Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials

PubMed Central

Miotto, Riccardo

2015-01-01

Objective To develop a cost-effective, case-based reasoning framework for clinical research eligibility screening by only reusing the electronic health records (EHRs) of minimal enrolled participants to represent the target patient for each trial under consideration. Materials and Methods The EHR data—specifically diagnosis, medications, laboratory results, and clinical notes—of known clinical trial participants were aggregated to profile the “target patient” for a trial, which was used to discover new eligible patients for that trial. The EHR data of unseen patients were matched to this “target patient” to determine their relevance to the trial; the higher the relevance, the more likely the patient was eligible. Relevance scores were a weighted linear combination of cosine similarities computed over individual EHR data types. For evaluation, we identified 262 participants of 13 diversified clinical trials conducted at Columbia University as our gold standard. We ran a 2-fold cross validation with half of the participants used for training and the other half used for testing along with other 30 000 patients selected at random from our clinical database. We performed binary classification and ranking experiments. Results The overall area under the ROC curve for classification was 0.95, enabling the highlight of eligible patients with good precision. Ranking showed satisfactory results especially at the top of the recommended list, with each trial having at least one eligible patient in the top five positions. Conclusions This relevance-based method can potentially be used to identify eligible patients for clinical trials by processing patient EHR data alone without parsing free-text eligibility criteria, and shows promise of efficient “case-based reasoning” modeled only on minimal trial participants. PMID:25769682

Linking Guidelines to Electronic Health Record Design for Improved Chronic Disease Management

PubMed Central

Barretto, Sistine A.; Warren, Jim; Goodchild, Andrew; Bird, Linda; Heard, Sam; Stumptner, Markus

2003-01-01

The promise of electronic decision support to promote evidence based practice remains elusive in the context of chronic disease management. We examine the problem of achieving a close relationship of Electronic Health Record (EHR) content to other components of a clinical information system (guidelines, decision support and work-flow), particularly linking the decisions made by providers back to the guidelines. We use the openEHR architecture, which allows extension of a core Reference Model via Archetypes to refine the detailed information recording options for specific classes of encounter. We illustrate the use of openEHR for tracking the relationship of a series of clinical encounters to a guideline via a case study of guideline-compliant treatment of hypertension in diabetes. This case study shows the contribution guideline content can have on problem-specific EHR structure and demonstrates the potential for a constructive interaction of electronic decision support and the EHR. PMID:14728135

PACS and electronic health records

NASA Astrophysics Data System (ADS)

Cohen, Simona; Gilboa, Flora; Shani, Uri

2002-05-01

Electronic Health Record (EHR) is a major component of the health informatics domain. An important part of the EHR is the medical images obtained over a patient's lifetime and stored in diverse PACS. The vision presented in this paper is that future medical information systems will convert data from various medical sources -- including diverse modalities, PACS, HIS, CIS, RIS, and proprietary systems -- to HL7 standard XML documents. Then, the various documents are indexed and compiled to EHRs, upon which complex queries can be posed. We describe the conversion of data retrieved from PACS systems through DICOM to HL7 standard XML documents. This enables the EHR system to answer queries such as 'Get all chest images of patients at the age of 20-30, that have blood type 'A' and are allergic to pine trees', which a single PACS cannot answer. The integration of data from multiple sources makes our approach capable of delivering such answers. It enables the correlation of medical, demographic, clinical, and even genetic information. In addition, by fully indexing all the tagged data in DICOM objects, it becomes possible to offer access to huge amounts of valuable data, which can be better exploited in the specific radiology domain.

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

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.

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.

SMART Platforms: Building the App Store for Biosurveillance

PubMed Central

Mandl, Kenneth D.

2013-01-01

Objective To enable public health departments to develop “apps” to run on electronic health records (EHRs) for (1) biosurveillance and case reporting and (2) delivering alerts to the point of care. We describe a novel health information technology platform with substitutable apps constructed around core services enabling EHRs to function as iPhone-like platforms. Introduction Health care information is a fundamental source of data for biosurveillance, yet configuring EHRs to report relevant data to health departments is technically challenging, labor intensive, and often requires custom solutions for each installation. Public health agencies wishing to deliver alerts to clinicians also must engage in an endless array of one-off systems integrations. Despite a $48B investment in HIT, and meaningful use criteria requiring reporting to biosurveillance systems, most vendor electronic health records are architected monolithically, making modification difficult for hospitals and physician practices. An alternative approach is to reimagine EHRs as iPhone-like platforms supporting substitutable apps-based functionality. Substitutability is the capability inherent in a system of replacing one application with another of similar functionality. Methods Substitutability requires that the purchaser of an app can replace one application with another without being technically expert, without requiring re-engineering other applications that they are using, and without having to consult or require assistance of any of the vendors of previously installed or currently installed applications. Apps necessarily compete with each other promoting progress and adaptability. The Substitutable Medical Applications, Reusable Technologies (SMART) Platforms project is funded by a $15M grant from Office of the National Coordinator of Health Information Technology’s Strategic Health IT Advanced Research Projects (SHARP) Program. All SMART standards are open and the core software is open source. The SMART project promotes substitutability through an application programming interface (API) that can be adopted as part of a “container” built around by a wide variety of HIT, providing readonly access to the underlying data model and a software development toolkit to readily create apps. SMART containers are HIT systems, that have implemented the SMART API or a portion of it. Containers marshal data sources and present them consistently across the SMART API. SMART applications consume the API and are substitutable. Results SMART provides a common platform supporting an “app store for biosurveillance” as an approach to enabling one stop shopping for public health departments—to create an app once, and distribute it everywhere. Further, such apps can be readily updated or created—for example, in the case of an emerging infection, an app may be designed to collect additional data at emergency department triage. Or a public health department may widely distribute an app, interoperable with any SMART-enabled EMR, that delivers contextualized alerts when patient electronic records are opened, or through background processes. SMART has sparked an ecosystem of apps developers and attracted existing health information technology platforms to adopt the SMART API—including, traditional, open source, and next generation EHRs, patient-facing platforms and health information exchanges. SMART-enabled platforms to date include the Cerner EMR, the WorldVista EHR, the OpenMRS EHR, the i2b2 analytic platform, and the Indivo X personal health record. The SMART team is working with the Mirth Corporation, to SMART-enable the HealthBridge and Redwood MedNet Health Information Exchanges. We have demonstrated that a single SMART app can run, unmodified, in all of these environments, as long as the underlying platform collects the required data types. Major EHR vendors are currently adapting the SMART API for their products. Conclusions The SMART system enables nimble customization of any electronic health record system to create either a reporting function (outgoing communication) or an alerting function (incoming communication) establishing a technology for a robust linkage between public health and clinical environments.

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.

A 'green button' for using aggregate patient data at the point of care.

PubMed

Longhurst, Christopher A; Harrington, Robert A; Shah, Nigam H

2014-07-01

Randomized controlled trials have traditionally been the gold standard against which all other sources of clinical evidence are measured. However, the cost of conducting these trials can be prohibitive. In addition, evidence from the trials frequently rests on narrow patient-inclusion criteria and thus may not generalize well to real clinical situations. Given the increasing availability of comprehensive clinical data in electronic health records (EHRs), some health system leaders are now advocating for a shift away from traditional trials and toward large-scale retrospective studies, which can use practice-based evidence that is generated as a by-product of clinical processes. Other thought leaders in clinical research suggest that EHRs should be used to lower the cost of trials by integrating point-of-care randomization and data capture into clinical processes. We believe that a successful learning health care system will require both approaches, and we suggest a model that resolves this escalating tension: a "green button" function within EHRs to help clinicians leverage aggregate patient data for decision making at the point of care. Giving clinicians such a tool would support patient care decisions in the absence of gold-standard evidence and would help prioritize clinical questions for which EHR-enabled randomization should be carried out. The privacy rule in the Health Insurance Portability and Accountability Act (HIPAA) of 1996 may require revision to support this novel use of patient data. Project HOPE—The People-to-People Health Foundation, Inc.

Fear of e-Health records implementation?

PubMed

Laur, Audrey

2015-03-01

As our world is dominated by Information Communication and Technologies (ICT), governments of many leading countries have decided to implement ICT in their health systems. The first step is the digitalisation of medical records (e-Health Records or EHRs). In order to reduce concerns that health systems encountered, EHRs are supposed to prevent duplicated prescriptions and hospitalisations, ineffective transferability of medical records, lack of communication in clinical assessments, etc. They are also expected to improve the relationship between health providers and patients. At first sight, EHR seems to offer considerable potential for assisting health policies, enabling the development of new tools to facilitate coordination and cooperation among health professionals and promoting a new approach to sharing medical information. However, as discussed in this article, recent debates have shown that EHR presents pros and cons (technical, financial, social) that governments need to clarify urgently. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Automated integration of continuous glucose monitor data in the electronic health record using consumer technology.

PubMed

Kumar, Rajiv B; Goren, Nira D; Stark, David E; Wall, Dennis P; Longhurst, Christopher A

2016-05-01

The diabetes healthcare provider plays a key role in interpreting blood glucose trends, but few institutions have successfully integrated patient home glucose data in the electronic health record (EHR). Published implementations to date have required custom interfaces, which limit wide-scale replication. We piloted automated integration of continuous glucose monitor data in the EHR using widely available consumer technology for 10 pediatric patients with insulin-dependent diabetes. Establishment of a passive data communication bridge via a patient's/parent's smartphone enabled automated integration and analytics of patient device data within the EHR between scheduled clinic visits. It is feasible to utilize available consumer technology to assess and triage home diabetes device data within the EHR, and to engage patients/parents and improve healthcare provider workflow. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

SMART precision cancer medicine: a FHIR-based app to provide genomic information at the point of care.

PubMed

Warner, Jeremy L; Rioth, Matthew J; Mandl, Kenneth D; Mandel, Joshua C; Kreda, David A; Kohane, Isaac S; Carbone, Daniel; Oreto, Ross; Wang, Lucy; Zhu, Shilin; Yao, Heming; Alterovitz, Gil

2016-07-01

Precision cancer medicine (PCM) will require ready access to genomic data within the clinical workflow and tools to assist clinical interpretation and enable decisions. Since most electronic health record (EHR) systems do not yet provide such functionality, we developed an EHR-agnostic, clinico-genomic mobile app to demonstrate several features that will be needed for point-of-care conversations. Our prototype, called Substitutable Medical Applications and Reusable Technology (SMART)® PCM, visualizes genomic information in real time, comparing a patient's diagnosis-specific somatic gene mutations detected by PCR-based hotspot testing to a population-level set of comparable data. The initial prototype works for patient specimens with 0 or 1 detected mutation. Genomics extensions were created for the Health Level Seven® Fast Healthcare Interoperability Resources (FHIR)® standard; otherwise, the prototype is a normal SMART on FHIR app. The PCM prototype can rapidly present a visualization that compares a patient's somatic genomic alterations against a distribution built from more than 3000 patients, along with context-specific links to external knowledge bases. Initial evaluation by oncologists provided important feedback about the prototype's strengths and weaknesses. We added several requested enhancements and successfully demonstrated the app at the inaugural American Society of Clinical Oncology Interoperability Demonstration; we have also begun to expand visualization capabilities to include cancer specimens with multiple mutations. PCM is open-source software for clinicians to present the individual patient within the population-level spectrum of cancer somatic mutations. The app can be implemented on any SMART on FHIR-enabled EHRs, and future versions of PCM should be able to evolve in parallel with external knowledge bases. © 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.

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

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.

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.

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.

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.

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.

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.

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

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.

Free and open source enabling technologies for patient-centric, guideline-based clinical decision support: a survey.

PubMed

Leong, T Y; Kaiser, K; Miksch, S

2007-01-01

Guideline-based clinical decision support is an emerging paradigm to help reduce error, lower cost, and improve quality in evidence-based medicine. The free and open source (FOS) approach is a promising alternative for delivering cost-effective information technology (IT) solutions in health care. In this paper, we survey the current FOS enabling technologies for patient-centric, guideline-based care, and discuss the current trends and future directions of their role in clinical decision support. We searched PubMed, major biomedical informatics websites, and the web in general for papers and links related to FOS health care IT systems. We also relied on our background and knowledge for specific subtopics. We focused on the functionalities of guideline modeling tools, and briefly examined the supporting technologies for terminology, data exchange and electronic health record (EHR) standards. To effectively support patient-centric, guideline-based care, the computerized guidelines and protocols need to be integrated with existing clinical information systems or EHRs. Technologies that enable such integration should be accessible, interoperable, and scalable. A plethora of FOS tools and techniques for supporting different knowledge management and quality assurance tasks involved are available. Many challenges, however, remain in their implementation. There are active and growing trends of deploying FOS enabling technologies for integrating clinical guidelines, protocols, and pathways into the main care processes. The continuing development and maturation of such technologies are likely to make increasingly significant contributions to patient-centric, guideline-based clinical decision support.

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.

A Model for Developing Clinical Analytics Capacity: Closing the Loops on Outcomes to Optimize Quality.

PubMed

Eggert, Corinne; Moselle, Kenneth; Protti, Denis; Sanders, Dale

2017-01-01

Closed Loop Analytics© is receiving growing interest in healthcare as a term referring to information technology, local data and clinical analytics working together to generate evidence for improvement. The Closed Loop Analytics model consists of three loops corresponding to the decision-making levels of an organization and the associated data within each loop - Patients, Protocols, and Populations. The authors propose that each of these levels should utilize the same ecosystem of electronic health record (EHR) and enterprise data warehouse (EDW) enabled data, in a closed-loop fashion, with that data being repackaged and delivered to suit the analytic and decision support needs of each level, in support of better outcomes.

Validation of International Classification of Diseases coding for bone metastases in electronic health records using technology-enabled abstraction.

PubMed

Liede, Alexander; Hernandez, Rohini K; Roth, Maayan; Calkins, Geoffrey; Larrabee, Katherine; Nicacio, Leo

2015-01-01

The accuracy of bone metastases diagnostic coding based on International Classification of Diseases, ninth revision (ICD-9) is unknown for most large databases used for epidemiologic research in the US. Electronic health records (EHR) are the preferred source of data, but often clinically relevant data occur only as unstructured free text. We examined the validity of bone metastases ICD-9 coding in structured EHR and administrative claims relative to the complete (structured and unstructured) patient chart obtained through technology-enabled chart abstraction. Female patients with breast cancer with ≥1 visit after November 2010 were identified from three community oncology practices in the US. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of bone metastases ICD-9 code 198.5. The technology-enabled abstraction displays portions of the chart to clinically trained abstractors for targeted review, thereby maximizing efficiency. We evaluated effects of misclassification of patients developing skeletal complications or treated with bone-targeting agents (BTAs), and timing of BTA. Among 8,796 patients with breast cancer, 524 had confirmed bone metastases using chart abstraction. Sensitivity was 0.67 (95% confidence interval [CI] =0.63-0.71) based on structured EHR, and specificity was high at 0.98 (95% CI =0.98-0.99) with corresponding PPV of 0.71 (95% CI =0.67-0.75) and NPV of 0.98 (95% CI =0.98-0.98). From claims, sensitivity was 0.78 (95% CI =0.74-0.81), and specificity was 0.98 (95% CI =0.98-0.98) with PPV of 0.72 (95% CI =0.68-0.76) and NPV of 0.99 (95% CI =0.98-0.99). Structured data and claims missed 17% of bone metastases (89 of 524). False negatives were associated with measurable overestimation of the proportion treated with BTA or with a skeletal complication. Median date of diagnosis was delayed in structured data (32 days) and claims (43 days) compared with technology-assisted EHR. Technology-enabled chart abstraction of unstructured EHR greatly improves data quality, minimizing false negatives when identifying patients with bone metastases that may lead to inaccurate conclusions that can affect delivery of care.

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

Learning Relational Policies from Electronic Health Record Access Logs

PubMed Central

Malin, Bradley; Nyemba, Steve; Paulett, John

2011-01-01

Modern healthcare organizations (HCOs) are composed of complex dynamic teams to ensure clinical operations are executed in a quick and competent manner. At the same time, the fluid nature of such environments hinders administrators' efforts to define access control policies that appropriately balance patient privacy and healthcare functions. Manual efforts to define these policies are labor-intensive and error-prone, often resulting in systems that endow certain care providers with overly broad access to patients' medical records while restricting other providers from legitimate and timely use. In this work, we propose an alternative method to generate these policies by automatically mining usage patterns from electronic health record (EHR) systems. EHR systems are increasingly being integrated into clinical environments and our approach is designed to be generalizable across HCOs, thus assisting in the design and evaluation of local access control policies. Our technique, which is grounded in data mining and social network analysis theory, extracts a statistical model of the organization from the access logs of its EHRs. In doing so, our approach enables the review of predefined policies, as well as the discovery of unknown behaviors. We evaluate our approach with five months of access logs from the Vanderbilt University Medical Center and confirm the existence of stable social structures and intuitive business operations. Additionally, we demonstrate that there is significant turnover in the interactions between users in the HCO and that policies learned at the department level afford greater stability over time. PMID:21277996

Integration of Hospital Information and Clinical Decision Support Systems to Enable the Reuse of Electronic Health Record Data.

PubMed

Kopanitsa, Georgy

2017-05-18

The efficiency and acceptance of clinical decision support systems (CDSS) can increase if they reuse medical data captured during health care delivery. High heterogeneity of the existing legacy data formats has become the main barrier for the reuse of data. Thus, we need to apply data modeling mechanisms that provide standardization, transformation, accumulation and querying medical data to allow its reuse. In this paper, we focus on the interoperability issues of the hospital information systems (HIS) and CDSS data integration. Our study is based on the approach proposed by Marcos et al. where archetypes are used as a standardized mechanism for the interaction of a CDSS with an electronic health record (EHR). We build an integration tool to enable CDSSs collect data from various institutions without a need for modifications in the implementation. The approach implies development of a conceptual level as a set of archetypes representing concepts required by a CDSS. Treatment case data from Regional Clinical Hospital in Tomsk, Russia was extracted, transformed and loaded to the archetype database of a clinical decision support system. Test records' normalization has been performed by defining transformation and aggregation rules between the EHR data and the archetypes. These mapping rules were used to automatically generate openEHR compliant data. After the transformation, archetype data instances were loaded into the CDSS archetype based data storage. The performance times showed acceptable performance for the extraction stage with a mean of 17.428 s per year (3436 case records). The transformation times were also acceptable with 136.954 s per year (0.039 s per one instance). The accuracy evaluation showed the correctness and applicability of the method for the wide range of HISes. These operations were performed without interrupting the HIS workflow to prevent the HISes from disturbing the service provision to the users. The project results have proven that archetype based technologies are mature enough to be applied in routine operations that require extraction, transformation, loading and querying medical data from heterogeneous EHR systems. Inference models in clinical research and CDSS can benefit from this by defining queries to a valid data set with known structure and constraints. The standard based nature of the archetype approach allows an easy integration of CDSSs with existing EHR systems.

A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data.

PubMed

Delussu, Giovanni; Lianas, Luca; Frexia, Francesca; Zanetti, Gianluigi

2016-01-01

This work presents a scalable data access layer, called PyEHR, designed to support the implementation of data management systems for secondary use of structured heterogeneous biomedical and clinical data. PyEHR adopts the openEHR's formalisms to guarantee the decoupling of data descriptions from implementation details and exploits structure indexing to accelerate searches. Data persistence is guaranteed by a driver layer with a common driver interface. Interfaces for two NoSQL Database Management Systems are already implemented: MongoDB and Elasticsearch. We evaluated the scalability of PyEHR experimentally through two types of tests, called "Constant Load" and "Constant Number of Records", with queries of increasing complexity on synthetic datasets of ten million records each, containing very complex openEHR archetype structures, distributed on up to ten computing nodes.

User-composable Electronic Health Record Improves Efficiency of Clinician Data Viewing for Patient Case Appraisal: A Mixed-Methods Study.

PubMed

Senathirajah, Yalini; Kaufman, David; Bakken, Suzanne

2016-01-01

Challenges in the design of electronic health records (EHRs) include designing usable systems that must meet the complex, rapidly changing, and high-stakes information needs of clinicians. The ability to move and assemble elements together on the same page has significant human-computer interaction (HCI) and efficiency advantages, and can mitigate the problems of negotiating multiple fixed screens and the associated cognitive burdens. We compare MedWISE-a novel EHR that supports user-composable displays-with a conventional EHR in terms of the number of repeat views of data elements for patient case appraisal. The study used mixed-methods for examination of clinical data viewing in four patient cases. The study compared use of an experimental user-composable EHR with use of a conventional EHR, for case appraisal. Eleven clinicians used a user-composable EHR in a case appraisal task in the laboratory setting. This was compared with log file analysis of the same patient cases in the conventional EHR. We investigated the number of repeat views of the same clinical information during a session and across these two contexts, and compared them using Fisher's exact test. There was a significant difference (p<.0001) in proportion of cases with repeat data element viewing between the user-composable EHR (14.6 percent) and conventional EHR (72.6 percent). Users of conventional EHRs repeatedly viewed the same information elements in the same session, as revealed by log files. Our findings are consistent with the hypothesis that conventional systems require that the user view many screens and remember information between screens, causing the user to forget information and to have to access the information a second time. Other mechanisms (such as reduction in navigation over a population of users due to interface sharing, and information selection) may also contribute to increased efficiency in the experimental system. Systems that allow a composable approach that enables the user to gather together on the same screen any desired information elements may confer cognitive support benefits that can increase productive use of systems by reducing fragmented information. By reducing cognitive overload, it can also enhance the user experience.

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.

Using a medical simulation center as an electronic health record usability laboratory

PubMed Central

Landman, Adam B; Redden, Lisa; Neri, Pamela; Poole, Stephen; Horsky, Jan; Raja, Ali S; Pozner, Charles N; Schiff, Gordon; Poon, Eric G

2014-01-01

Usability testing is increasingly being recognized as a way to increase the usability and safety of health information technology (HIT). Medical simulation centers can serve as testing environments for HIT usability studies. We integrated the quality assurance version of our emergency department (ED) electronic health record (EHR) into our medical simulation center and piloted a clinical care scenario in which emergency medicine resident physicians evaluated a simulated ED patient and documented electronically using the ED EHR. Meticulous planning and close collaboration with expert simulation staff was important for designing test scenarios, pilot testing, and running the sessions. Similarly, working with information systems teams was important for integration of the EHR. Electronic tools are needed to facilitate entry of fictitious clinical results while the simulation scenario is unfolding. EHRs can be successfully integrated into existing simulation centers, which may provide realistic environments for usability testing, training, and evaluation of human–computer interactions. PMID:24249778

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.

Integrating Genomic Resources with Electronic Health Records using the HL7 Infobutton Standard

PubMed Central

Overby, Casey Lynnette; Del Fiol, Guilherme; Rubinstein, Wendy S.; Maglott, Donna R.; Nelson, Tristan H.; Milosavljevic, Aleksandar; Martin, Christa L.; Goehringer, Scott R.; Freimuth, Robert R.; Williams, Marc S.

2016-01-01

Summary Background The Clinical Genome Resource (ClinGen) Electronic Health Record (EHR) Workgroup aims to integrate ClinGen resources with EHRs. A promising option to enable this integration is through the Health Level Seven (HL7) Infobutton Standard. EHR systems that are certified according to the US Meaningful Use program provide HL7-compliant infobutton capabilities, which can be leveraged to support clinical decision-making in genomics. Objectives To integrate genomic knowledge resources using the HL7 infobutton standard. Two tactics to achieve this objective were: (1) creating an HL7-compliant search interface for ClinGen, and (2) proposing guidance for genomic resources on achieving HL7 Infobutton standard accessibility and compliance. Methods We built a search interface utilizing OpenInfobutton, an open source reference implementation of the HL7 Infobutton standard. ClinGen resources were assessed for readiness towards HL7 compliance. Finally, based upon our experiences we provide recommendations for publishers seeking to achieve HL7 compliance. Results Eight genomic resources and two sub-resources were integrated with the ClinGen search engine via OpenInfobutton and the HL7 infobutton standard. Resources we assessed have varying levels of readiness towards HL7-compliance. Furthermore, we found that adoption of standard terminologies used by EHR systems is the main gap to achieve compliance. Conclusion Genomic resources can be integrated with EHR systems via the HL7 Infobutton standard using OpenInfobutton. Full compliance of genomic resources with the Infobutton standard would further enhance interoperability with EHR systems. PMID:27579472

Which components of health information technology will drive financial value?

PubMed

Kern, Lisa M; Wilcox, Adam; Shapiro, Jason; Dhopeshwarkar, Rina V; Kaushal, Rainu

2012-08-01

The financial effects of electronic health records (EHRs) and health information exchange (HIE) are largely unknown, despite unprecedented federal incentives for their use. We sought to understand which components of EHRs and HIE are most likely to drive financial savings in the ambulatory, inpatient, and emergency department settings. Framework development and a national expert panel. We searched the literature to identify functionalities enabled by EHRs and HIE across the 3 healthcare settings. We rated each of 233 functionality-setting combinations on their likelihood of having a positive financial effect. We validated the top-scoring functionalities with a panel of 28 national experts, and we compared the high-scoring functionalities with Stage 1 meaningful use criteria. We identified 54 high-scoring functionality- setting combinations, 27 for EHRs and 27 for HIE. Examples of high-scoring functionalities included providing alerts for expensive medications, providing alerts for redundant lab orders, sending and receiving imaging reports, and enabling structured medication reconciliation. Of the 54 high-scoring functionalities, 25 (46%) are represented in Stage 1 meaningful use. Many of the functionalities not yet represented in meaningful use correspond with functionalities that focus directly on healthcare utilization and costs rather than on healthcare quality per se. This work can inform the development and selection of future meaningful use measures; inform implementation efforts, as clinicians and hospitals choose from among a "menu" of measures for meaningful use; and inform evaluation efforts, as investigators seek to measure the actual financial impact of EHRs and HIE.

Structuring Legacy Pathology Reports by openEHR Archetypes to Enable Semantic Querying.

PubMed

Kropf, Stefan; Krücken, Peter; Mueller, Wolf; Denecke, Kerstin

2017-05-18

Clinical information is often stored as free text, e.g. in discharge summaries or pathology reports. These documents are semi-structured using section headers, numbered lists, items and classification strings. However, it is still challenging to retrieve relevant documents since keyword searches applied on complete unstructured documents result in many false positive retrieval results. We are concentrating on the processing of pathology reports as an example for unstructured clinical documents. The objective is to transform reports semi-automatically into an information structure that enables an improved access and retrieval of relevant data. The data is expected to be stored in a standardized, structured way to make it accessible for queries that are applied to specific sections of a document (section-sensitive queries) and for information reuse. Our processing pipeline comprises information modelling, section boundary detection and section-sensitive queries. For enabling a focused search in unstructured data, documents are automatically structured and transformed into a patient information model specified through openEHR archetypes. The resulting XML-based pathology electronic health records (PEHRs) are queried by XQuery and visualized by XSLT in HTML. Pathology reports (PRs) can be reliably structured into sections by a keyword-based approach. The information modelling using openEHR allows saving time in the modelling process since many archetypes can be reused. The resulting standardized, structured PEHRs allow accessing relevant data by retrieving data matching user queries. Mapping unstructured reports into a standardized information model is a practical solution for a better access to data. Archetype-based XML enables section-sensitive retrieval and visualisation by well-established XML techniques. Focussing the retrieval to particular sections has the potential of saving retrieval time and improving the accuracy of the retrieval.

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.

Natural Language Processing–Enabled and Conventional Data Capture Methods for Input to Electronic Health Records: A Comparative Usability Study

PubMed Central

Sheehan, Barbara; Stetson, Peter; Bhatt, Ashish R; Field, Adele I; Patel, Chirag; Maisel, James Mark

2016-01-01

Background The process of documentation in electronic health records (EHRs) is known to be time consuming, inefficient, and cumbersome. The use of dictation coupled with manual transcription has become an increasingly common practice. In recent years, natural language processing (NLP)–enabled data capture has become a viable alternative for data entry. It enables the clinician to maintain control of the process and potentially reduce the documentation burden. The question remains how this NLP-enabled workflow will impact EHR usability and whether it can meet the structured data and other EHR requirements while enhancing the user’s experience. Objective The objective of this study is evaluate the comparative effectiveness of an NLP-enabled data capture method using dictation and data extraction from transcribed documents (NLP Entry) in terms of documentation time, documentation quality, and usability versus standard EHR keyboard-and-mouse data entry. Methods This formative study investigated the results of using 4 combinations of NLP Entry and Standard Entry methods (“protocols”) of EHR data capture. We compared a novel dictation-based protocol using MediSapien NLP (NLP-NLP) for structured data capture against a standard structured data capture protocol (Standard-Standard) as well as 2 novel hybrid protocols (NLP-Standard and Standard-NLP). The 31 participants included neurologists, cardiologists, and nephrologists. Participants generated 4 consultation or admission notes using 4 documentation protocols. We recorded the time on task, documentation quality (using the Physician Documentation Quality Instrument, PDQI-9), and usability of the documentation processes. Results A total of 118 notes were documented across the 3 subject areas. The NLP-NLP protocol required a median of 5.2 minutes per cardiology note, 7.3 minutes per nephrology note, and 8.5 minutes per neurology note compared with 16.9, 20.7, and 21.2 minutes, respectively, using the Standard-Standard protocol and 13.8, 21.3, and 18.7 minutes using the Standard-NLP protocol (1 of 2 hybrid methods). Using 8 out of 9 characteristics measured by the PDQI-9 instrument, the NLP-NLP protocol received a median quality score sum of 24.5; the Standard-Standard protocol received a median sum of 29; and the Standard-NLP protocol received a median sum of 29.5. The mean total score of the usability measure was 36.7 when the participants used the NLP-NLP protocol compared with 30.3 when they used the Standard-Standard protocol. Conclusions In this study, the feasibility of an approach to EHR data capture involving the application of NLP to transcribed dictation was demonstrated. This novel dictation-based approach has the potential to reduce the time required for documentation and improve usability while maintaining documentation quality. Future research will evaluate the NLP-based EHR data capture approach in a clinical setting. It is reasonable to assert that EHRs will increasingly use NLP-enabled data entry tools such as MediSapien NLP because they hold promise for enhancing the documentation process and end-user experience. PMID:27793791

Natural Language Processing-Enabled and Conventional Data Capture Methods for Input to Electronic Health Records: A Comparative Usability Study.

PubMed

Kaufman, David R; Sheehan, Barbara; Stetson, Peter; Bhatt, Ashish R; Field, Adele I; Patel, Chirag; Maisel, James Mark

2016-10-28

The process of documentation in electronic health records (EHRs) is known to be time consuming, inefficient, and cumbersome. The use of dictation coupled with manual transcription has become an increasingly common practice. In recent years, natural language processing (NLP)-enabled data capture has become a viable alternative for data entry. It enables the clinician to maintain control of the process and potentially reduce the documentation burden. The question remains how this NLP-enabled workflow will impact EHR usability and whether it can meet the structured data and other EHR requirements while enhancing the user's experience. The objective of this study is evaluate the comparative effectiveness of an NLP-enabled data capture method using dictation and data extraction from transcribed documents (NLP Entry) in terms of documentation time, documentation quality, and usability versus standard EHR keyboard-and-mouse data entry. This formative study investigated the results of using 4 combinations of NLP Entry and Standard Entry methods ("protocols") of EHR data capture. We compared a novel dictation-based protocol using MediSapien NLP (NLP-NLP) for structured data capture against a standard structured data capture protocol (Standard-Standard) as well as 2 novel hybrid protocols (NLP-Standard and Standard-NLP). The 31 participants included neurologists, cardiologists, and nephrologists. Participants generated 4 consultation or admission notes using 4 documentation protocols. We recorded the time on task, documentation quality (using the Physician Documentation Quality Instrument, PDQI-9), and usability of the documentation processes. A total of 118 notes were documented across the 3 subject areas. The NLP-NLP protocol required a median of 5.2 minutes per cardiology note, 7.3 minutes per nephrology note, and 8.5 minutes per neurology note compared with 16.9, 20.7, and 21.2 minutes, respectively, using the Standard-Standard protocol and 13.8, 21.3, and 18.7 minutes using the Standard-NLP protocol (1 of 2 hybrid methods). Using 8 out of 9 characteristics measured by the PDQI-9 instrument, the NLP-NLP protocol received a median quality score sum of 24.5; the Standard-Standard protocol received a median sum of 29; and the Standard-NLP protocol received a median sum of 29.5. The mean total score of the usability measure was 36.7 when the participants used the NLP-NLP protocol compared with 30.3 when they used the Standard-Standard protocol. In this study, the feasibility of an approach to EHR data capture involving the application of NLP to transcribed dictation was demonstrated. This novel dictation-based approach has the potential to reduce the time required for documentation and improve usability while maintaining documentation quality. Future research will evaluate the NLP-based EHR data capture approach in a clinical setting. It is reasonable to assert that EHRs will increasingly use NLP-enabled data entry tools such as MediSapien NLP because they hold promise for enhancing the documentation process and end-user experience. ©David R. Kaufman, Barbara Sheehan, Peter Stetson, Ashish R. Bhatt, Adele I. Field, Chirag Patel, James Mark Maisel. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 28.10.2016.

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.

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

Recommendation of standardized health learning contents using archetypes and semantic web technologies.

PubMed

Legaz-García, María del Carmen; Martínez-Costa, Catalina; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2012-01-01

Linking Electronic Healthcare Records (EHR) content to educational materials has been considered a key international recommendation to enable clinical engagement and to promote patient safety. This would suggest citizens to access reliable information available on the web and to guide them properly. In this paper, we describe an approach in that direction, based on the use of dual model EHR standards and standardized educational contents. The recommendation method will be based on the semantic coverage of the learning content repository for a particular archetype, which will be calculated by applying semantic web technologies like ontologies and semantic annotations.

The Analytic Information Warehouse (AIW): a Platform for Analytics using Electronic Health Record Data

PubMed Central

Post, Andrew R.; Kurc, Tahsin; Cholleti, Sharath; Gao, Jingjing; Lin, Xia; Bornstein, William; Cantrell, Dedra; Levine, David; Hohmann, Sam; Saltz, Joel H.

2013-01-01

Objective To create an analytics platform for specifying and detecting clinical phenotypes and other derived variables in electronic health record (EHR) data for quality improvement investigations. Materials and Methods We have developed an architecture for an Analytic Information Warehouse (AIW). It supports transforming data represented in different physical schemas into a common data model, specifying derived variables in terms of the common model to enable their reuse, computing derived variables while enforcing invariants and ensuring correctness and consistency of data transformations, long-term curation of derived data, and export of derived data into standard analysis tools. It includes software that implements these features and a computing environment that enables secure high-performance access to and processing of large datasets extracted from EHRs. Results We have implemented and deployed the architecture in production locally. The software is available as open source. We have used it as part of hospital operations in a project to reduce rates of hospital readmission within 30 days. The project examined the association of over 100 derived variables representing disease and co-morbidity phenotypes with readmissions in five years of data from our institution’s clinical data warehouse and the UHC Clinical Database (CDB). The CDB contains administrative data from over 200 hospitals that are in academic medical centers or affiliated with such centers. Discussion and Conclusion A widely available platform for managing and detecting phenotypes in EHR data could accelerate the use of such data in quality improvement and comparative effectiveness studies. PMID:23402960

An information extraction framework for cohort identification using electronic health records.

PubMed

Liu, Hongfang; Bielinski, Suzette J; Sohn, Sunghwan; Murphy, Sean; Wagholikar, Kavishwar B; Jonnalagadda, Siddhartha R; Ravikumar, K E; Wu, Stephen T; Kullo, Iftikhar J; Chute, Christopher G

2013-01-01

Information extraction (IE), a natural language processing (NLP) task that automatically extracts structured or semi-structured information from free text, has become popular in the clinical domain for supporting automated systems at point-of-care and enabling secondary use of electronic health records (EHRs) for clinical and translational research. However, a high performance IE system can be very challenging to construct due to the complexity and dynamic nature of human language. In this paper, we report an IE framework for cohort identification using EHRs that is a knowledge-driven framework developed under the Unstructured Information Management Architecture (UIMA). A system to extract specific information can be developed by subject matter experts through expert knowledge engineering of the externalized knowledge resources used in the framework.

Integrating cancer genomic data into electronic health records.

PubMed

Warner, Jeremy L; Jain, Sandeep K; Levy, Mia A

2016-10-26

The rise of genomically targeted therapies and immunotherapy has revolutionized the practice of oncology in the last 10-15 years. At the same time, new technologies and the electronic health record (EHR) in particular have permeated the oncology clinic. Initially designed as billing and clinical documentation systems, EHR systems have not anticipated the complexity and variety of genomic information that needs to be reviewed, interpreted, and acted upon on a daily basis. Improved integration of cancer genomic data with EHR systems will help guide clinician decision making, support secondary uses, and ultimately improve patient care within oncology clinics. Some of the key factors relating to the challenge of integrating cancer genomic data into EHRs include: the bioinformatics pipelines that translate raw genomic data into meaningful, actionable results; the role of human curation in the interpretation of variant calls; and the need for consistent standards with regard to genomic and clinical data. Several emerging paradigms for integration are discussed in this review, including: non-standardized efforts between individual institutions and genomic testing laboratories; "middleware" products that portray genomic information, albeit outside of the clinical workflow; and application programming interfaces that have the potential to work within clinical workflow. The critical need for clinical-genomic knowledge bases, which can be independent or integrated into the aforementioned solutions, is also discussed.

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

Data-driven human rights: using the electronic health record to promote human rights in jail.

PubMed

Glowa-Kollisch, Sarah; Andrade, Kelly; Stazesky, Richard; Teixeira, Paul; Kaba, Fatos; Macdonald, Ross; Rosner, Zachary; Selling, Daniel; Parsons, Amanda; Venters, Homer

2014-06-14

The electronic health record (EHR) is a commonplace innovation designed to promote efficiency, quality, and continuity of health services. In the New York City jail system, we implemented an EHR across 12 jails between 2008 and 2011. During the same time, our work increasingly focused on the importance of human rights as an essential element to the provision of medical and mental health care for our patients. Consequently, we made major modifications to the EHR to allow for better surveillance of vulnerable populations and enable reporting and analysis of patterns of abuse, neglect, and other patient concerns related to human rights. These modifications have improved our ability to find and care for patients injured in jail and those with mental health exacerbations. More work is needed, however, to optimize the potential of the EHR as a tool to promote human rights among patients in jail. Copyright © 2014 Sheffield, Durante, Rahona, and Zarcadoolas. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

Clinical code set engineering for reusing EHR data for research: A review.

PubMed

Williams, Richard; Kontopantelis, Evangelos; Buchan, Iain; Peek, Niels

2017-06-01

The construction of reliable, reusable clinical code sets is essential when re-using Electronic Health Record (EHR) data for research. Yet code set definitions are rarely transparent and their sharing is almost non-existent. There is a lack of methodological standards for the management (construction, sharing, revision and reuse) of clinical code sets which needs to be addressed to ensure the reliability and credibility of studies which use code sets. To review methodological literature on the management of sets of clinical codes used in research on clinical databases and to provide a list of best practice recommendations for future studies and software tools. We performed an exhaustive search for methodological papers about clinical code set engineering for re-using EHR data in research. This was supplemented with papers identified by snowball sampling. In addition, a list of e-phenotyping systems was constructed by merging references from several systematic reviews on this topic, and the processes adopted by those systems for code set management was reviewed. Thirty methodological papers were reviewed. Common approaches included: creating an initial list of synonyms for the condition of interest (n=20); making use of the hierarchical nature of coding terminologies during searching (n=23); reviewing sets with clinician input (n=20); and reusing and updating an existing code set (n=20). Several open source software tools (n=3) were discovered. There is a need for software tools that enable users to easily and quickly create, revise, extend, review and share code sets and we provide a list of recommendations for their design and implementation. Research re-using EHR data could be improved through the further development, more widespread use and routine reporting of the methods by which clinical codes were selected. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Design and implementation of a web-based patient portal linked to an ambulatory care electronic health record: patient gateway for diabetes collaborative care.

PubMed

Grant, Richard W; Wald, Jonathan S; Poon, Eric G; Schnipper, Jeffrey L; Gandhi, Tejal K; Volk, Lynn A; Middleton, Blackford

2006-10-01

Despite the availability of expert guidelines and widespread diabetes quality improvement efforts, care of patients with diabetes remains suboptimal. Two key barriers to care that may be amenable to informatics-based interventions include (1) lack of patient engagement with therapeutic care plans and (2) lack of medication adjustment by physicians ("clinical inertia") during clinical encounters. The authors describe the conceptual framework, design, implementation, and analysis plan for a diabetes patient web-portal linked directly to the electronic health record (EHR) of a large academic medical center via secure Internet access designed to overcome barriers to effective diabetes care. Partners HealthCare System (Boston, MA), a multi-hospital health care network comprising several thousand physicians caring for over 1 million individual patients, has developed a comprehensive patient web-portal called Patient Gateway that allows patients to interact directly with their EHR via secure Internet access. Using this portal, a specific diabetes interface was designed to maximize patient engagement by importing the patient's current clinical data in an educational format, providing patient-tailored decision support, and enabling the patient to author a "Diabetes Care Plan." The physician view of the patient's Diabetes Care Plan was designed to be concise and to fit into typical EHR clinical workflow. We successfully designed and implemented a Diabetes Patient portal that allows direct interaction with our system's EHR. We are assessing the impact of this advanced informatics tool for collaborative diabetes care in a clinic-randomized controlled trial among 14 primary care practices within our integrated health care system.

Leveraging Big Data and Electronic Health Records to Enhance Novel Approaches to Acute Kidney Injury Research and Care.

PubMed

Sutherland, Scott M; Goldstein, Stuart L; Bagshaw, Sean M

2017-01-01

While acute kidney injury (AKI) has been poorly defined historically, a decade of effort has culminated in a standardized, consensus definition. In parallel, electronic health records (EHRs) have been adopted with greater regularity, clinical informatics approaches have been refined, and the field of EHR-enabled care improvement and research has burgeoned. Although both fields have matured in isolation, uniting the 2 has the capacity to redefine AKI-related care and research. This article describes how the application of a consistent AKI definition to the EHR dataset can accurately and rapidly diagnose and identify AKI events. Furthermore, this electronic, automated diagnostic strategy creates the opportunity to develop predictive approaches, optimize AKI alerts, and trace AKI events across institutions, care platforms, and administrative datasets. © 2017 S. Karger AG, Basel.

Health informatics 3.0.

PubMed

Kalra, Dipak

2011-01-01

Web 3.0 promises us smart computer services that will interact with each other and leverage knowledge about us and our immediate context to deliver prioritised and relevant information to support decisions and actions. Healthcare must take advantage of such new knowledge-integrating services, in particular to support better co-operation between professionals of different disciplines working in different locations, and to enable well-informed co-operation between clinicians and patients. To grasp the potential of Web 3.0 we will need well-harmonised semantic resources that can richly connect virtual teams and link their strategies to real-time and tailored evidence. Facts, decision logic, care pathway steps, alerts, education need to be embedded within components that can interact with multiple EHR systems and services consistently. Using Health Informatics 3.0 a patient's current situation could be compared with the outcomes of very similar patients (from across millions) to deliver personalised care recommendations. The integration of EHRs with biomedical sciences ('omics) research results and predictive models such as the Virtual Physiological Human could help speed up the translation of new knowledge into clinical practice. The mission, and challenge, for Health Informatics 3.0 is to enable healthy citizens, patients and professionals to collaborate within a knowledge-empowered social network in which patient specific information and personalised real-time evidence are seamlessly interwoven.

Archetype-based conversion of EHR content models: pilot experience with a regional EHR system.

PubMed

Chen, Rong; Klein, Gunnar O; Sundvall, Erik; Karlsson, Daniel; Ahlfeldt, Hans

2009-07-01

Exchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format. The openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bi-directional conversion between openEHR archetypes and COSMIC templates. Automated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats. The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards.

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

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.

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

Developing Software to “Track and Catch” Missed Follow-up of Abnormal Test Results in a Complex Sociotechnical Environment

PubMed Central

Smith, M.; Murphy, D.; Laxmisan, A.; Sittig, D.; Reis, B.; Esquivel, A.; Singh, H.

2013-01-01

Summary Background Abnormal test results do not always receive timely follow-up, even when providers are notified through electronic health record (EHR)-based alerts. High workload, alert fatigue, and other demands on attention disrupt a provider’s prospective memory for tasks required to initiate follow-up. Thus, EHR-based tracking and reminding functionalities are needed to improve follow-up. Objectives The purpose of this study was to develop a decision-support software prototype enabling individual and system-wide tracking of abnormal test result alerts lacking follow-up, and to conduct formative evaluations, including usability testing. Methods We developed a working prototype software system, the Alert Watch And Response Engine (AWARE), to detect abnormal test result alerts lacking documented follow-up, and to present context-specific reminders to providers. Development and testing took place within the VA’s EHR and focused on four cancer-related abnormal test results. Design concepts emphasized mitigating the effects of high workload and alert fatigue while being minimally intrusive. We conducted a multifaceted formative evaluation of the software, addressing fit within the larger socio-technical system. Evaluations included usability testing with the prototype and interview questions about organizational and workflow factors. Participants included 23 physicians, 9 clinical information technology specialists, and 8 quality/safety managers. Results Evaluation results indicated that our software prototype fit within the technical environment and clinical workflow, and physicians were able to use it successfully. Quality/safety managers reported that the tool would be useful in future quality assurance activities to detect patients who lack documented follow-up. Additionally, we successfully installed the software on the local facility’s “test” EHR system, thus demonstrating technical compatibility. Conclusion To address the factors involved in missed test results, we developed a software prototype to account for technical, usability, organizational, and workflow needs. Our evaluation has shown the feasibility of the prototype as a means of facilitating better follow-up for cancer-related abnormal test results. PMID:24155789

Developing software to "track and catch" missed follow-up of abnormal test results in a complex sociotechnical environment.

PubMed

Smith, M; Murphy, D; Laxmisan, A; Sittig, D; Reis, B; Esquivel, A; Singh, H

2013-01-01

Abnormal test results do not always receive timely follow-up, even when providers are notified through electronic health record (EHR)-based alerts. High workload, alert fatigue, and other demands on attention disrupt a provider's prospective memory for tasks required to initiate follow-up. Thus, EHR-based tracking and reminding functionalities are needed to improve follow-up. The purpose of this study was to develop a decision-support software prototype enabling individual and system-wide tracking of abnormal test result alerts lacking follow-up, and to conduct formative evaluations, including usability testing. We developed a working prototype software system, the Alert Watch And Response Engine (AWARE), to detect abnormal test result alerts lacking documented follow-up, and to present context-specific reminders to providers. Development and testing took place within the VA's EHR and focused on four cancer-related abnormal test results. Design concepts emphasized mitigating the effects of high workload and alert fatigue while being minimally intrusive. We conducted a multifaceted formative evaluation of the software, addressing fit within the larger socio-technical system. Evaluations included usability testing with the prototype and interview questions about organizational and workflow factors. Participants included 23 physicians, 9 clinical information technology specialists, and 8 quality/safety managers. Evaluation results indicated that our software prototype fit within the technical environment and clinical workflow, and physicians were able to use it successfully. Quality/safety managers reported that the tool would be useful in future quality assurance activities to detect patients who lack documented follow-up. Additionally, we successfully installed the software on the local facility's "test" EHR system, thus demonstrating technical compatibility. To address the factors involved in missed test results, we developed a software prototype to account for technical, usability, organizational, and workflow needs. Our evaluation has shown the feasibility of the prototype as a means of facilitating better follow-up for cancer-related abnormal test results.

An Information Extraction Framework for Cohort Identification Using Electronic Health Records

PubMed Central

Liu, Hongfang; Bielinski, Suzette J.; Sohn, Sunghwan; Murphy, Sean; Wagholikar, Kavishwar B.; Jonnalagadda, Siddhartha R.; Ravikumar, K.E.; Wu, Stephen T.; Kullo, Iftikhar J.; Chute, Christopher G

Information extraction (IE), a natural language processing (NLP) task that automatically extracts structured or semi-structured information from free text, has become popular in the clinical domain for supporting automated systems at point-of-care and enabling secondary use of electronic health records (EHRs) for clinical and translational research. However, a high performance IE system can be very challenging to construct due to the complexity and dynamic nature of human language. In this paper, we report an IE framework for cohort identification using EHRs that is a knowledge-driven framework developed under the Unstructured Information Management Architecture (UIMA). A system to extract specific information can be developed by subject matter experts through expert knowledge engineering of the externalized knowledge resources used in the framework. PMID:24303255

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.

A Semantic Parsing Method for Mapping Clinical Questions to Logical Forms

PubMed Central

Roberts, Kirk; Patra, Braja Gopal

2017-01-01

This paper presents a method for converting natural language questions about structured data in the electronic health record (EHR) into logical forms. The logical forms can then subsequently be converted to EHR-dependent structured queries. The natural language processing task, known as semantic parsing, has the potential to convert questions to logical forms with extremely high precision, resulting in a system that is usable and trusted by clinicians for real-time use in clinical settings. We propose a hybrid semantic parsing method, combining rule-based methods with a machine learning-based classifier. The overall semantic parsing precision on a set of 212 questions is 95.6%. The parser’s rules furthermore allow it to “know what it does not know”, enabling the system to indicate when unknown terms prevent it from understanding the question’s full logical structure. When combined with a module for converting a logical form into an EHR-dependent query, this high-precision approach allows for a question answering system to provide a user with a single, verifiably correct answer. PMID:29854217

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.

A mobile app for securely capturing and transferring clinical images to the electronic health record: description and preliminary usability study.

PubMed

Landman, Adam; Emani, Srinivas; Carlile, Narath; Rosenthal, David I; Semakov, Simon; Pallin, Daniel J; Poon, Eric G

2015-01-02

Photographs are important tools to record, track, and communicate clinical findings. Mobile devices with high-resolution cameras are now ubiquitous, giving clinicians the opportunity to capture and share images from the bedside. However, secure and efficient ways to manage and share digital images are lacking. The aim of this study is to describe the implementation of a secure application for capturing and storing clinical images in the electronic health record (EHR), and to describe initial user experiences. We developed CliniCam, a secure Apple iOS (iPhone, iPad) application that allows for user authentication, patient selection, image capture, image annotation, and storage of images as a Portable Document Format (PDF) file in the EHR. We leveraged our organization's enterprise service-oriented architecture to transmit the image file from CliniCam to our enterprise clinical data repository. There is no permanent storage of protected health information on the mobile device. CliniCam also required connection to our organization's secure WiFi network. Resident physicians from emergency medicine, internal medicine, and dermatology used CliniCam in clinical practice for one month. They were then asked to complete a survey on their experience. We analyzed the survey results using descriptive statistics. Twenty-eight physicians participated and 19/28 (68%) completed the survey. Of the respondents who used CliniCam, 89% found it useful or very useful for clinical practice and easy to use, and wanted to continue using the app. Respondents provided constructive feedback on location of the photos in the EHR, preferring to have photos embedded in (or linked to) clinical notes instead of storing them as separate PDFs within the EHR. Some users experienced difficulty with WiFi connectivity which was addressed by enhancing CliniCam to check for connectivity on launch. CliniCam was implemented successfully and found to be easy to use and useful for clinical practice. CliniCam is now available to all clinical users in our hospital, providing a secure and efficient way to capture clinical images and to insert them into the EHR. Future clinical image apps should more closely link clinical images and clinical documentation and consider enabling secure transmission over public WiFi or cellular networks.

User-composable Electronic Health Record Improves Efficiency of Clinician Data Viewing for Patient Case Appraisal: A Mixed-Methods Study

PubMed Central

Senathirajah, Yalini; Kaufman, David; Bakken, Suzanne

2016-01-01

Background: Challenges in the design of electronic health records (EHRs) include designing usable systems that must meet the complex, rapidly changing, and high-stakes information needs of clinicians. The ability to move and assemble elements together on the same page has significant human-computer interaction (HCI) and efficiency advantages, and can mitigate the problems of negotiating multiple fixed screens and the associated cognitive burdens. Objective: We compare MedWISE—a novel EHR that supports user-composable displays—with a conventional EHR in terms of the number of repeat views of data elements for patient case appraisal. Design and Methods: The study used mixed-methods for examination of clinical data viewing in four patient cases. The study compared use of an experimental user-composable EHR with use of a conventional EHR, for case appraisal. Eleven clinicians used a user-composable EHR in a case appraisal task in the laboratory setting. This was compared with log file analysis of the same patient cases in the conventional EHR. We investigated the number of repeat views of the same clinical information during a session and across these two contexts, and compared them using Fisher’s exact test. Results: There was a significant difference (p<.0001) in proportion of cases with repeat data element viewing between the user-composable EHR (14.6 percent) and conventional EHR (72.6 percent). Discussion and Conclusion: Users of conventional EHRs repeatedly viewed the same information elements in the same session, as revealed by log files. Our findings are consistent with the hypothesis that conventional systems require that the user view many screens and remember information between screens, causing the user to forget information and to have to access the information a second time. Other mechanisms (such as reduction in navigation over a population of users due to interface sharing, and information selection) may also contribute to increased efficiency in the experimental system. Systems that allow a composable approach that enables the user to gather together on the same screen any desired information elements may confer cognitive support benefits that can increase productive use of systems by reducing fragmented information. By reducing cognitive overload, it can also enhance the user experience. PMID:27195306

A semantic framework to protect the privacy of electronic health records with non-numerical attributes.

PubMed

Martínez, Sergio; Sánchez, David; Valls, Aida

2013-04-01

Structured patient data like Electronic Health Records (EHRs) are a valuable source for clinical research. However, the sensitive nature of such information requires some anonymisation procedure to be applied before releasing the data to third parties. Several studies have shown that the removal of identifying attributes, like the Social Security Number, is not enough to obtain an anonymous data file, since unique combinations of other attributes as for example, rare diagnoses and personalised treatments, may lead to patient's identity disclosure. To tackle this problem, Statistical Disclosure Control (SDC) methods have been proposed to mask sensitive attributes while preserving, up to a certain degree, the utility of anonymised data. Most of these methods focus on continuous-scale numerical data. Considering that part of the clinical data found in EHRs is expressed with non-numerical attributes as for example, diagnoses, symptoms, procedures, etc., their application to EHRs produces far from optimal results. In this paper, we propose a general framework to enable the accurate application of SDC methods to non-numerical clinical data, with a focus on the preservation of semantics. To do so, we exploit structured medical knowledge bases like SNOMED CT to propose semantically-grounded operators to compare, aggregate and sort non-numerical terms. Our framework has been applied to several well-known SDC methods and evaluated using a real clinical dataset with non-numerical attributes. Results show that the exploitation of medical semantics produces anonymised datasets that better preserve the utility of EHRs. Copyright © 2012 Elsevier Inc. All rights reserved.

Multi-centric universal pseudonymisation for secondary use of the EHR.

PubMed

Lo Iacono, Luigi

2007-01-01

This paper discusses the importance of protecting the privacy of patient data kept in an Electronic Health Record (EHR) in the case, where it leaves the control- and protection-sphere of the health care realm for secondary uses such as clinical or epidemiological research projects, health care research, assessment of treatment quality or economic assessments. The paper focuses on multi-centric studies, where various data sources are linked together using Grid technologies. It introduces a pseudonymisation system which enables a multi-centric universal pseudonymisation, meaning that a patient's identity will result in the same pseudonym, regardless of which participating study center the patient data is collected.

Archetype-based conversion of EHR content models: pilot experience with a regional EHR system

PubMed Central

2009-01-01

Background Exchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format. Methods The openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bi-directional conversion between openEHR archetypes and COSMIC templates. Results Automated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats. Conclusion The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards. PMID:19570196

[The electronic health record: computerised provider order entry and the electronic instruction document as new functionalities].

PubMed

Derikx, Joep P M; Erdkamp, Frans L G; Hoofwijk, A G M

2013-01-01

An electronic health record (EHR) should provide 4 key functionalities: (a) documenting patient data; (b) facilitating computerised provider order entry; (c) displaying the results of diagnostic research; and (d) providing support for healthcare providers in the clinical decision-making process.- Computerised provider order entry into the EHR enables the electronic receipt and transfer of orders to ancillary departments, which can take the place of handwritten orders.- By classifying the computer provider order entries according to disorders, digital care pathways can be created. Such care pathways could result in faster and improved diagnostics.- Communicating by means of an electronic instruction document that is linked to a computerised provider order entry facilitates the provision of healthcare in a safer, more efficient and auditable manner.- The implementation of a full-scale EHR has been delayed as a result of economic, technical and legal barriers, as well as some resistance by physicians.

A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains.

PubMed

Sinaci, A Anil; Laleci Erturkmen, Gokce B

2013-10-01

In order to enable secondary use of Electronic Health Records (EHRs) by bridging the interoperability gap between clinical care and research domains, in this paper, a unified methodology and the supporting framework is introduced which brings together the power of metadata registries (MDR) and semantic web technologies. We introduce a federated semantic metadata registry framework by extending the ISO/IEC 11179 standard, and enable integration of data element registries through Linked Open Data (LOD) principles where each Common Data Element (CDE) can be uniquely referenced, queried and processed to enable the syntactic and semantic interoperability. Each CDE and their components are maintained as LOD resources enabling semantic links with other CDEs, terminology systems and with implementation dependent content models; hence facilitating semantic search, much effective reuse and semantic interoperability across different application domains. There are several important efforts addressing the semantic interoperability in healthcare domain such as IHE DEX profile proposal, CDISC SHARE and CDISC2RDF. Our architecture complements these by providing a framework to interlink existing data element registries and repositories for multiplying their potential for semantic interoperability to a greater extent. Open source implementation of the federated semantic MDR framework presented in this paper is the core of the semantic interoperability layer of the SALUS project which enables the execution of the post marketing safety analysis studies on top of existing EHR systems. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Exploring the Association Between Electronic Health Record Use and Burnout Among Psychiatry Residents and Faculty: a Pilot Survey Study.

PubMed

Domaney, Nicholas M; Torous, John; Greenberg, William E

2018-05-21

Burnout is a phenomenon with profound negative effects on the US healthcare system. Little is known about the relationship between time spent working on electronic health record (EHR) and burnout among psychiatry residents. The purpose of this study is to generate preliminary data on EHR use and burnout among psychiatry residents and faculty. In August 2017, psychiatry residents and faculty at an academic medical center were given the Maslach Burnout Inventory (MBI), a standardized measurement tool for burnout, and a survey of factors related to EHR use and potential risk factors for burnout. MBI data along with selected burnout risk and protective factors were analyzed with R Studio software. Responses were obtained from 40 psychiatry residents (73%) and 12 clinical faculty members (40%). Residents reported 22 h per week using EHR on average. Mean score of residents surveyed in postgraduate year (PGY)-1-4 met criteria for high emotional exhaustion associated with burnout. The magnitude of correlation between EHR use and emotional exhaustion was stronger than for other burnout factors including sleep, exercise, and clinical service. Psychiatry residents show signs of high emotional exhaustion, which is associated with burnout. Results demonstrate a strong positive correlation between EHR use and resident burnout. Time spent on EHR use may be an area of importance for psychiatry program directors and other psychiatric educators to consider when seeking to minimize burnout and promote wellness.

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.

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.

We are bitter, but we are better off: case study of the implementation of an electronic health record system into a mental health hospital in England

PubMed Central

2012-01-01

Background In contrast to the acute hospital sector, there have been relatively few implementations of integrated electronic health record (EHR) systems into specialist mental health settings. The National Programme for Information Technology (NPfIT) in England was the most expensive IT-based transformation of public services ever undertaken, which aimed amongst other things, to implement integrated EHR systems into mental health hospitals. This paper describes the arrival, the process of implementation, stakeholders’ experiences and the local consequences of the implementation of an EHR system into a mental health hospital. Methods Longitudinal, real-time, case study-based evaluation of the implementation and adoption of an EHR software (RiO) into an English mental health hospital known here as Beta. We conducted 48 in-depth interviews with a wide range of internal and external stakeholders, undertook 26 hours of on-site observations, and obtained 65 sets of relevant documents from various types relating to Beta. Analysis was both inductive and deductive, the latter being informed by the ‘sociotechnical changing’ theoretical framework. Results Many interviewees perceived the implementation of the EHR system as challenging and cumbersome. During the early stages of the implementation, some clinicians felt that using the software was time-consuming leading to the conclusion that the EHR was not fit for purpose. Most interviewees considered the chain of deployment of the EHR–which was imposed by NPfIT–as bureaucratic and obstructive, which restricted customization and as a result limited adoption and use. The low IT literacy among users at Beta was a further barrier to the implementation of the EHR. This along with inadequate training in using the EHR software led to resistance to the significant cultural and work environment changes initiated by EHR. Despite the many challenges, Beta achieved some early positive results. These included: the ability to check progress notes and monitor staff activities; improving quality of care as a result of real-time, more accurate and shared patient records across the hospital; and potentially improving the safety of care through increasing the legibility of the clinical record. Conclusions Notwithstanding what was seen as a turbulent, painful and troublesome implementation of the EHR system, Beta achieved some early clinical and managerial benefits from implementing EHRs. The ‘sociotechnical changing’ framework helped us go beyond the dichotomy of success versus failure, when conducting the evaluation and interpreting findings. Given the scope for continued development, there are good reasons, we argue, to scale up the intake of EHR systems by mental health care settings. Software customization and appropriate support are essential to work EHR out in such organizations. PMID:23272770

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

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

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.

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.

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.

Using Electronic Health Records to Support Clinical Trials: A Report on Stakeholder Engagement for EHR4CR

PubMed Central

McCowan, Colin; Thomson, Elizabeth; Szmigielski, Cezary A.; Kalra, Dipak; Sullivan, Frank M.; Prokosch, Hans-Ulrich; Dugas, Martin; Ford, Ian

2015-01-01

Background. The conduct of clinical trials is increasingly challenging due to greater complexity and governance requirements as well as difficulties with recruitment and retention. Electronic Health Records for Clinical Research (EHR4CR) aims at improving the conduct of trials by using existing routinely collected data, but little is known about stakeholder views on data availability, information governance, and acceptable working practices. Methods. Senior figures in healthcare organisations across Europe were provided with a description of the project and structured interviews were subsequently conducted to elicit their views. Results. 37 structured interviewees in Germany, UK, Switzerland, and France indicated strong support for the proposed EHR4CR platform. All interviewees reported that using the platform for assessing feasibility would enhance the conduct of clinical trials and the majority also felt it would reduce workloads. Interviewees felt the platform could enhance trial recruitment and adverse event reporting but also felt it could raise either ethical or information governance concerns in their country. Conclusions. There was clear support for EHR4CR and a belief that it could reduce workloads and improve the conduct and quality of trials. However data security, privacy, and information governance issues would need to be carefully managed in the development of the platform. PMID:26539523

Using Electronic Health Records to Support Clinical Trials: A Report on Stakeholder Engagement for EHR4CR.

PubMed

McCowan, Colin; Thomson, Elizabeth; Szmigielski, Cezary A; Kalra, Dipak; Sullivan, Frank M; Prokosch, Hans-Ulrich; Dugas, Martin; Ford, Ian

2015-01-01

The conduct of clinical trials is increasingly challenging due to greater complexity and governance requirements as well as difficulties with recruitment and retention. Electronic Health Records for Clinical Research (EHR4CR) aims at improving the conduct of trials by using existing routinely collected data, but little is known about stakeholder views on data availability, information governance, and acceptable working practices. Senior figures in healthcare organisations across Europe were provided with a description of the project and structured interviews were subsequently conducted to elicit their views. 37 structured interviewees in Germany, UK, Switzerland, and France indicated strong support for the proposed EHR4CR platform. All interviewees reported that using the platform for assessing feasibility would enhance the conduct of clinical trials and the majority also felt it would reduce workloads. Interviewees felt the platform could enhance trial recruitment and adverse event reporting but also felt it could raise either ethical or information governance concerns in their country. There was clear support for EHR4CR and a belief that it could reduce workloads and improve the conduct and quality of trials. However data security, privacy, and information governance issues would need to be carefully managed in the development of the platform.

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.

Developing knowledge resources to support precision medicine: principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC).

PubMed

Hoffman, James M; Dunnenberger, Henry M; Kevin Hicks, J; Caudle, Kelly E; Whirl Carrillo, Michelle; Freimuth, Robert R; Williams, Marc S; Klein, Teri E; Peterson, Josh F

2016-07-01

To move beyond a select few genes/drugs, the successful adoption of pharmacogenomics into routine clinical care requires a curated and machine-readable database of pharmacogenomic knowledge suitable for use in an electronic health record (EHR) with clinical decision support (CDS). Recognizing that EHR vendors do not yet provide a standard set of CDS functions for pharmacogenetics, the Clinical Pharmacogenetics Implementation Consortium (CPIC) Informatics Working Group is developing and systematically incorporating a set of EHR-agnostic implementation resources into all CPIC guidelines. These resources illustrate how to integrate pharmacogenomic test results in clinical information systems with CDS to facilitate the use of patient genomic data at the point of care. Based on our collective experience creating existing CPIC resources and implementing pharmacogenomics at our practice sites, we outline principles to define the key features of future knowledge bases and discuss the importance of these knowledge resources for pharmacogenomics and ultimately precision medicine. © 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.

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

Electronic health records and support for primary care teamwork.

PubMed

O'Malley, Ann S; Draper, Kevin; Gourevitch, Rebecca; Cross, Dori A; Scholle, Sarah Hudson

2015-03-01

Consensus that enhanced teamwork is necessary for efficient and effective primary care delivery is growing. We sought to identify how electronic health records (EHRs) facilitate and pose challenges to primary care teams as well as how practices are overcoming these challenges. Practices in this qualitative study were selected from those recognized as patient-centered medical homes via the National Committee for Quality Assurance 2011 tool, which included a section on practice teamwork. We interviewed 63 respondents, ranging from physicians to front-desk staff, from 27 primary care practices ranging in size, type, geography, and population size. EHRs were found to facilitate communication and task delegation in primary care teams through instant messaging, task management software, and the ability to create evidence-based templates for symptom-specific data collection from patients by medical assistants and nurses (which can offload work from physicians). Areas where respondents felt that electronic medical record EHR functionalities were weakest and posed challenges to teamwork included the lack of integrated care manager software and care plans in EHRs, poor practice registry functionality and interoperability, and inadequate ease of tracking patient data in the EHR over time. Practices developed solutions for some of the challenges they faced when attempting to use EHRs to support teamwork but wanted more permanent vendor and policy solutions for other challenges. EHR vendors in the United States need to work alongside practicing primary care teams to create more clinically useful EHRs that support dynamic care plans, integrated care management software, more functional and interoperable practice registries, and greater ease of data tracking over time. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Natural language processing of clinical notes for identification of critical limb ischemia.

PubMed

Afzal, Naveed; Mallipeddi, Vishnu Priya; Sohn, Sunghwan; Liu, Hongfang; Chaudhry, Rajeev; Scott, Christopher G; Kullo, Iftikhar J; Arruda-Olson, Adelaide M

2018-03-01

Critical limb ischemia (CLI) is a complication of advanced peripheral artery disease (PAD) with diagnosis based on the presence of clinical signs and symptoms. However, automated identification of cases from electronic health records (EHRs) is challenging due to absence of a single definitive International Classification of Diseases (ICD-9 or ICD-10) code for CLI. In this study, we extend a previously validated natural language processing (NLP) algorithm for PAD identification to develop and validate a subphenotyping NLP algorithm (CLI-NLP) for identification of CLI cases from clinical notes. We compared performance of the CLI-NLP algorithm with CLI-related ICD-9 billing codes. The gold standard for validation was human abstraction of clinical notes from EHRs. Compared to billing codes the CLI-NLP algorithm had higher positive predictive value (PPV) (CLI-NLP 96%, billing codes 67%, p < 0.001), specificity (CLI-NLP 98%, billing codes 74%, p < 0.001) and F1-score (CLI-NLP 90%, billing codes 76%, p < 0.001). The sensitivity of these two methods was similar (CLI-NLP 84%; billing codes 88%; p < 0.12). The CLI-NLP algorithm for identification of CLI from narrative clinical notes in an EHR had excellent PPV and has potential for translation to patient care as it will enable automated identification of CLI cases for quality projects, clinical decision support tools and support a learning healthcare system. Copyright © 2017 The Authors. Published by Elsevier B.V. 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.

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.

A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data

PubMed Central

Lianas, Luca; Frexia, Francesca; Zanetti, Gianluigi

2016-01-01

This work presents a scalable data access layer, called PyEHR, designed to support the implementation of data management systems for secondary use of structured heterogeneous biomedical and clinical data. PyEHR adopts the openEHR’s formalisms to guarantee the decoupling of data descriptions from implementation details and exploits structure indexing to accelerate searches. Data persistence is guaranteed by a driver layer with a common driver interface. Interfaces for two NoSQL Database Management Systems are already implemented: MongoDB and Elasticsearch. We evaluated the scalability of PyEHR experimentally through two types of tests, called “Constant Load” and “Constant Number of Records”, with queries of increasing complexity on synthetic datasets of ten million records each, containing very complex openEHR archetype structures, distributed on up to ten computing nodes. PMID:27936191

Resilient Practices in Maintaining Safety of Health Information Technologies

PubMed Central

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

2014-01-01

Electronic health record systems (EHRs) can improve safety and reliability of health care, but they can also introduce new vulnerabilities by failing to accommodate changes within a dynamic EHR-enabled health care system. Continuous assessment and improvement is thus essential for achieving resilience in EHR-enabled health care systems. Given the rapid adoption of EHRs by many organizations that are still early in their experiences with EHR safety, it is important to understand practices for maintaining resilience used by organizations with a track record of success in EHR use. We conducted interviews about safety practices with 56 key informants (including information technology managers, chief medical information officers, physicians, and patient safety officers) at two large health care systems recognized as leaders in EHR use. We identified 156 references to resilience-related practices from 41 informants. Framework analysis generated five categories of resilient practices: (a) sensitivity to dynamics and interdependencies affecting risks, (b) basic monitoring and responding practices, (c) management of practices and resources for monitoring and responding, (d) sensitivity to risks beyond the horizon, and (e) reflecting on risks with the safety and quality control process itself. The categories reflect three functions that facilitate resilience: reflection, transcending boundaries, and involving sharp-end practitioners in safety management. PMID:25866492

Eliciting end-user expectations to guide the implementation process of a new electronic health record: A case study using concept mapping.

PubMed

Joukes, Erik; Cornet, Ronald; de Bruijne, Martine C; de Keizer, Nicolette F

2016-03-01

To evaluate the usability of concept mapping to elicit the expectations of healthcare professionals regarding the implementation of a new electronic health record (EHR). These expectations need to be taken into account during the implementation process to maximize the chance of success of the EHR. Two university hospitals in Amsterdam, The Netherlands, in the preparation phase of jointly implementing a new EHR. During this study the hospitals had different methods of documenting patient information (legacy EHR vs. paper-based records). Concept mapping was used to determine and classify the expectations of healthcare professionals regarding the implementation of a new EHR. A multidisciplinary group of 46 healthcare professionals from both university hospitals participated in this study. Expectations were elicited in focus groups, their relevance and feasibility were assessed through a web-questionnaire. Nonmetric multidimensional scaling and clustering methods were used to identify clusters of expectations. We found nine clusters of expectations, each covering an important topic to enable the healthcare professionals to work properly with the new EHR once implemented: usability, data use and reuse, facility conditions, data registration, support, training, internal communication, patients, and collaboration. Average importance and feasibility of each of the clusters was high. Concept mapping is an effective method to find topics that, according to healthcare professionals, are important to consider during the implementation of a new EHR. The method helps to combine the input of a large group of stakeholders at limited efforts. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Linking electronic health record-extracted psychosocial data in real-time to risk of readmission for heart failure.

PubMed

Watson, Alice J; O'Rourke, Julia; Jethwani, Kamal; Cami, Aurel; Stern, Theodore A; Kvedar, Joseph C; Chueh, Henry C; Zai, Adrian H

2011-01-01

Knowledge of psychosocial characteristics that helps to identify patients at increased risk for readmission for heart failure (HF) may facilitate timely and targeted care. We hypothesized that certain psychosocial characteristics extracted from the electronic health record (EHR) would be associated with an increased risk for hospital readmission within the next 30 days. We identified 15 psychosocial predictors of readmission. Eleven of these were extracted from the EHR (six from structured data sources and five from unstructured clinical notes). We then analyzed their association with the likelihood of hospital readmission within the next 30 days among 729 patients admitted for HF. Finally, we developed a multivariable predictive model to recognize individuals at high risk for readmission. We found five characteristics-dementia, depression, adherence, declining/refusal of services, and missed clinical appointments-that were associated with an increased risk for hospital readmission: the first four features were captured from unstructured clinical notes, while the last item was captured from a structured data source. Unstructured clinical notes contain important knowledge on the relationship between psychosocial risk factors and an increased risk of readmission for HF that would otherwise have been missed if only structured data were considered. Gathering this EHR-based knowledge can be automated, thus enabling timely and targeted care. Copyright © 2011 The Academy of Psychosomatic Medicine. Published by Elsevier Inc. All rights reserved.

Linking electronic health record-extracted psychosocial data in real-time to risk of readmission for heart failure

PubMed Central

Watson, Alice J.; O’Rourke, Julia; Jethwani, Kamal; Cami, Aurel; Stern, Theodore A.; Kvedar, Joseph C.; Chueh, Henry C.; Zai, Adrian H.

2013-01-01

Background Knowledge of psychosocial characteristics that helps to identify patients at increased risk for readmission for heart failure (HF) may facilitate timely and targeted care. Objective We hypothesized that certain psychosocial characteristics extracted from the electronic health record (EHR) would be associated with an increased risk for hospital readmission within the next 30 days. Methods We identified 15 psychosocial predictors of readmission. Eleven of these were extracted from the EHR (six from structured data sources and five from unstructured clinical notes). We then analyzed their association with the likelihood of hospital readmission within the next 30 days among 729 patients admitted for HF. Finally, we developed a multivariable predictive model to recognize individuals at high risk for readmission. Results We found five characteristics—dementia, depression, adherence, declining/refusal of services, and missed clinical appointments—that were associated with an increased risk for hospital readmission: the first four features were captured from unstructured clinical notes, while the last item was captured from a structured data source. Conclusions Unstructured clinical notes contain important knowledge on the relationship between psychosocial risk factors and an increased risk of readmission for HF that would otherwise have been missed if only structured data were considered. Gathering this EHR-based knowledge can be automated, thus enabling timely and targeted care. PMID:21777714

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.

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.

Gradual electronic health record implementation: new insights on physician and patient adaptation.

PubMed

Shield, Renée R; Goldman, Roberta E; Anthony, David A; Wang, Nina; Doyle, Richard J; Borkan, Jeffrey

2010-01-01

Although there is significant interest in implementation of electronic health records (EHRs), limited data have been published in the United States about how physicians, staff, and patients adapt to this implementation process. The purpose of this research was to examine the effects of EHR implementation, especially regarding physician-patient communication and behaviors and patients' responses. We undertook a 22-month, triangulation design, mixed methods study of gradual EHR implementation in a residency-based family medicine outpatient center. Data collection included participant observation and time measurements of 170 clinical encounters, patient exit interviews, focus groups with nurses, nurse's aides, and office staff, and unstructured observations and interviews with nursing staff and physicians. Analysis involved iterative immersion-crystallization discussion and searches for alternate hypotheses. Patient trust in the physician and security in the physician-patient relationship appeared to override most patients' concerns about information technology. Overall, staff concerns about potential deleterious consequences of EHR implementation were dispelled, positive anticipated outcomes were realized, and unexpected benefits were found. Physicians appeared to become comfortable with the "third actor" in the room, and nursing and office staff resistance to EHR implementation was ameliorated with improved work efficiencies. Unexpected advantages included just-in-time improvements and decreased physician time out of the examination room. Strong patient trust in the physician-patient relationship was maintained and work flow improved with EHR implementation. Gradual EHR implementation may help support the development of beneficial physician and staff adaptations, while maintaining positive patient-physician relationships and fostering the sharing of medical information.

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

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.

Acute Kidney Injury and Big Data.

PubMed

Sutherland, Scott M; Goldstein, Stuart L; Bagshaw, Sean M

2018-01-01

The recognition of a standardized, consensus definition for acute kidney injury (AKI) has been an important milestone in critical care nephrology, which has facilitated innovation in prevention, quality of care, and outcomes research among the growing population of hospitalized patients susceptible to AKI. Concomitantly, there have been substantial advances in "big data" technologies in medicine, including electronic health records (EHR), data registries and repositories, and data management and analytic methodologies. EHRs are increasingly being adopted, clinical informatics is constantly being refined, and the field of EHR-enabled care improvement and research has grown exponentially. While these fields have matured independently, integrating the two has the potential to redefine and integrate AKI-related care and research. AKI is an ideal condition to exploit big data health care innovation for several reasons: AKI is common, increasingly encountered in hospitalized settings, imposes meaningful risk for adverse events and poor outcomes, has incremental cost implications, and has been plagued by suboptimal quality of care. In this concise review, we discuss the potential applications of big data technologies, particularly modern EHR platforms and health data repositories, to transform our capacity for AKI prediction, detection, and care quality. © 2018 S. Karger AG, Basel.

Chart biopsy: an emerging medical practice enabled by electronic health records and its impacts on emergency department-inpatient admission handoffs.

PubMed

Hilligoss, Brian; Zheng, Kai

2013-01-01

To examine how clinicians on the receiving end of admission handoffs use electronic health records (EHRs) in preparation for those handoffs and to identify the kinds of impacts such usage may have. This analysis is part of a two-year ethnographic study of emergency department (ED) to internal medicine admission handoffs at a tertiary teaching and referral hospital. Qualitative data were gathered and analyzed iteratively, following a grounded theory methodology. Data collection methods included semi-structured interviews (N = 48), observations (349 hours), and recording of handoff conversations (N = 48). Data analyses involved coding, memo writing, and member checking. The use of EHRs has enabled an emerging practice that we refer to as pre-handoff "chart biopsy": the activity of selectively examining portions of a patient's health record to gather specific data or information about that patient or to get a broader sense of the patient and the care that patient has received. Three functions of chart biopsy are identified: getting an overview of the patient; preparing for handoff and subsequent care; and defending against potential biases. Chart biopsies appear to impact important clinical and organizational processes. Among these are the nature and quality of handoff interactions, and the quality of care, including the appropriateness of dispositioning of patients. Chart biopsy has the potential to enrich collaboration and to enable the hospital to act safely, efficiently, and effectively. Implications for handoff research and for the design and evaluation of EHRs are also discussed.

Role of Social Knowledge Networking technology in facilitating meaningful use of Electronic Health Record medication reconciliation.

PubMed

Rangachari, Pavani

2016-06-01

Despite the federal policy impetus towards EHR Medication Reconciliation, hospital adherence has lagged for one chief reason; low physician engagement, which in turn emanates from lack of consensus in regard to which physician is responsible for managing a patient's medication list, and the importance of medication reconciliation as a tool for improving patient safety and quality of care. The Technology-in-Practice (TIP) framework stresses the role of human action in enacting structures of technology use or "technologies-in-practice." Applying the TIP framework to the EHR Medication Reconciliation context, helps frame the problem as one of low physician engagement in performing EHR Medication Reconciliation, translating to limited-use-EHR-in-practice. Concurrently, the problem suggests a hierarchical network structure, reflecting limited communication among hospital administrators and clinical providers on the importance of EHR Medication Reconciliation in improving patient safety. Integrating the TIP literature with the more recent knowledge-in-Practice (KIP) literature suggests that EHR-in-practice could be transformed from "limited use" to "meaningful use" through the use of Social Knowledge Networking (SKN) Technology to create new social network structures, and enable engagement, learning, and practice change. Correspondingly, the objectives of this paper are to: 1) Conduct a narrative review of the literature on "technology use," to understand how technologies-in-practice may be transformed from limited use to meaningful use; 2) Conduct a narrative review of the literature on "organizational change implementation," to understand how changes in technology use could be successfully implemented and sustained in a healthcare organizational context; and 3) Apply lessons learned from the narrative literature reviews to identify strategies for the meaningful use and successful implementation of EHR Medication Reconciliation technology.

EHR Big Data Deep Phenotyping

PubMed Central

Lenert, L.; Lopez-Campos, G.

2014-01-01

Summary Objectives Given the quickening speed of discovery of variant disease drivers from combined patient genotype and phenotype data, the objective is to provide methodology using big data technology to support the definition of deep phenotypes in medical records. Methods As the vast stores of genomic information increase with next generation sequencing, the importance of deep phenotyping increases. The growth of genomic data and adoption of Electronic Health Records (EHR) in medicine provides a unique opportunity to integrate phenotype and genotype data into medical records. The method by which collections of clinical findings and other health related data are leveraged to form meaningful phenotypes is an active area of research. Longitudinal data stored in EHRs provide a wealth of information that can be used to construct phenotypes of patients. We focus on a practical problem around data integration for deep phenotype identification within EHR data. The use of big data approaches are described that enable scalable markup of EHR events that can be used for semantic and temporal similarity analysis to support the identification of phenotype and genotype relationships. Conclusions Stead and colleagues’ 2005 concept of using light standards to increase the productivity of software systems by riding on the wave of hardware/processing power is described as a harbinger for designing future healthcare systems. The big data solution, using flexible markup, provides a route to improved utilization of processing power for organizing patient records in genotype and phenotype research. PMID:25123744

A multi-institution evaluation of clinical profile anonymization

PubMed Central

Heatherly, Raymond; Rasmussen, Luke V; Peissig, Peggy L; Pacheco, Jennifer A; Harris, Paul; Denny, Joshua C

2016-01-01

Background and objective: There is an increasing desire to share de-identified electronic health records (EHRs) for secondary uses, but there are concerns that clinical terms can be exploited to compromise patient identities. Anonymization algorithms mitigate such threats while enabling novel discoveries, but their evaluation has been limited to single institutions. Here, we study how an existing clinical profile anonymization fares at multiple medical centers. Methods: We apply a state-of-the-art k-anonymization algorithm, with k set to the standard value 5, to the International Classification of Disease, ninth edition codes for patients in a hypothyroidism association study at three medical centers: Marshfield Clinic, Northwestern University, and Vanderbilt University. We assess utility when anonymizing at three population levels: all patients in 1) the EHR system; 2) the biorepository; and 3) a hypothyroidism study. We evaluate utility using 1) changes to the number included in the dataset, 2) number of codes included, and 3) regions generalization and suppression were required. Results: Our findings yield several notable results. First, we show that anonymizing in the context of the entire EHR yields a significantly greater quantity of data by reducing the amount of generalized regions from ∼15% to ∼0.5%. Second, ∼70% of codes that needed generalization only generalized two or three codes in the largest anonymization. Conclusions: Sharing large volumes of clinical data in support of phenome-wide association studies is possible while safeguarding privacy to the underlying individuals. PMID:26567325

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.

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.

Temporal data representation, normalization, extraction, and reasoning: A review from clinical domain

PubMed Central

Madkour, Mohcine; Benhaddou, Driss; Tao, Cui

2016-01-01

Background and Objective We live our lives by the calendar and the clock, but time is also an abstraction, even an illusion. The sense of time can be both domain-specific and complex, and is often left implicit, requiring significant domain knowledge to accurately recognize and harness. In the clinical domain, the momentum gained from recent advances in infrastructure and governance practices has enabled the collection of tremendous amount of data at each moment in time. Electronic Health Records (EHRs) have paved the way to making these data available for practitioners and researchers. However, temporal data representation, normalization, extraction and reasoning are very important in order to mine such massive data and therefore for constructing the clinical timeline. The objective of this work is to provide an overview of the problem of constructing a timeline at the clinical point of care and to summarize the state-of-the-art in processing temporal information of clinical narratives. Methods This review surveys the methods used in three important area: modeling and representing of time, Medical NLP methods for extracting time, and methods of time reasoning and processing. The review emphasis on the current existing gap between present methods and the semantic web technologies and catch up with the possible combinations. Results the main findings of this review is revealing the importance of time processing not only in constructing timelines and clinical decision support systems but also as a vital component of EHR data models and operations. Conclusions Extracting temporal information in clinical narratives is a challenging task. The inclusion of ontologies and semantic web will lead to better assessment of the annotation task and, together with medical NLP techniques, will help resolving granularity and co-reference resolution problems. PMID:27040831

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.

Patient Summary and medicines reconciliation: application of the ISO/CEN EN 13606 standard in clinical practice.

PubMed

Farfán Sedano, Francisco J; Terrón Cuadrado, Marta; Castellanos Clemente, Yolanda; Serrano Balazote, Pablo; Moner Cano, David; Robles Viejo, Montserrat

2011-01-01

The comparison of the patient's current medication list with the medication being ordered when admitted to Hospital, identifying omissions, duplications, dosing errors, and potential interactions, constitutes the core process of medicines reconciliation. Access to the medication the patient is taking at home could be unfeasible as this information is frequently stored in various locations and in diverse proprietary formats. The lack of interoperability between those information systems, namely the Primary Care and the Specialized Electronic Health Records (EHRs), facilitates medication errors and endangers patient safety. Thus, the development of a Patient Summary that includes clinical data from different electronic systems will allow doctors access to relevant information enabling a safer and more efficient assistance. Such a collection of data from heterogeneous and distributed systems has been achieved in this Project through the construction of a federated view based on the ISO/CEN EN13606 Standard for architecture and communication of EHRs.

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.

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.

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.

Dissipation and entropy production in open quantum systems

NASA Astrophysics Data System (ADS)

Majima, H.; Suzuki, A.

2010-11-01

A microscopic description of an open system is generally expressed by the Hamiltonian of the form: Htot = Hsys + Henviron + Hsys-environ. We developed a microscopic theory of entropy and derived a general formula, so-called "entropy-Hamiltonian relation" (EHR), that connects the entropy of the system to the interaction Hamiltonian represented by Hsys-environ for a nonequilibrium open quantum system. To derive the EHR formula, we mapped the open quantum system to the representation space of the Liouville-space formulation or thermo field dynamics (TFD), and thus worked on the representation space Script L := Script H otimes , where Script H denotes the ordinary Hilbert space while the tilde Hilbert space conjugates to Script H. We show that the natural transformation (mapping) of nonequilibrium open quantum systems is accomplished within the theoretical structure of TFD. By using the obtained EHR formula, we also derived the equation of motion for the distribution function of the system. We demonstrated that by knowing the microscopic description of the interaction, namely, the specific form of Hsys-environ on the representation space Script L, the EHR formulas enable us to evaluate the entropy of the system and to gain some information about entropy for nonequilibrium open quantum systems.

Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study.

PubMed

Dewey, Frederick E; Murray, Michael F; Overton, John D; Habegger, Lukas; Leader, Joseph B; Fetterolf, Samantha N; O'Dushlaine, Colm; Van Hout, Cristopher V; Staples, Jeffrey; Gonzaga-Jauregui, Claudia; Metpally, Raghu; Pendergrass, Sarah A; Giovanni, Monica A; Kirchner, H Lester; Balasubramanian, Suganthi; Abul-Husn, Noura S; Hartzel, Dustin N; Lavage, Daniel R; Kost, Korey A; Packer, Jonathan S; Lopez, Alexander E; Penn, John; Mukherjee, Semanti; Gosalia, Nehal; Kanagaraj, Manoj; Li, Alexander H; Mitnaul, Lyndon J; Adams, Lance J; Person, Thomas N; Praveen, Kavita; Marcketta, Anthony; Lebo, Matthew S; Austin-Tse, Christina A; Mason-Suares, Heather M; Bruse, Shannon; Mellis, Scott; Phillips, Robert; Stahl, Neil; Murphy, Andrew; Economides, Aris; Skelding, Kimberly A; Still, Christopher D; Elmore, James R; Borecki, Ingrid B; Yancopoulos, George D; Davis, F Daniel; Faucett, William A; Gottesman, Omri; Ritchie, Marylyn D; Shuldiner, Alan R; Reid, Jeffrey G; Ledbetter, David H; Baras, Aris; Carey, David J

2016-12-23

The DiscovEHR collaboration between the Regeneron Genetics Center and Geisinger Health System couples high-throughput sequencing to an integrated health care system using longitudinal electronic health records (EHRs). We sequenced the exomes of 50,726 adult participants in the DiscovEHR study to identify ~4.2 million rare single-nucleotide variants and insertion/deletion events, of which ~176,000 are predicted to result in a loss of gene function. Linking these data to EHR-derived clinical phenotypes, we find clinical associations supporting therapeutic targets, including genes encoding drug targets for lipid lowering, and identify previously unidentified rare alleles associated with lipid levels and other blood level traits. About 3.5% of individuals harbor deleterious variants in 76 clinically actionable genes. The DiscovEHR data set provides a blueprint for large-scale precision medicine initiatives and genomics-guided therapeutic discovery. Copyright © 2016, American Association for the Advancement of Science.

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.

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.

Specialty pharmaceuticals care management in an integrated health care delivery system with electronic health records.

PubMed

Monroe, C Douglas; Chin, Karen Y

2013-05-01

The specialty pharmaceuticals market is expanding more rapidly than the traditional pharmaceuticals market. Specialty pharmacy operations have evolved to deliver selected medications and associated clinical services. The growing role of specialty drugs requires new approaches to managing the use of these drugs. The focus, expectations, and emphasis in specialty drug management in an integrated health care delivery system such as Kaiser Permanente (KP) can vary as compared with more conventional health care systems. The KP Specialty Pharmacy (KP-SP) serves KP members across the United States. This descriptive account addresses the impetus for specialty drug management within KP, the use of tools such as an electronic health record (EHR) system and process management software, the KP-SP approach for specialty pharmacy services, and the emphasis on quality measurement of services provided. Kaiser Permanente's integrated system enables KP-SP pharmacists to coordinate the provision of specialty drugs while monitoring laboratory values, physician visits, and most other relevant elements of the patient's therapy. Process management software facilitates the counseling of patients, promotion of adherence, and interventions to resolve clinical, logistic, or pharmacy benefit issues. The integrated EHR affords KP-SP pharmacists advantages for care management that should become available to more health care systems with broadened adoption of EHRs. The KP-SP experience may help to establish models for clinical pharmacy services as health care systems and information systems become more integrated.

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.

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

Security and Privacy in a DACS.

PubMed

Delgado, Jaime; Llorente, Silvia; Pàmies, Martí; Vilalta, Josep

2016-01-01

The management of electronic health records (EHR), in general, and clinical documents, in particular, is becoming a key issue in the daily work of Healthcare Organizations (HO). The need for providing secure and private access to, and storage for, clinical documents together with the need for HO to interoperate, raises a number of issues difficult to solve. Many systems are in place to manage EHR and documents. Some of these Healthcare Information Systems (HIS) follow standards in their document structure and communications protocols, but many do not. In fact, they are mostly proprietary and do not interoperate. Our proposal to solve the current situation is the use of a DACS (Document Archiving and Communication System) for providing security, privacy and standardized access to clinical documents.

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.

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.

Exploiting Temporal Constraints of Clinical Guidelines by Applying OpenEHR Archetypes.

PubMed

Cintho, Lilian Mie Mukai; Garcia, Diego; da Silva Santos, Bruno Henrique; Sacchi, Lucia; Quaglini, Silvana; Moro, Claudia Maria Cabral

2017-01-01

Studies describing Computer-Interpretable Clinical Guidelines (CIG) with temporal constrains (TC) generally have not addressed issues related to their integration into Electronic Health Record (EHR) systems. This study aimed to represent TCs contained in clinical guidelines by applying archetypes and Guideline Definition Language (GDL) to incorporate decision support into EHRs. An example of each TC class in the clinical guideline for management of Atrial Fibrillation was represented using archetypes and GDL.

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

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.

-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.

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.

Use of electronic health record structured text and its payoffs. The approach and barriers to using structured text in EHR to document care encounters.

PubMed

Benge, James; Beach, Thomas; Gladding, Connie; Maestas, Gail

2008-01-01

The Military Health System (MHS) deployed its electronic health record (EHR), AHLTA to Military Treatment Facilities (MTFs) around the world. This paper focuses on the approach and barriers to using structured text in AHLTA to document care encounters and illustrates the direct correlation between the use of structured text and achievement of expected benefits. AHLTA uses commercially available products, a health data dictionary and standardized medical terminology, enabling the capture of structured computable data. With structured text stored in the AHLTA Clinical Data Repository (CDR), the MHS has seen a return on its EHR investment with improvements in the accuracy and completeness of coding and the documentation of care provided. Determining the aspects of documentation where structured text is most beneficial, as well as the degree of structured text needed has been a significant challenge. This paper describes how the economic value framework aligns the enterprise strategic objectives with the EHR investment features, performance metrics and expected benefits. The framework analyses focus on return on investment calculations, baseline assessment and post-implementation benefits validation. Cost avoidance, revenue enhancements and operational improvements, such as evidence-based medicine and medical surveillance can be directly attributed to use structured text.

Disassociation for electronic health record privacy.

PubMed

Loukides, Grigorios; Liagouris, John; Gkoulalas-Divanis, Aris; Terrovitis, Manolis

2014-08-01

The dissemination of Electronic Health Record (EHR) data, beyond the originating healthcare institutions, can enable large-scale, low-cost medical studies that have the potential to improve public health. Thus, funding bodies, such as the National Institutes of Health (NIH) in the U.S., encourage or require the dissemination of EHR data, and a growing number of innovative medical investigations are being performed using such data. However, simply disseminating EHR data, after removing identifying information, may risk privacy, as patients can still be linked with their record, based on diagnosis codes. This paper proposes the first approach that prevents this type of data linkage using disassociation, an operation that transforms records by splitting them into carefully selected subsets. Our approach preserves privacy with significantly lower data utility loss than existing methods and does not require data owners to specify diagnosis codes that may lead to identity disclosure, as these methods do. Consequently, it can be employed when data need to be shared broadly and be used in studies, beyond the intended ones. Through extensive experiments using EHR data, we demonstrate that our method can construct data that are highly useful for supporting various types of clinical case count studies and general medical analysis tasks. Copyright © 2014 Elsevier Inc. All rights reserved.

A multi-institution evaluation of clinical profile anonymization.

PubMed

Heatherly, Raymond; Rasmussen, Luke V; Peissig, Peggy L; Pacheco, Jennifer A; Harris, Paul; Denny, Joshua C; Malin, Bradley A

2016-04-01

There is an increasing desire to share de-identified electronic health records (EHRs) for secondary uses, but there are concerns that clinical terms can be exploited to compromise patient identities. Anonymization algorithms mitigate such threats while enabling novel discoveries, but their evaluation has been limited to single institutions. Here, we study how an existing clinical profile anonymization fares at multiple medical centers. We apply a state-of-the-artk-anonymization algorithm, withkset to the standard value 5, to the International Classification of Disease, ninth edition codes for patients in a hypothyroidism association study at three medical centers: Marshfield Clinic, Northwestern University, and Vanderbilt University. We assess utility when anonymizing at three population levels: all patients in 1) the EHR system; 2) the biorepository; and 3) a hypothyroidism study. We evaluate utility using 1) changes to the number included in the dataset, 2) number of codes included, and 3) regions generalization and suppression were required. Our findings yield several notable results. First, we show that anonymizing in the context of the entire EHR yields a significantly greater quantity of data by reducing the amount of generalized regions from ∼15% to ∼0.5%. Second, ∼70% of codes that needed generalization only generalized two or three codes in the largest anonymization. Sharing large volumes of clinical data in support of phenome-wide association studies is possible while safeguarding privacy to the underlying individuals. © 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.

An Architecture for Integrated Regional Health Telematics Networks

DTIC Science & Technology

2001-10-25

that enables informed citizens to have an impact on the healthcare system and to be more concerned and care for their own health . The current...resource, educational, integrated electronic health record (I- EHR ), and added value services [2]. These classes of telematic services are applica...cally distributed clinical information systems . 5) Finally, added-value services (e.g. image processing, information indexing, data pre-fetching

"Big data" and the electronic health record.

PubMed

Ross, M K; Wei, W; Ohno-Machado, L

2014-08-15

Implementation of Electronic Health Record (EHR) systems continues to expand. The massive number of patient encounters results in high amounts of stored data. Transforming clinical data into knowledge to improve patient care has been the goal of biomedical informatics professionals for many decades, and this work is now increasingly recognized outside our field. In reviewing the literature for the past three years, we focus on "big data" in the context of EHR systems and we report on some examples of how secondary use of data has been put into practice. We searched PubMed database for articles from January 1, 2011 to November 1, 2013. We initiated the search with keywords related to "big data" and EHR. We identified relevant articles and additional keywords from the retrieved articles were added. Based on the new keywords, more articles were retrieved and we manually narrowed down the set utilizing predefined inclusion and exclusion criteria. Our final review includes articles categorized into the themes of data mining (pharmacovigilance, phenotyping, natural language processing), data application and integration (clinical decision support, personal monitoring, social media), and privacy and security. The increasing adoption of EHR systems worldwide makes it possible to capture large amounts of clinical data. There is an increasing number of articles addressing the theme of "big data", and the concepts associated with these articles vary. The next step is to transform healthcare big data into actionable knowledge.

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.

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.

Use of electronic health records to ascertain, validate and phenotype acute myocardial infarction: A systematic review and recommendations.

PubMed

Rubbo, Bruna; Fitzpatrick, Natalie K; Denaxas, Spiros; Daskalopoulou, Marina; Yu, Ning; Patel, Riyaz S; Hemingway, Harry

2015-01-01

Electronic health records (EHRs) offer the opportunity to ascertain clinical outcomes at large scale and low cost, thus facilitating cohort studies, quality of care research and clinical trials. For acute myocardial infarction (AMI) the extent to which different EHR sources are accessible and accurate remains uncertain. Using MEDLINE and EMBASE we identified thirty three studies, reporting a total of 128658 patients, published between January 2000 and July 2014 that permitted assessment of the validity of AMI diagnosis drawn from EHR sources against a reference such as manual chart review. In contrast to clinical practice, only one study used EHR-derived markers of myocardial necrosis to identify possible AMI cases, none used electrocardiogram findings and one used symptoms in the form of free text combined with coded diagnosis. The remaining studies relied mostly on coded diagnosis. Thirty one studies reported positive predictive value (PPV)≥ 70% between AMI diagnosis from both secondary care and primary care EHRs and the reference. Among fifteen studies reporting EHR-derived AMI phenotypes, three cross-referenced ST-segment elevation AMI diagnosis (PPV range 71-100%), two non-ST-segment elevation AMI (PPV 91.0, 92.1%), three non-fatal AMI (PPV range 82-92.2%) and six fatal AMI (PPV range 64-91.7%). Clinical coding of EHR-derived AMI diagnosis in primary care and secondary care was found to be accurate in different clinical settings and for different phenotypes. However, markers of myocardial necrosis, ECG and symptoms, the cornerstones of a clinical diagnosis, are underutilised and remain a challenge to retrieve from EHRs. Copyright © 2015. Published by Elsevier Ireland Ltd.

Implementing EHRs: An Exploratory Study to Examine Current Practices in Migrating Physician Practice

PubMed Central

Dolezel, Diane; Moczygemba, Jackie

2015-01-01

Implementation of electronic health record (EHR) systems in physician practices is challenging and complex. In the past, physicians had little incentive to move from paper-based records. With the passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act in 2009, Medicare and Medicaid incentive payments are now available for physicians who implement EHRs for meaningful use. The Office of the National Coordinator for Health Information Technology (ONC) has ample detail on clinical data needed for meaningful use in order to assess the quality of patient care. Details are lacking, however, on how much clinical data, if any, should be transferred from the old paper records during an EHR implementation project. The purpose of this exploratory study was to investigate and document the elements of longitudinal clinical data that are essential for inclusion in the EHR of physicians in a clinical practice setting, as reported by the office managers of the physicians in the study group. PMID:26807077

Practice Facilitator Strategies for Addressing Electronic Health Record Data Challenges for Quality Improvement: EvidenceNOW.

PubMed

Hemler, Jennifer R; Hall, Jennifer D; Cholan, Raja A; Crabtree, Benjamin F; Damschroder, Laura J; Solberg, Leif I; Ono, Sarah S; Cohen, Deborah J

2018-01-01

Practice facilitators ("facilitators") can play an important role in supporting primary care practices in performing quality improvement (QI), but they need complete and accurate clinical performance data from practices' electronic health records (EHR) to help them set improvement priorities, guide clinical change, and monitor progress. Here, we describe the strategies facilitators use to help practices perform QI when complete or accurate performance data are not available. Seven regional cooperatives enrolled approximately 1500 small-to-medium-sized primary care practices and 136 facilitators in EvidenceNOW, the Agency for Healthcare Research and Quality's initiative to improve cardiovascular preventive services. The national evaluation team analyzed qualitative data from online diaries, site visit field notes, and interviews to discover how facilitators worked with practices on EHR data challenges to obtain and use data for QI. We found facilitators faced practice-level EHR data challenges, such as a lack of clinical performance data, partial or incomplete clinical performance data, and inaccurate clinical performance data. We found that facilitators responded to these challenges, respectively, by using other data sources or tools to fill in for missing data, approximating performance reports and generating patient lists, and teaching practices how to document care and confirm performance measures. In addition, facilitators helped practices communicate with EHR vendors or health systems in requesting data they needed. Overall, facilitators tailored strategies to fit the individual practice and helped build data skills and trust. Facilitators can use a range of strategies to help practices perform data-driven QI when performance data are inaccurate, incomplete, or missing. Support is necessary to help practices, particularly those with EHR data challenges, build their capacity for conducting data-driven QI that is required of them for participating in practice transformation and performance-based payment programs. It is questionable how practices with data challenges will perform in programs without this kind of support. © Copyright 2018 by the American Board of Family Medicine.

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.

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.

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.

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.

Outcomes of Computerized Physician Order Entry in an Electronic Health Record After Implementation in an Outpatient Oncology Setting

PubMed Central

Harshberger, Cara A.; Harper, Abigail J.; Carro, George W.; Spath, Wayne E.; Hui, Wendy C.; Lawton, Jessica M.; Brockstein, Bruce E.

2011-01-01

Purpose: Computerized physician order entry (CPOE) in electronic health records (EHR) has been recognized as an important tool in optimal health care provision that can reduce errors and improve safety. The objective of this study is to describe documentation completeness and user satisfaction of medical charts before and after implementation of an outpatient oncology EHR/ CPOE system in a hospital-based outpatient cancer center within three treatment sites. Methods: This study is a retrospective chart review of 90 patients who received one of the following regimens between 1999 and 2006: FOLFOX, AC, carboplatin + paclitaxel, ABVD, cisplatin + etoposide, R-CHOP, and clinical trials. Documentation completeness scores were assigned to each chart based on the number of documented data points found out of the total data points assessed. EHR/CPOE documentation completeness was compared with completeness of paper charts orders of the same regimens. A user satisfaction survey of the paper chart and EHR/CPOE system was conducted among the physicians, nurses, and pharmacists who worked with both systems. Results: The mean percentage of identified data points successfully found in the EHR/CPOE charts was 93% versus 67% in the paper charts (P < .001). Regimen complexity did not alter the number of data points found. The survey response rate was 64%, and the results showed that satisfaction was statistically significant in favor of the EHR/CPOE system. Conclusion: Using EHR/CPOE systems improves completeness of medical record and chemotherapy order documentation and improves user satisfaction with the medical record system. EHR/CPOE requires constant vigilance and maintenance to optimize patient safety. PMID:22043187

-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

Using EHR audit trail logs to analyze clinical workflow: A case study from community-based ambulatory clinics.

PubMed

Wu, Danny T Y; Smart, Nikolas; Ciemins, Elizabeth L; Lanham, Holly J; Lindberg, Curt; Zheng, Kai

2017-01-01

To develop a workflow-supported clinical documentation system, it is a critical first step to understand clinical workflow. While Time and Motion studies has been regarded as the gold standard of workflow analysis, this method can be resource consuming and its data may be biased due to the cognitive limitation of human observers. In this study, we aimed to evaluate the feasibility and validity of using EHR audit trail logs to analyze clinical workflow. Specifically, we compared three known workflow changes from our previous study with the corresponding EHR audit trail logs of the study participants. The results showed that EHR audit trail logs can be a valid source for clinical workflow analysis, and can provide an objective view of clinicians' behaviors, multi-dimensional comparisons, and a highly extensible analysis framework.

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.

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.

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

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.

Comparative effectiveness research in DARTNet primary care practices: point of care data collection on hypoglycemia and over-the-counter and herbal use among patients diagnosed with diabetes.

PubMed

Libby, Anne M; Pace, Wilson; Bryan, Cathy; Anderson, Heather Orton; Ellis, Samuel L; Allen, Richard Read; Brandt, Elias; Huebschmann, Amy G; West, David; Valuck, Robert J

2010-06-01

The Distributed Ambulatory Research in Therapeutics Network (DARTNet) is a federated network of electronic health record (EHR) data, designed as a platform for next-generation comparative effectiveness research in real-world settings. DARTNet links information from nonintegrated primary care clinics that use EHRs to deliver ambulatory care to overcome limitations with traditional observational research. Test the ability to conduct a remote, electronic point of care study in DARTNet practices by prompting clinic staff to obtain specific information during a patient encounter. Prospective survey of patients identified through queries of clinical data repositories in federated network organizations. On patient visit, survey is triggered and data are relinked to the EHR, de-identified, and copied for evaluation. Adult patients diagnosed with diabetes mellitus that scheduled a clinic visit for any reason in a 2-week period in DARTNet primary care practices. Survey on hypoglycemic events (past month) and over-the-counter and herbal supplement use. DARTNet facilitated point of care data collection triggered by an electronic prompt for additional information at a patient visit. More than one-third of respondents (33% response rate) reported either mild (45%) or severe hypoglycemic events (5%) in the month before the survey; only 3 of those were also coded using the ICD-9 (a significant difference in detection rates 37% vs. 1%). Nearly one-quarter of patients reported taking an OTC/herbal, 4% specifically for the treatment of symptoms of diabetes. Prospective data collection is feasible in DARTNet and can enable comparative effectiveness and safety research.

Using electronic health records for clinical research: the case of the EHR4CR project.

PubMed

De Moor, Georges; Sundgren, Mats; Kalra, Dipak; Schmidt, Andreas; Dugas, Martin; Claerhout, Brecht; Karakoyun, Töresin; Ohmann, Christian; Lastic, Pierre-Yves; Ammour, Nadir; Kush, Rebecca; Dupont, Danielle; Cuggia, Marc; Daniel, Christel; Thienpont, Geert; Coorevits, Pascal

2015-02-01

To describe the IMI EHR4CR project which is designing and developing, and aims to demonstrate, a scalable, widely acceptable and efficient approach to interoperability between EHR systems and clinical research systems. The IMI EHR4CR project is combining and extending several previously isolated state-of-the-art technical components through a new approach to develop a platform for reusing EHR data to support medical research. This will be achieved through multiple but unified initiatives across different major disease areas (e.g. cardiovascular, cancer) and clinical research use cases (protocol feasibility, patient identification and recruitment, clinical trial execution and serious adverse event reporting), with various local and national stakeholders across several countries and therefore under various legal frameworks. An initial instance of the platform has been built, providing communication, security and terminology services to the eleven participating hospitals and ten pharmaceutical companies located in seven European countries. Proof-of-concept demonstrators have been built and evaluated for the protocol feasibility and patient recruitment scenarios. The specifications of the clinical trial execution and the adverse event reporting scenarios have been documented and reviewed. Through a combination of a consortium that brings collectively many years of experience from previous relevant EU projects and of the global conduct of clinical trials, of an approach to ethics that engages many important stakeholders across Europe to ensure acceptability, of a robust iterative design methodology for the platform services that is anchored on requirements of an underlying Service Oriented Architecture that has been designed to be scalable and adaptable, EHR4CR could be well placed to deliver a sound, useful and well accepted pan-European solution for the reuse of hospital EHR data to support clinical research studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Primary Care Practices' Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement.

PubMed

Cohen, Deborah J; Dorr, David A; Knierim, Kyle; DuBard, C Annette; Hemler, Jennifer R; Hall, Jennifer D; Marino, Miguel; Solberg, Leif I; McConnell, K John; Nichols, Len M; Nease, Donald E; Edwards, Samuel T; Wu, Winfred Y; Pham-Singer, Hang; Kho, Abel N; Phillips, Robert L; Rasmussen, Luke V; Duffy, F Daniel; Balasubramanian, Bijal A

2018-04-01

Federal value-based payment programs require primary care practices to conduct quality improvement activities, informed by the electronic reports on clinical quality measures that their electronic health records (EHRs) generate. To determine whether EHRs produce reports adequate to the task, we examined survey responses from 1,492 practices across twelve states, supplemented with qualitative data. Meaningful-use participation, which requires the use of a federally certified EHR, was associated with the ability to generate reports-but the reports did not necessarily support quality improvement initiatives. Practices reported numerous challenges in generating adequate reports, such as difficulty manipulating and aligning measurement time frames with quality improvement needs, lack of functionality for generating reports on electronic clinical quality measures at different levels, discordance between clinical guidelines and measures available in reports, questionable data quality, and vendors that were unreceptive to changing EHR configuration beyond federal requirements. The current state of EHR measurement functionality may be insufficient to support federal initiatives that tie payment to clinical quality measures.

Primary Care Practices’ Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement

PubMed Central

Cohen, Deborah J.; Dorr, David A.; Knierim, Kyle; DuBard, C. Annette; Hemler, Jennifer R.; Hall, Jennifer D.; Marino, Miguel; Solberg, Leif I.; McConnell, K. John; Nichols, Len M.; Nease, Donald E.; Edwards, Samuel T.; Wu, Winfred Y.; Pham-Singer, Hang; Kho, Abel N.; Phillips, Robert L.; Rasmussen, Luke V.; Duffy, F. Daniel; Balasubramanian, Bijal A.

2018-01-01

Federal value-based payment programs require primary care practices to conduct quality improvement activities, informed by the electronic reports on clinical quality measures that their electronic health records (EHRs) generate. To determine whether EHRs produce reports adequate to the task, we examined survey responses from 1,492 practices across twelve states, supplemented with qualitative data. Meaningful-use participation, which requires the use of a federally certified EHR, was associated with the ability to generate reports—but the reports did not necessarily support quality improvement initiatives. Practices reported numerous challenges in generating adequate reports, such as difficulty manipulating and aligning measurement time frames with quality improvement needs, lack of functionality for generating reports on electronic clinical quality measures at different levels, discordance between clinical guidelines and measures available in reports, questionable data quality, and vendors that were unreceptive to changing EHR configuration beyond federal requirements. The current state of EHR measurement functionality may be insufficient to support federal initiatives that tie payment to clinical quality measures. PMID:29608365

Development and Implementation of Team-Based Panel Management Tools: Filling the Gap between Patient and Population Information Systems.

PubMed

Watts, Brook; Lawrence, Renée H; Drawz, Paul; Carter, Cameron; Shumaker, Amy Hirsch; Kern, Elizabeth F

2016-08-01

Effective team-based models of care, such as the Patient-Centered Medical Home, require electronic tools to support proactive population management strategies that emphasize care coordination and quality improvement. Despite the spread of electronic health records (EHRs) and vendors marketing population health tools, clinical practices still may lack the ability to have: (1) local control over types of data collected/reports generated, (2) timely data (eg, up-to-date data, not several months old), and accordingly (3) the ability to efficiently monitor and improve patient outcomes. This article describes a quality improvement project at the hospital system level to develop and implement a flexible panel management (PM) tool to improve care of subpopulations of patients (eg, panels of patients with diabetes) by clinical teams. An in-depth case analysis approach is used to explore barriers and facilitators in building a PM registry tool for team-based management needs using standard data elements (eg, laboratory values, pharmacy records) found in EHRs. Also described are factors that may contribute to sustainability; to date the tool has been adapted to 6 disease-focused subpopulations encompassing more than 200,000 patients. Two key lessons emerged from this initiative: (1) though challenging, team-based clinical end users and information technology needed to work together consistently to refine the product, and (2) locally developed population management tools can provide efficient data tracking for frontline clinical teams and leadership. The preliminary work identified critical gaps that were successfully addressed by building local PM registry tools from EHR-derived data and offers lessons learned for others engaged in similar work. (Population Health Management 2016;19:232-239).

Creating a foundation for implementing an electronic health records (EHR)-integrated Social Knowledge Networking (SKN) system on medication reconciliation.

PubMed

Rangachari, P; Dellsperger, K C; Fallaw, D; Davis, I; Sumner, M; Ray, W; Fiedler, S; Nguyen, T; Rethemeyer, R

2018-04-01

In fall 2016, Augusta University received a two-year grant from AHRQ, to implement a Social Knowledge Networking (SKN) system for enabling its health system, AU-Health, to progress from "limited use" of EHR Medication Reconciliation (MedRec) Technology, to "meaningful use." Phase 1 sought to identify a comprehensive set of issues related to EHR MedRec encountered by practitioners at AU-Health. These efforts helped develop a Reporting Tool , which, along with a Discussion Tool , was incorporated into the AU-Health EHR, at the end of Phase 1. Phase 2 (currently underway), comprises a 52-week pilot of the EHR-integrated SKN system in outpatient and inpatient medicine units. The purpose of this paper is to describe the methods and results of Phase 1. Phase 1 utilized an exploratory mixed-method approach, involving two rounds of data collection. This included 15 individual interviews followed by a survey of 200 practitioners, i.e., physicians, nurses, and pharmacists, based in the outpatient and inpatient medicine service at AU Health. Thematic analysis of interviews identified 55 issue-items related to EHR MedRec under 9 issue-categories. The survey sought practitioners' importance-rating of all issue-items identified from interviews. A total of 127 (63%) survey responses were received. Factor analysis served to validate the following 6 of the 9 issue-categories, all of which, were rated "Important" or higher (on average), by over 70% of all respondents: 1) Care-Coordination (CCI); 2) Patient-Education (PEI); 3) Ownership-and-Accountability (OAI); 4) Processes-of-Care (PCI); 5) IT-Related (ITRI); and 6) Workforce-Training (WTI). Significance-testing of importance-rating by professional affiliation revealed no statistically significant differences for CCI and PEI; and some statistically significant differences for OAI, PCI, ITRI, and WTI. There were two key gleanings from the issues related to EHR MedRec unearthed by this study: 1) there was an absence of shared understanding among practitioners, of the value of EHR MedRec in promoting patient safety, which contributed to workarounds, and suboptimal use of the EHR MedRec system; and 2) there was a socio-technical dimension to many of the issues, creating an added layer of complexity. These gleanings in turn, provide insights into best practices for managing both clinical transitions-of-care in the EHR MedRec process; and socio-technical challenges encountered in EHR MedRec implementation.

Creating a foundation for implementing an electronic health records (EHR)-integrated Social Knowledge Networking (SKN) system on medication reconciliation

PubMed Central

Rangachari, P.; Dellsperger, K.C; Fallaw, D.; Davis, I.; Sumner, M.; Ray, W.; Fiedler, S.; Nguyen, T.; Rethemeyer, R.

2018-01-01

Background In fall 2016, Augusta University received a two-year grant from AHRQ, to implement a Social Knowledge Networking (SKN) system for enabling its health system, AU-Health, to progress from “limited use” of EHR Medication Reconciliation (MedRec) Technology, to “meaningful use.” Phase 1 sought to identify a comprehensive set of issues related to EHR MedRec encountered by practitioners at AU-Health. These efforts helped develop a Reporting Tool, which, along with a Discussion Tool, was incorporated into the AU-Health EHR, at the end of Phase 1. Phase 2 (currently underway), comprises a 52-week pilot of the EHR-integrated SKN system in outpatient and inpatient medicine units. The purpose of this paper is to describe the methods and results of Phase 1. Methods Phase 1 utilized an exploratory mixed-method approach, involving two rounds of data collection. This included 15 individual interviews followed by a survey of 200 practitioners, i.e., physicians, nurses, and pharmacists, based in the outpatient and inpatient medicine service at AU Health. Results Thematic analysis of interviews identified 55 issue-items related to EHR MedRec under 9 issue-categories. The survey sought practitioners’ importance-rating of all issue-items identified from interviews. A total of 127 (63%) survey responses were received. Factor analysis served to validate the following 6 of the 9 issue-categories, all of which, were rated “Important” or higher (on average), by over 70% of all respondents: 1) Care-Coordination (CCI); 2) Patient-Education (PEI); 3) Ownership-and-Accountability (OAI); 4) Processes-of-Care (PCI); 5) IT-Related (ITRI); and 6) Workforce-Training (WTI). Significance-testing of importance-rating by professional affiliation revealed no statistically significant differences for CCI and PEI; and some statistically significant differences for OAI, PCI, ITRI, and WTI. Conclusion There were two key gleanings from the issues related to EHR MedRec unearthed by this study: 1) there was an absence of shared understanding among practitioners, of the value of EHR MedRec in promoting patient safety, which contributed to workarounds, and suboptimal use of the EHR MedRec system; and 2) there was a socio-technical dimension to many of the issues, creating an added layer of complexity. These gleanings in turn, provide insights into best practices for managing both clinical transitions-of-care in the EHR MedRec process; and socio-technical challenges encountered in EHR MedRec implementation. PMID:29682132

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.

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.

Creating personalised clinical pathways by semantic interoperability with electronic health records.

PubMed

Wang, Hua-Qiong; Li, Jing-Song; Zhang, Yi-Fan; Suzuki, Muneou; Araki, Kenji

2013-06-01

There is a growing realisation that clinical pathways (CPs) are vital for improving the treatment quality of healthcare organisations. However, treatment personalisation is one of the main challenges when implementing CPs, and the inadequate dynamic adaptability restricts the practicality of CPs. The purpose of this study is to improve the practicality of CPs using semantic interoperability between knowledge-based CPs and semantic electronic health records (EHRs). Simple protocol and resource description framework query language is used to gather patient information from semantic EHRs. The gathered patient information is entered into the CP ontology represented by web ontology language. Then, after reasoning over rules described by semantic web rule language in the Jena semantic framework, we adjust the standardised CPs to meet different patients' practical needs. A CP for acute appendicitis is used as an example to illustrate how to achieve CP customisation based on the semantic interoperability between knowledge-based CPs and semantic EHRs. A personalised care plan is generated by comprehensively analysing the patient's personal allergy history and past medical history, which are stored in semantic EHRs. Additionally, by monitoring the patient's clinical information, an exception is recorded and handled during CP execution. According to execution results of the actual example, the solutions we present are shown to be technically feasible. This study contributes towards improving the clinical personalised practicality of standardised CPs. In addition, this study establishes the foundation for future work on the research and development of an independent CP system. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

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.

Engineering the electronic health record for safety: a multi-level video-based approach to diagnosing and preventing technology-induced error arising from usability problems.

PubMed

Borycki, Elizabeth M; Kushniruk, Andre W; Kuwata, Shigeki; Kannry, Joseph

2011-01-01

Electronic health records (EHRs) promise to improve and streamline healthcare through electronic entry and retrieval of patient data. Furthermore, based on a number of studies showing their positive benefits, they promise to reduce medical error and make healthcare safer. However, a growing body of literature has clearly documented that if EHRS are not designed properly and with usability as an important goal in their design, rather than reducing error, EHR deployment has the potential to actually increase medical error. In this paper we describe our approach to engineering (and reengineering) EHRs in order to increase their beneficial potential while at the same time improving their safety. The approach described in this paper involves an integration of the methods of usability analysis with video analysis of end users interacting with EHR systems and extends the evaluation of the usability of EHRs to include the assessment of the impact of these systems on work practices. Using clinical simulations, we analyze human-computer interaction in real healthcare settings (in a portable, low-cost and high fidelity manner) and include both artificial and naturalistic data collection to identify potential usability problems and sources of technology-induced error prior to widespread system release. Two case studies where the methods we have developed and refined have been applied at different levels of user-computer interaction are described.

“Big Data” and the Electronic Health Record

PubMed Central

Ross, M. K.; Wei, Wei

2014-01-01

Summary Objectives Implementation of Electronic Health Record (EHR) systems continues to expand. The massive number of patient encounters results in high amounts of stored data. Transforming clinical data into knowledge to improve patient care has been the goal of biomedical informatics professionals for many decades, and this work is now increasingly recognized outside our field. In reviewing the literature for the past three years, we focus on “big data” in the context of EHR systems and we report on some examples of how secondary use of data has been put into practice. Methods We searched PubMed database for articles from January 1, 2011 to November 1, 2013. We initiated the search with keywords related to “big data” and EHR. We identified relevant articles and additional keywords from the retrieved articles were added. Based on the new keywords, more articles were retrieved and we manually narrowed down the set utilizing predefined inclusion and exclusion criteria. Results Our final review includes articles categorized into the themes of data mining (pharmacovigilance, phenotyping, natural language processing), data application and integration (clinical decision support, personal monitoring, social media), and privacy and security. Conclusion The increasing adoption of EHR systems worldwide makes it possible to capture large amounts of clinical data. There is an increasing number of articles addressing the theme of “big data”, and the concepts associated with these articles vary. The next step is to transform healthcare big data into actionable knowledge. PMID:25123728

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.

Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces.

PubMed

Samal, Lipika; D'Amore, John D; Bates, David W; Wright, Adam

2017-11-01

Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

C-C1-04: Building a Health Services Information Technology Research Environment

PubMed Central

Gehrum, David W; Jones, JB; Romania, Gregory J; Young, David L; Lerch, Virginia R; Bruce, Christa A; Donkochik, Diane; Stewart, Walter F

2010-01-01

Background: The electronic health record (EHR) has opened a new era for health services research (HSR) where information technology (IT) is used to re-engineer care processes. While the EHR provides one means of advancing novel solutions, a promising strategy is to develop tools (e.g., online questionnaires, visual display tools, decision support) distinct from, but which interact with, the EHR. Development of such software tools outside the EHR offers an advantage in flexibility, sophistication, and ultimately in portability to other settings. However, institutional IT departments have an imperative to protect patient data and to standardize IT processes to ensure system-level security and support traditional business needs. Such imperatives usually present formidable process barriers to testing novel software solutions. We describe how, in collaboration with our IT department, we are creating an environment and a process that allows for routine and rapid testing of novel software solutions. Methods: We convened a working group consisting of IT and research personnel with expertise in information security, database design/management, web design, EHR programming, and health services research. The working group was tasked with developing a research IT environment to accomplish two objectives: maintain network/ data security and regulatory compliance; allow researchers working with external vendors to rapidly prototype and, in a clinical setting, test web-based tools. Results: Two parallel solutions, one focused on hardware, the second on oversight and management, were developed. First, we concluded that three separate, staged development environments were required to allow external vendor access for testing software and for transitioning software to be used in a clinic. In parallel, the extant oversight process for approving/managing access to internal/external personnel had to be altered to reflect the scope and scale of discrete research projects, as opposed to an enterpriselevel approach to IT management. Conclusions: Innovation in health services software development requires a flexible, scalable IT environment adapted to the unique objectives of a HSR software development model. In our experience, implementing the hardware solution is less challenging than the cultural change required to implement such a model and the modifications to administrative and oversight processes to sustain an environment for rapid product development and testing.

[Development of an ophthalmological clinical information system for inpatient eye clinics].

PubMed

Kortüm, K U; Müller, M; Babenko, A; Kampik, A; Kreutzer, T C

2015-12-01

In times of increased digitalization in healthcare, departments of ophthalmology are faced with the challenge of introducing electronic clinical health records (EHR); however, specialized software for ophthalmology is not available with most major EHR sytems. The aim of this project was to create specific ophthalmological user interfaces for large inpatient eye care providers within a hospitalwide EHR. Additionally the integration of ophthalmic imaging systems, scheduling and surgical documentation should be achieved. The existing EHR i.s.h.med (Siemens, Germany) was modified using advanced business application programming (ABAP) language to create specific ophthalmological user interfaces for reproduction and moreover optimization of the clinical workflow. A user interface for documentation of ambulatory patients with eight tabs was designed. From June 2013 to October 2014 a total of 61,551 patient contact details were documented. For surgical documentation a separate user interface was set up. Digital clinical orders for documentation of registration and scheduling of operations user interfaces were also set up. A direct integration of ophthalmic imaging modalities could be established. An ophthalmologist-orientated EHR for outpatient and surgical documentation for inpatient clinics was created and successfully implemented. By incorporation of imaging procedures the foundation of future smart/big data analyses was created.

Designing a system for patients controlling providers' access to their electronic health records: organizational and technical challenges.

PubMed

Leventhal, Jeremy C; Cummins, Jonathan A; Schwartz, Peter H; Martin, Douglas K; Tierney, William M

2015-01-01

Electronic health records (EHRs) are proliferating, and financial incentives encourage their use. Applying Fair Information Practice principles to EHRs necessitates balancing patients' rights to control their personal information with providers' data needs to deliver safe, high-quality care. We describe the technical and organizational challenges faced in capturing patients' preferences for patient-controlled EHR access and applying those preferences to an existing EHR. We established an online system for capturing patients' preferences for who could view their EHRs (listing all participating clinic providers individually and categorically-physicians, nurses, other staff) and what data to redact (none, all, or by specific categories of sensitive data or patient age). We then modified existing data-viewing software serving a state-wide health information exchange and a large urban health system and its primary care clinics to allow patients' preferences to guide data displays to providers. Patients could allow or restrict data displays to all clinicians and staff in a demonstration primary care clinic, categories of providers (physicians, nurses, others), or individual providers. They could also restrict access to all EHR data or any or all of five categories of sensitive data (mental and reproductive health, sexually transmitted diseases, HIV/AIDS, and substance abuse) and for specific patient ages. The EHR viewer displayed data via reports, data flowsheets, and coded and free text data displayed by Google-like searches. Unless patients recorded restrictions, by default all requested data were displayed to all providers. Data patients wanted restricted were not displayed, with no indication they were redacted. Technical barriers prevented redacting restricted information in free textnotes. The program allowed providers to hit a "Break the Glass" button to override patients' restrictions, recording the date, time, and next screen viewed. Establishing patient-control over EHR data displays was complex and required ethical, clinical, database, and programming expertise and difficult choices to overcome technical and health system constraints. Assessing patients' preferences for access to their EHRs and applying them in clinical practice requires wide-ranging technical, clinical, and bioethical expertise, to make tough choices to overcome significant technical and organization challenges.

Simulation of patient flow in multiple healthcare units using process and data mining techniques for model identification.

PubMed

Kovalchuk, Sergey V; Funkner, Anastasia A; Metsker, Oleg G; Yakovlev, Aleksey N

2018-06-01

An approach to building a hybrid simulation of patient flow is introduced with a combination of data-driven methods for automation of model identification. The approach is described with a conceptual framework and basic methods for combination of different techniques. The implementation of the proposed approach for simulation of the acute coronary syndrome (ACS) was developed and used in an experimental study. A combination of data, text, process mining techniques, and machine learning approaches for the analysis of electronic health records (EHRs) with discrete-event simulation (DES) and queueing theory for the simulation of patient flow was proposed. The performed analysis of EHRs for ACS patients enabled identification of several classes of clinical pathways (CPs) which were used to implement a more realistic simulation of the patient flow. The developed solution was implemented using Python libraries (SimPy, SciPy, and others). The proposed approach enables more a realistic and detailed simulation of the patient flow within a group of related departments. An experimental study shows an improved simulation of patient length of stay for ACS patient flow obtained from EHRs in Almazov National Medical Research Centre in Saint Petersburg, Russia. The proposed approach, methods, and solutions provide a conceptual, methodological, and programming framework for the implementation of a simulation of complex and diverse scenarios within a flow of patients for different purposes: decision making, training, management optimization, and others. Copyright © 2018 Elsevier Inc. All rights reserved.

Clinical experiences of collaborative imaging diagnosis in Shanghai district healthcare services

NASA Astrophysics Data System (ADS)

Zhang, Kai; Ling, Tonghui; Yang, Yuanyuan; Sun, Jianyong; Wang, Mingqing; Zhang, Jianguo

2016-03-01

To improve healthcare service quality with balancing healthcare resources between large and small hospitals, as well as reducing costs, each district health administration in Shanghai with more than 24 million citizens has built image-enabled electronic healthcare records (iEHR) system to share patient medical records and encourage patients to visit small hospitals for initial evaluations and preliminary diagnoses first, then go to large hospitals to have better specialists' services. We implemented solution for iEHR systems, based on the IHE XDS-I integration profile and installed the systems in more than 100 hospitals cross three districts in Shanghai and one city in Jiangsu Province in last few years. Here, we give operational results of these systems in these four districts and evaluated the performance of the systems in servicing the regional collaborative imaging diagnosis.

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.

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.

i3b3: Infobuttons for i2b2 as a Mechanism for Investigating the Information Needs of Clinical Researchers.

PubMed

Kennell, Timothy; Dempsey, Donald M; Cimino, James J

2016-01-01

The information needs of clinicians, as they interact with the EHR, are well-studied. Clinical researchers also interact with the EHR and, while they might be expected to have some similar needs, the unique needs that arise due to nature of their work remain largely unstudied. For clinicians, infobuttons (context-aware hyperlinks) provide a mechanism of studying these information needs. Here we describe the integration of infobuttons into i2b2, a popular data warehouse commonly used by clinical researchers, using a plugin. A preliminary survey of i2b2 developers suggests a general interest in infobuttons for i2b2 and indicates good likelihood for their deployment, where they may be used as a tool for further studying these needs in greater detail.

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

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.

Applying representational state transfer (REST) architecture to archetype-based electronic health record systems

PubMed Central

2013-01-01

Background The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content. The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored. Results The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored. A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping. Conclusions Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications. PMID:23656624

Applying representational state transfer (REST) architecture to archetype-based electronic health record systems.

PubMed

Sundvall, Erik; Nyström, Mikael; Karlsson, Daniel; Eneling, Martin; Chen, Rong; Örman, Håkan

2013-05-09

The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content.The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored. The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored.A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping. Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications.

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.

A loosely coupled framework for terminology controlled distributed EHR search for patient cohort identification in clinical research.

PubMed

Zhao, Lei; Lim Choi Keung, Sarah N; Taweel, Adel; Tyler, Edward; Ogunsina, Ire; Rossiter, James; Delaney, Brendan C; Peterson, Kevin A; Hobbs, F D Richard; Arvanitis, Theodoros N

2012-01-01

Heterogeneous data models and coding schemes for electronic health records present challenges for automated search across distributed data sources. This paper describes a loosely coupled software framework based on the terminology controlled approach to enable the interoperation between the search interface and heterogeneous data sources. Software components interoperate via common terminology service and abstract criteria model so as to promote component reuse and incremental system evolution.

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.

Bridging clinical researcher perceptions and health IT realities: A case study of stakeholder creep.

PubMed

Panyard, Daniel J; Ramly, Edmond; Dean, Shannon M; Bartels, Christie M

2018-02-01

We present a case report detailing a challenge in health information technology (HIT) project implementations we term "stakeholder creep": not thoroughly identifying which stakeholders need to be involved and why before starting a project, consequently not understanding the true effort, skill sets, social capital, and time required to complete the project. A root cause analysis was performed post-implementation to understand what led to stakeholder creep. HIT project stakeholders were given a questionnaire to comment on these misconceptions and a proposed implementation tool to help mitigate stakeholder creep. Stakeholder creep contributed to an unexpected increase in time (3-month delayed go-live) and effort (68% over expected HIT work hours). Four main clinician/researcher misconceptions were identified that contributed to the development of stakeholder creep: 1) that EHR IT is a single group; 2) that all EHR IT members know the entire EHR functionality; 3) that changes to an EHR need the input of just a single EHR IT member; and 4) that the technological complexity of a project mirrors the clinical complexity. HIT project stakeholders similarly perceived clinicians/researchers to hold these misconceptions. The proposed stakeholder planning tool was perceived to be feasible and helpful. Stakeholder creep can negatively affect HIT project implementations. Projects may be susceptible to stakeholder creep when clinicians/researchers hold misconceptions related to HIT organization and processes. Implementation tools, such as the proposed stakeholder checklist, could be helpful in preempting and mitigating the effect of stakeholder creep. Copyright © 2017 Elsevier B.V. All rights reserved.

Physician Interaction with Electronic Medical Records: A Qualitative Study

ERIC Educational Resources Information Center

Noteboom, Cherie Bakker

2010-01-01

The integration of EHR (Electronic Health Records) in IT infrastructures supporting organizations enable improved access to and recording of patient data, enhanced ability to make better and more-timely decisions, and improved quality and reduced errors. Despite these benefits, there are mixed results as to the use of EHR. The literature suggests…

Electronic health records implementation: an evaluation of information system impact and contingency factors.

PubMed

Nguyen, Lemai; Bellucci, Emilia; Nguyen, Linh Thuy

2014-11-01

This paper provides a review of EHR (electronic health record) implementations around the world and reports on findings including benefits and issues associated with EHR implementation. A systematic literature review was conducted from peer-reviewed scholarly journal publications from the last 10 years (2001-2011). The search was conducted using various publication collections including: Scopus, Embase, Informit, Medline, Proquest Health and Medical Complete. This paper reports on our analysis of previous empirical studies of EHR implementations. We analysed data based on an extension of DeLone and McLean's information system (IS) evaluation framework. The extended framework integrates DeLone and McLean's dimensions, including information quality, system quality, service quality, intention of use and usage, user satisfaction and net benefits, together with contingent dimensions, including systems development, implementation attributes and organisational aspects, as identified by Van der Meijden and colleagues. A mix of evidence-based positive and negative impacts of EHR was found across different evaluation dimensions. In addition, a number of contingent factors were found to contribute to successful implementation of EHR. This review does not include white papers or industry surveys, non-English papers, or those published outside the review time period. This review confirms the potential of this technology to aid patient care and clinical documentation; for example, in improved documentation quality, increased administration efficiency, as well as better quality, safety and coordination of care. Common negative impacts include changes to workflow and work disruption. Mixed observations were found on EHR quality, adoption and satisfaction. The review warns future implementers of EHR to carefully undertake the technology implementation exercise. The review also informs healthcare providers of contingent factors that potentially affect EHR development and implementation in an organisational setting. Our findings suggest a lack of socio-technical connectives between the clinician, the patient and the technology in developing and implementing EHR and future developments in patient-accessible EHR. In addition, a synthesis of DeLone and McLean's framework and Van der Meijden and colleagues' contingent factors has been found useful in comprehensively understanding and evaluating EHR implementations. Crown Copyright © 2014. Published by Elsevier Ireland Ltd. All rights reserved.

Interventions to increase physician efficiency and comfort with an electronic health record system.

PubMed

Jalota, L; Aryal, M R; Mahmood, M; Wasser, T; Donato, A

2015-01-01

To determine comfort when using the Electronic Health Record (EHR) and increase in documentation efficiency after an educational intervention for physicians to improve their transition to a new EHR. This study was a single-center randomized, parallel, non-blinded controlled trial of real-time, focused educational interventions by physician peers in addition to usual training in the intervention arm compared with usual training in the control arm. Participants were 44 internal medicine physicians and residents stratified to groups using a survey of comfort with electronic media during rollout of a system-wide EHR and order entry system. Outcomes were median time to complete a progress note, notes completed after shift, and comfort with EHR at 20 and 40 shifts. In the intervention group, 73 education sessions averaging 14.4 (SD: 7.7) minutes were completed with intervention group participants, who received an average of 3.47 (SD: 2.1) interventions. Intervention group participants decreased their time to complete a progress note more quickly than controls over 30 shifts (p < 0.001) and recorded significantly fewer progress notes after scheduled duty hours (77 versus 292, p < 0.001). Comfort with EHRs increased significantly in both groups from baseline but did not differ significantly by group. Intervention group participants felt that the intervention was more helpful than their standard training (3.47 versus 1.95 on 4-point scale). Physicians teaching physicians during clinical work improved physician efficiency but not comfort with EHRs. More study is needed to determine best methods to assist those most challenged with new EHR rollouts.

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

Effect of pay-for-performance incentives on quality of care in small practices with electronic health records: a randomized trial.

PubMed

Bardach, Naomi S; Wang, Jason J; De Leon, Samantha F; Shih, Sarah C; Boscardin, W John; Goldman, L Elizabeth; Dudley, R Adams

2013-09-11

Most evaluations of pay-for-performance (P4P) incentives have focused on large-group practices. Thus, the effect of P4P in small practices, where many US residents receive care, is largely unknown. Furthermore, whether electronic health records (EHRs) with chronic disease management capabilities support small-practice response to P4P has not been studied. To assess the effect of P4P incentives on quality in EHR-enabled small practices in the context of an established quality improvement initiative. A cluster-randomized trial of small (<10 clinicians) primary care clinics in New York City from April 2009 through March 2010. A city program provided all participating clinics with the same EHR software with decision support and patient registry functionalities and quality improvement specialists offering technical assistance. Incentivized clinics were paid for each patient whose care met the performance criteria, but they received higher payments for patients with comorbidities, who had Medicaid insurance, or who were uninsured (maximum payments: $200/patient; $100,000/clinic). Quality reports were given quarterly to both the intervention and control groups. Comparison of differences in performance improvement, from the beginning to the end of the study, between control and intervention clinics for aspirin or antithrombotic prescription, blood pressure control, cholesterol control, and smoking cessation interventions. Mixed-effects logistic regression was used to account for clustering of patients within clinics, with a treatment by time interaction term assessing the statistical significance of the effect of the intervention. Participating clinics (n = 42 for each group) had similar baseline characteristics, with a mean of 4592 (median, 2500) patients at the intervention group clinics and 3042 (median, 2000) at the control group clinics. Intervention clinics had greater adjusted absolute improvement in rates of appropriate antithrombotic prescription (12.0% vs 6.1%, difference: 6.0% [95% CI, 2.2% to 9.7%], P = .001 for interaction term), blood pressure control (no comorbidities: 9.7% vs 4.3%, difference: 5.5% [95% CI, 1.6% to 9.3%], P = .01 for interaction term; with diabetes mellitus: 9.0% vs 1.2%, difference: 7.8% [95% CI, 3.2% to 12.4%], P = .007 for interaction term; with diabetes mellitus or ischemic vascular disease: 9.5% vs 1.7%, difference: 7.8% [95% CI, 3.0% to 12.6%], P = .01 for interaction term), and in smoking cessation interventions (12.4% vs 7.7%, difference: 4.7% [95% CI, -0.3% to 9.6%], P = .02 for interaction term). Intervention clinics performed better on all measures for Medicaid and uninsured patients except cholesterol control, but no differences were statistically significant. Among small EHR-enabled clinics, a P4P incentive program compared with usual care resulted in modest improvements in cardiovascular care processes and outcomes. Because most proposed P4P programs are intended to remain in place more than a year, further research is needed to determine whether this effect increases or decreases over time. clinicaltrials.gov Identifier: NCT00884013.

A needs assessment of health information technology for improving care coordination in three leading patient-centered medical homes.

PubMed

Richardson, Joshua E; Vest, Joshua R; Green, Cori M; Kern, Lisa M; Kaushal, Rainu

2015-07-01

We investigated ways that patient-centered medical homes (PCMHs) are currently using health information technology (IT) for care coordination and what types of health IT are needed to improve care coordination. A multi-disciplinary team of researchers conducted semi-structured telephone interviews with 28 participants from 3 PCMHs in the United States. Participants included administrators and clinicians from PCMHs, electronic health record (EHR) and health information exchange (HIE) representatives, and policy makers. Participants identified multiple barriers to care coordination using current health IT tools. We identified five areas in which health IT can improve care coordination in PCMHs: 1) monitoring patient populations, 2) notifying clinicians and other staff when specific patients move across care settings, 3) collaborating around patients, 4) reporting activities, and 5) interoperability. To accomplish these tasks, many participants described using homegrown care coordination systems separate from EHRs. The participants in this study have resources, experience, and expertise with using health IT for care coordination, yet they still identified multiple areas for improvement. We hypothesize that focusing health IT development in the five areas we identified can enable more effective care coordination. Key findings from this work are that homegrown systems apart from EHRs are currently used to support care coordination and, also, that reporting tools are key components of care coordination. New health IT that enables monitoring, notifying, collaborating, reporting, and interoperability would enhance care coordination within PCMHs beyond what current health IT enables. © 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.

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.

Experts speak: advice from key informants to small, rural hospitals on implementing the electronic health record system.

PubMed

Craven, Catherine K; Sievert, MaryEllen C; Hicks, Lanis L; Alexander, Gregory L; Hearne, Leonard B; Holmes, John H

2013-01-01

The US government has allocated $30 billion dollars to implement Electronic Health Records (EHRs) in hospitals and provider practices through a policy called Meaningful Use. Small, rural hospitals, particularly those designated as Critical Access Hospitals (CAHs), comprising nearly a quarter of US hospitals, had not implemented EHRs before. Little is known on implementation in this setting. We interviewed a spectrum of 31 experts in the domain. The interviews were then analyzed qualitatively to ascertain the expert recommendations. Nineteen themes emerged. The pool of experts included staff from CAHs that had recently implemented EHRs. We were able to compare their answers with those of other experts and make recommendations for stakeholders. CAH peer experts focused less on issues such as physician buy-in, communication, and the EHR team. None of them indicated concern or focus on clinical decision support systems, leadership, or governance. They were especially concerned with system selection, technology, preparatory work and a need to know more about workflow and optimization. These differences were explained by the size and nature of these small hospitals.

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

Designing for privacy management in hospitals: Understanding the gap between user activities and IT staff's understandings.

PubMed

Eikey, Elizabeth V; Murphy, Alison R; Reddy, Madhu C; Xu, Heng

2015-12-01

We examined the role of privacy in collaborative clinical work and how it is understood by hospital IT staff. The purpose of our study was to identify the gaps between hospital IT staff members' perceptions of how electronic health record (EHR) users' protect the privacy of patient information and how users actually protect patients' private information in their daily collaborative activities. Since the IT staff play an important role in implementing and maintaining the EHR, any gaps that exist between the IT staff's perceptions of user work practices and the users' actual work practices can result in a number of problems in the configuration, implementation, or customization of the EHR, which can lead to collaboration challenges, interrupted workflow, and privacy breaches. We used qualitative data collection methods for this study. We conducted semi-structured interviews with 20 hospital IT staff members. We also conducted observations of EHR users in the in-patient units of the same hospital. We identified gaps in IT staff's understandings of users' work activities, especially in regards to privacy-compromising workarounds that are used by users and why they are used. We discuss the reasons why this gap may exist between IT staff and users and ways to improve IT staff's understanding of why users perform certain privacy-compromising workarounds. A hospital's IT staff face a daunting task in ensuring users' collaborative work practices are supported by the system while providing effective privacy mechanisms. In order to achieve both goals, the IT staff must have a clear understanding of their users' practices. However, as this study highlights, there may be a mismatch between the IT staff's understandings of how users protect patient privacy and how users actually protect privacy. Copyright © 2015. Published by Elsevier Ireland Ltd.

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

A Practical Approach to Governance and Optimization of Structured Data Elements.

PubMed

Collins, Sarah A; Gesner, Emily; Morgan, Steven; Mar, Perry; Maviglia, Saverio; Colburn, Doreen; Tierney, Diana; Rocha, Roberto

2015-01-01

Definition and configuration of clinical content in an enterprise-wide electronic health record (EHR) implementation is highly complex. Sharing of data definitions across applications within an EHR implementation project may be constrained by practical limitations, including time, tools, and expertise. However, maintaining rigor in an approach to data governance is important for sustainability and consistency. With this understanding, we have defined a practical approach for governance of structured data elements to optimize data definitions given limited resources. This approach includes a 10 step process: 1) identification of clinical topics, 2) creation of draft reference models for clinical topics, 3) scoring of downstream data needs for clinical topics, 4) prioritization of clinical topics, 5) validation of reference models for clinical topics, and 6) calculation of gap analyses of EHR compared against reference model, 7) communication of validated reference models across project members, 8) requested revisions to EHR based on gap analysis, 9) evaluation of usage of reference models across project, and 10) Monitoring for new evidence requiring revisions to reference model.

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.

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.

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.

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.

Assessing organizational capacity for achieving meaningful use of electronic health records.

PubMed

Shea, Christopher M; Malone, Robb; Weinberger, Morris; Reiter, Kristin L; Thornhill, Jonathan; Lord, Jennifer; Nguyen, Nicholas G; Weiner, Bryan J

2014-01-01

Health care institutions are scrambling to manage the complex organizational change required for achieving meaningful use (MU) of electronic health records (EHR). Assessing baseline organizational capacity for the change can be a useful step toward effective planning and resource allocation. The aim of this article is to describe an adaptable method and tool for assessing organizational capacity for achieving MU of EHR. Data on organizational capacity (people, processes, and technology resources) and barriers are presented from outpatient clinics within one integrated health care delivery system; thus, the focus is on MU requirements for eligible professionals, not eligible hospitals. We conducted 109 interviews with representatives from 46 outpatient clinics. Most clinics had core elements of the people domain of capacity in place. However, the process domain was problematic for many clinics, specifically, capturing problem lists as structured data and having standard processes for maintaining the problem list in the EHR. Also, nearly half of all clinics did not have methods for tracking compliance with their existing processes. Finally, most clinics maintained clinical information in multiple systems, not just the EHR. The most common perceived barriers to MU for eligible professionals included EHR functionality, changes to workflows, increased workload, and resistance to change. Organizational capacity assessments provide a broad institutional perspective and an in-depth clinic-level perspective useful for making resource decisions and tailoring strategies to support the MU change effort for eligible professionals.

Method to integrate clinical guidelines into the electronic health record (EHR) by applying the archetypes approach.

PubMed

Garcia, Diego; Moro, Claudia Maria Cabral; Cicogna, Paulo Eduardo; Carvalho, Deborah Ribeiro

2013-01-01

Clinical guidelines are documents that assist healthcare professionals, facilitating and standardizing diagnosis, management, and treatment in specific areas. Computerized guidelines as decision support systems (DSS) attempt to increase the performance of tasks and facilitate the use of guidelines. Most DSS are not integrated into the electronic health record (EHR), ordering some degree of rework especially related to data collection. This study's objective was to present a method for integrating clinical guidelines into the EHR. The study developed first a way to identify data and rules contained in the guidelines, and then incorporate rules into an archetype-based EHR. The proposed method tested was anemia treatment in the Chronic Kidney Disease Guideline. The phases of the method are: data and rules identification; archetypes elaboration; rules definition and inclusion in inference engine; and DSS-EHR integration and validation. The main feature of the proposed method is that it is generic and can be applied toany type of guideline.

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.

Evidence that electronic health records can promote physician counseling for healthy behaviors.

PubMed

Bae, Jaeyong; Hockenberry, Jason M; Rask, Kimberly J; Becker, Edmund R

Health behavior counseling services may help patients manage chronic conditions effectively and slow disease progression. Studies show, however, that many providers fail to provide these services because of time constraints and inability to tailor counseling to individual patient needs. Electronic health records (EHRs) have the potential to increase appropriate counseling by providing pertinent patient information at the point of care and clinical decision support. This study estimates the impact of select EHR functionalities on the rate of health behavior counseling provided during primary care visits. Multivariable regression analyses of the 2007-2010 National Ambulatory Medical Care Survey were conducted to examine whether eight EHR components representing four core functionalities of EHR systems were correlated with the rate of health behavior counseling services. Propensity score matching was used to control for confounding factors given the use of observational data. To address concerns that EHR may only lead to improved documentation of counseling services and not necessarily improved care, the association of EHR functionalities with prescriptions for smoking cessation medications was also estimated. The use of an EHR system with health information and data, order entry and management, result management, decision support, and a notification system for abnormal test results was associated with an approximately 25% increase in the probability of health behavior counseling delivered. Clinical reminders were associated with more health behavior counseling services when available in combination with patient problem lists. The laboratory results viewer was also associated with more counseling services when implemented with a notification system for abnormal results. An EHR system with key supportive functionalities can enhance delivery of preventive health behavior counseling services in primary care settings. Meaningful use criteria should be evaluated to ensure that they encourage the adoption of EHR systems with those functionalities shown to improve clinical care.

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.

Code Status Reconciliation to Improve Identification and Documentation of Code Status in Electronic Health Records.

PubMed

Jain, Viral G; Greco, Peter J; Kaelber, David C

2017-03-08

Code status (CS) of a patient (part of their end-of-life wishes) can be critical information in healthcare delivery, which can change over time, especially at transitions of care. Although electronic health record (EHR) tools exist for medication reconciliation across transitions of care, much less attention is given to CS, and standard EHR tools have not been implemented for CS reconciliation (CSR). Lack of CSR creates significant potential patient safety and quality of life issues. To study the tools, workflow, and impact of clinical decision support (CDS) for CSR. We established rules for CS implementation in our EHR. At admission, a CS is required as part of a patient's admission order set. Using standard CDS tools in our EHR, we built an interruptive alert for CSR at discharge if a patient did not have the same inpatient (current) CS at discharge as that prior to admission CS. Of 80,587 admissions over a four year period (2 years prior to and post CSR implementation), CS discordance was seen in 3.5% of encounters which had full code status prior to admission, but Do Not Resuscitate (DNR) CS at discharge. In addition, 1.4% of the encounters had a different variant of the DNR CS at discharge when compared with CS prior to admission. On pre-post CSR implementation analysis, DNR CS per 1000 admissions per month increased significantly among patients discharged and in patients being admitted (mean ± SD: 85.36 ± 13.69 to 399.85 ± 182.86, p<0.001; and 1.99 ± 1.37 vs 16.70 ± 4.51, p<0.001, respectively). EHR enabled CSR is effective and represents a significant informatics opportunity to help honor patients' end-of-life wishes. CSR represents one example of non-medication reconciliation at transitions of care that should be considered in all EHRs to improve care quality and patient safety.

Benefits and drawbacks of electronic health record systems

PubMed Central

Menachemi, Nir; Collum, Taleah H

2011-01-01

The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 that was signed into law as part of the “stimulus package” represents the largest US initiative to date that is designed to encourage widespread use of electronic health records (EHRs). In light of the changes anticipated from this policy initiative, the purpose of this paper is to review and summarize the literature on the benefits and drawbacks of EHR systems. Much of the literature has focused on key EHR functionalities, including clinical decision support systems, computerized order entry systems, and health information exchange. Our paper describes the potential benefits of EHRs that include clinical outcomes (eg, improved quality, reduced medical errors), organizational outcomes (eg, financial and operational benefits), and societal outcomes (eg, improved ability to conduct research, improved population health, reduced costs). Despite these benefits, studies in the literature highlight drawbacks associated with EHRs, which include the high upfront acquisition costs, ongoing maintenance costs, and disruptions to workflows that contribute to temporary losses in productivity that are the result of learning a new system. Moreover, EHRs are associated with potential perceived privacy concerns among patients, which are further addressed legislatively in the HITECH Act. Overall, experts and policymakers believe that significant benefits to patients and society can be realized when EHRs are widely adopted and used in a “meaningful” way. PMID:22312227

Validating archetypes for the Multiple Sclerosis Functional Composite.

PubMed

Braun, Michael; Brandt, Alexander Ulrich; Schulz, Stefan; Boeker, Martin

2014-08-03

Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time-consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions.This case study provides evidence that both community- and tool-enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model.

Validating archetypes for the Multiple Sclerosis Functional Composite

PubMed Central

2014-01-01

Background Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. Methods A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Results Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time-consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. Conclusions The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions. This case study provides evidence that both community- and tool-enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model. PMID:25087081

Clinical height measurements are unreliable: a call for improvement.

PubMed

Mikula, A L; Hetzel, S J; Binkley, N; Anderson, P A

2016-10-01

Height measurements are currently used to guide imaging decisions that assist in osteoporosis care, but their clinical reliability is largely unknown. We found both clinical height measurements and electronic health record height data to be unreliable. Improvement in height measurement is needed to improve osteoporosis care. The aim of this study is to assess the accuracy and reliability of clinical height measurement in a university healthcare clinical setting. Electronic health record (EHR) review, direct measurement of clinical stadiometer accuracy, and observation of staff height measurement technique at outpatient facilities of the University of Wisconsin Hospital and Clinics. We examined 32 clinical stadiometers for reliability and observed 34 clinic staff perform height measurements at 12 outpatient primary care and specialty clinics. An EHR search identified 4711 men and women age 43 to 89 with no known metabolic bone disease who had more than one height measurement over 3 months. The short study period and exclusion were selected to evaluate change in recorded height not due to pathologic processes. Mean EHR recorded height change (first to last measurement) was -0.02 cm (SD 1.88 cm). Eighteen percent of patients had height measurement differences noted in the EHR of ≥2 cm over 3 months. The technical error of measurement (TEM) was 1.77 cm with a relative TEM of 1.04 %. None of the staff observed performing height measurements followed all recommended height measurement guidelines. Fifty percent of clinic staff reported they on occasion enter patient reported height into the EHR rather than performing a measurement. When performing direct measurements on stadiometers, the mean difference from a gold standard length was 0.24 cm (SD 0.80). Nine percent of stadiometers examined had an error of >1.5 cm. Clinical height measurements and EHR recorded height results are unreliable. Improvement in this measure is needed as an adjunct to improve osteoporosis care.

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

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.

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

New Unintended Adverse Consequences of Electronic Health Records

PubMed Central

Wright, A.; Ash, J.; Singh, H.

2016-01-01

Summary Although the health information technology industry has made considerable progress in the design, development, implementation, and use of electronic health records (EHRs), the lofty expectations of the early pioneers have not been met. In 2006, the Provider Order Entry Team at Oregon Health & Science University described a set of unintended adverse consequences (UACs), or unpredictable, emergent problems associated with computer-based provider order entry implementation, use, and maintenance. Many of these originally identified UACs have not been completely addressed or alleviated, some have evolved over time, and some new ones have emerged as EHRs became more widely available. The rapid increase in the adoption of EHRs, coupled with the changes in the types and attitudes of clinical users, has led to several new UACs, specifically: complete clinical information unavailable at the point of care; lack of innovations to improve system usability leading to frustrating user experiences; inadvertent disclosure of large amounts of patient-specific information; increased focus on computer-based quality measurement negatively affecting clinical workflows and patient-provider interactions; information overload from marginally useful computer-generated data; and a decline in the development and use of internally-developed EHRs. While each of these new UACs poses significant challenges to EHR developers and users alike, they also offer many opportunities. The challenge for clinical informatics researchers is to continue to refine our current systems while exploring new methods of overcoming these challenges and developing innovations to improve EHR interoperability, usability, security, functionality, clinical quality measurement, and information summarization and display. PMID:27830226

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

The Hub Population Health System: distributed ad hoc queries and alerts

PubMed Central

Anane, Sheila; Taverna, John; Amirfar, Sam; Stubbs-Dame, Remle; Singer, Jesse

2011-01-01

The Hub Population Health System enables the creation and distribution of queries for aggregate count information, clinical decision support alerts at the point-of-care for patients who meet specified conditions, and secure messages sent directly to provider electronic health record (EHR) inboxes. Using a metronidazole medication recall, the New York City Department of Health was able to determine the number of affected patients and message providers, and distribute an alert to participating practices. As of September 2011, the system is live in 400 practices and within a year will have over 532 practices with 2500 providers, representing over 2.5 million New Yorkers. The Hub can help public health experts to evaluate population health and quality improvement activities throughout the ambulatory care network. Multiple EHR vendors are building these features in partnership with the department's regional extension center in anticipation of new meaningful use requirements. PMID:22071531

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

Automated Methods to Extract Patient New Information from Clinical Notes in Electronic Health Record Systems

ERIC Educational Resources Information Center

Zhang, Rui

2013-01-01

The widespread adoption of Electronic Health Record (EHR) has resulted in rapid text proliferation within clinical care. Clinicians' use of copying and pasting functions in EHR systems further compounds this by creating a large amount of redundant clinical information in clinical documents. A mixture of redundant information (especially outdated…

A Semantic Web-based System for Managing Clinical Archetypes.

PubMed

Fernandez-Breis, Jesualdo Tomas; Menarguez-Tortosa, Marcos; Martinez-Costa, Catalina; Fernandez-Breis, Eneko; Herrero-Sempere, Jose; Moner, David; Sanchez, Jesus; Valencia-Garcia, Rafael; Robles, Montserrat

2008-01-01

Archetypes facilitate the sharing of clinical knowledge and therefore are a basic tool for achieving interoperability between healthcare information systems. In this paper, a Semantic Web System for Managing Archetypes is presented. This system allows for the semantic annotation of archetypes, as well for performing semantic searches. The current system is capable of working with both ISO13606 and OpenEHR archetypes.

Secure Messaging in Electronic Health Records and Its Impact on Diabetes Clinical Outcomes: A Systematic Review.

PubMed

Kuo, Alyce; Dang, Stuti

2016-09-01

In 2009, President Barack Obama signed into law the Health Information Technology for Economic and Clinical Health (HITECH) Act, which aims for the universal adoption of electronic health records (EHRs) in primary care settings and "meaningful use" of this technology. The objectives of "meaningful use" are well defined and executed in stages; one of the objectives of stage 2, beginning in 2014, was implementation of a secure messaging system between patients and providers. Secure messaging has been shown to positively affect patients who struggle with managing chronic diseases on a day to day basis. This review aims to assess the clinical evidence supporting the use of secure messaging in EHRs in self-management of diabetes. A systematic search of PubMed was conducted, and 320 results were returned. Of these, 11 were selected based on outlined criteria. Evidence from 7 of the 11 included studies suggests significant improvement in patients' hemoglobin A1c (HbA1c) with the use of secure messaging. However, improvements in patients' secondary outcomes, such as blood pressure and cholesterol, were inconsistent. Further work must be done to determine how to best maximize the potential of available tools such as secure messaging and EHRs to improve patient outcomes.

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.

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.

The Contextualization of Archetypes: Clinical Template Governance.

PubMed

Pedersen, Rune; Ulriksen, Gro-Hilde; Ellingsen, Gunnar

2015-01-01

This paper is a status report from a large-scale openEHR-based EPR project from the North Norway Regional Health Authority. It concerns the standardization of a regional ICT portfolio and the ongoing development of a new process oriented EPR systems encouraged by the unfolding of a national repository for openEHR archetypes. Subject of interest; the contextualization of clinical templates is governed over multiple national boundaries which is complex due to the dependency of clinical resources. From the outset of this, we are interested in how local, regional, and national organizers maneuver to standardize while applying OpenEHR technology.

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.

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.

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.

Analysis of Search on Clinical Narrative within the EHR

ERIC Educational Resources Information Center

Natarajan, Karthik

2012-01-01

Electronic Health Records (EHRs) are used increasingly in the hospital and outpatient settings, and patients are amassing digitized clinical information. On one hand, aggregating all the patient's clinical information can greatly assist health care workers in making sound decisions. On the other hand, it can result in information overload,…

Linking guidelines to Electronic Health Record design for improved chronic disease management.

PubMed

Barretto, Sistine A; Warren, Jim; Goodchild, Andrew; Bird, Linda; Heard, Sam; Stumptner, Markus

2003-01-01

The promise of electronic decision support to promote evidence based practice remains elusive in the context of chronic disease management. We examine the problem of achieving a close relationship of Electronic Health Record (EHR) content to other components of a clinical information system (guidelines, decision support and workflow), particularly linking the decisions made by providers back to the guidelines. We use the openEHR architecture, which allows extension of a core Reference Model via Archetypes to refine the detailed information recording options for specific classes of encounter. We illustrate the use of openEHR for tracking the relationship of a series of clinical encounters to a guideline via a case study of guideline-compliant treatment of hypertension in diabetes. This case study shows the contribution guideline content can have on problem-specific EHR structure and demonstrates the potential for a constructive interaction of electronic decision support and the EHR.

Should medical students track former patients in the electronic health record? An emerging ethical conflict.

PubMed

Brisson, Gregory E; Neely, Kathy Johnson; Tyler, Patrick D; Barnard, Cynthia

2015-08-01

Medical students are increasingly using electronic health records (EHRs) in clerkships, and medical educators should seek opportunities to use this new technology to improve training. One such opportunity is the ability to "track" former patients in the EHR, defined as following up on patients in the EHR for educational purposes for a defined period of time after they have left one's direct care. This activity offers great promise in clinical training by enabling students to audit their diagnostic impressions and follow the clinical history of illness in a manner not possible in the era of paper charting. However, tracking raises important questions about the ethical use of protected health information, including concerns about compromising patient autonomy, resulting in a conflict between medical education and patient privacy. The authors offer critical analysis of arguments on both sides and discuss strategies to balance the ethical conflict by optimizing outcomes and mitigating harms. They observe that tracking improves training, thus offering long-lasting benefits to society, and is supported by the principle of distributive justice. They conclude that students should be permitted to track for educational purposes, but only with defined limits to safeguard patient autonomy, including obtaining permission from patients, having legitimate educational intent, and self-restricting review of records to those essential for training. Lastly, the authors observe that this conflict will become increasingly important with completion of the planned Nationwide Health Information Network and emphasize the need for national guidelines on tracking patients in an ethically appropriate manner.

Workarounds Emerging From Electronic Health Record System Usage: Consequences for Patient Safety, Effectiveness of Care, and Efficiency of Care.

PubMed

Blijleven, Vincent; Koelemeijer, Kitty; Wetzels, Marijntje; Jaspers, Monique

2017-10-05

Health care providers resort to informal temporary practices known as workarounds for handling exceptions to normal workflow unintendedly imposed by electronic health record systems (EHRs). Although workarounds may seem favorable at first sight, they are generally suboptimal and may jeopardize patient safety, effectiveness of care, and efficiency of care. Research into the scope and impact of EHR workarounds on patient care processes is scarce. This paper provides insight into the effects of EHR workarounds on organizational workflows and outcomes of care services by identifying EHR workarounds and determining their rationales, scope, and impact on health care providers' workflows, patient safety, effectiveness of care, and efficiency of care. Knowing the rationale of a workaround provides valuable clues about the source of origin of each workaround and how each workaround could most effectively be resolved. Knowing the scope and impact a workaround has on EHR-related safety, effectiveness, and efficiency provides insight into how to address related concerns. Direct observations and follow-up semistructured interviews with 31 physicians, 13 nurses, and 3 clerks and qualitative bottom-up coding techniques was used to identify, analyze, and classify EHR workarounds. The research was conducted within 3 specialties and settings at a large university hospital. Rationales were associated with work system components (persons, technology and tools, tasks, organization, and physical environment) of the Systems Engineering Initiative for Patient Safety (SEIPS) framework to reveal their source of origin as well as to determine the scope and the impact of each EHR workaround from a structure-process-outcome perspective. A total of 15 rationales for EHR workarounds were identified of which 5 were associated with persons, 4 with technology and tools, 4 with the organization, and 2 with the tasks. Three of these 15 rationales for EHR workarounds have not been identified in prior research: data migration policy, enforced data entry, and task interference. EHR workaround rationales associated with different SEIPS work system components demand a different approach to be resolved. Persons-related workarounds may most effectively be resolved through personal training, organization-related workarounds through reviewing organizational policy and regulations, tasks-related workarounds through process redesign, and technology- and tools-related workarounds through EHR redesign efforts. Furthermore, insights gained from knowing a workaround's degree of influence as well as impact on patient safety, effectiveness of care, and efficiency of care can inform design and redesign of EHRs to further align EHR design with work contexts, subsequently leading to better organization and (safe) provision of care. In doing so, a research team in collaboration with all stakeholders could use the SEIPS framework to reflect on the current and potential future configurations of the work system to prevent unfavorable workarounds from occurring and how a redesign of the EHR would impact interactions between the work system components. ©Vincent Blijleven, Kitty Koelemeijer, Marijntje Wetzels, Monique Jaspers. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 05.10.2017.

Using geographic information systems (GIS) to identify communities in need of health insurance outreach: An OCHIN practice-based research network (PBRN) report.

PubMed

Angier, Heather; Likumahuwa, Sonja; Finnegan, Sean; Vakarcs, Trisha; Nelson, Christine; Bazemore, Andrew; Carrozza, Mark; DeVoe, Jennifer E

2014-01-01

Our practice-based research network (PBRN) is conducting an outreach intervention to increase health insurance coverage for patients seen in the network. To assist with outreach site selection, we sought an understandable way to use electronic health record (EHR) data to locate uninsured patients. Health insurance information was displayed within a web-based mapping platform to demonstrate the feasibility of using geographic information systems (GIS) to visualize EHR data. This study used EHR data from 52 clinics in the OCHIN PBRN. We included cross-sectional coverage data for patients aged 0 to 64 years with at least 1 visit to a study clinic during 2011 (n = 228,284). Our PBRN was successful in using GIS to identify intervention sites. Through use of the maps, we found geographic variation in insurance rates of patients seeking care in OCHIN PBRN clinics. Insurance rates also varied by age: The percentage of adults without insurance ranged from 13.2% to 86.8%; rates of children lacking insurance ranged from 1.1% to 71.7%. GIS also showed some areas of households with median incomes that had low insurance rates. EHR data can be imported into a web-based GIS mapping tool to visualize patient information. Using EHR data, we were able to observe smaller areas than could be seen using only publicly available data. Using this information, we identified appropriate OCHIN PBRN clinics for dissemination of an EHR-based insurance outreach intervention. GIS could also be used by clinics to visualize other patient-level characteristics to target clinic outreach efforts or interventions. © Copyright 2014 by the American Board of Family Medicine.

A long-term follow-up evaluation of electronic health record prescribing safety

PubMed Central

Abramson, Erika L; Malhotra, Sameer; Osorio, S Nena; Edwards, Alison; Cheriff, Adam; Cole, Curtis; Kaushal, Rainu

2013-01-01

Objective To be eligible for incentives through the Electronic Health Record (EHR) Incentive Program, many providers using older or locally developed EHRs will be transitioning to new, commercial EHRs. We previously evaluated prescribing errors made by providers in the first year following transition from a locally developed EHR with minimal prescribing clinical decision support (CDS) to a commercial EHR with robust CDS. Following system refinements, we conducted this study to assess the rates and types of errors 2 years after transition and determine the evolution of errors. Materials and methods We conducted a mixed methods cross-sectional case study of 16 physicians at an academic-affiliated ambulatory clinic from April to June 2010. We utilized standardized prescription and chart review to identify errors. Fourteen providers also participated in interviews. Results We analyzed 1905 prescriptions. The overall prescribing error rate was 3.8 per 100 prescriptions (95% CI 2.8 to 5.1). Error rates were significantly lower 2 years after transition (p<0.001 compared to pre-implementation, 12 weeks and 1 year after transition). Rates of near misses remained unchanged. Providers positively appreciated most system refinements, particularly reduced alert firing. Discussion Our study suggests that over time and with system refinements, use of a commercial EHR with advanced CDS can lead to low prescribing error rates, although more serious errors may require targeted interventions to eliminate them. Reducing alert firing frequency appears particularly important. Our results provide support for federal efforts promoting meaningful use of EHRs. Conclusions Ongoing error monitoring can allow CDS to be optimally tailored and help achieve maximal safety benefits. Clinical Trials Registration ClinicalTrials.gov, Identifier: NCT00603070. PMID:23578816

Does integrating nonurgent, clinically significant radiology alerts within the electronic health record impact closed-loop communication and follow-up?

PubMed Central

Dalal, Anuj K; Sahni, V Anik; Lacson, Ronilda; Khorasani, Ramin

2016-01-01

Objective To assess whether integrating critical result management software—Alert Notification of Critical Results (ANCR)—with an electronic health record (EHR)-based results management application impacts closed-loop communication and follow-up of nonurgent, clinically significant radiology results by primary care providers (PCPs). Materials and Methods This institutional review board-approved study was conducted at a large academic medical center. Postintervention, PCPs could acknowledge nonurgent, clinically significant ANCR-generated alerts (“alerts”) within ANCR or the EHR. Primary outcome was the proportion of alerts acknowledged via EHR over a 24-month postintervention. Chart abstractions for a random sample of alerts 12 months preintervention and 24 months postintervention were reviewed, and the follow-up rate of actionable alerts (eg, performing follow-up imaging, administering antibiotics) was estimated. Pre- and postintervention rates were compared using the Fisher exact test. Postintervention follow-up rate was compared for EHR-acknowledged alerts vs ANCR. Results Five thousand nine hundred and thirty-one alerts were acknowledged by 171 PCPs, with 100% acknowledgement (consistent with expected ANCR functionality). PCPs acknowledged 16% (688 of 4428) of postintervention alerts in the EHR, with the remaining in ANCR. Follow-up was documented for 85 of 90 (94%; 95% CI, 88%-98%) preintervention and 79 of 84 (94%; 95% CI, 87%-97%) postintervention alerts (P > .99). Postintervention, 11 of 14 (79%; 95% CI, 52%-92%) alerts were acknowledged via EHR and 68 of 70 (97%; 95% CI, 90%-99%) in ANCR had follow-up (P = .03). Conclusions Integrating ANCR and EHR provides an additional workflow for acknowledging nonurgent, clinically significant results without significant change in rates of closed-loop communication or follow-up of alerts. PMID:26335982

Evaluating Primary Care Providers' Views on Survivorship Care Plans Generated by an Electronic Health Record System

PubMed Central

Donohue, SarahMaria; Sesto, Mary E.; Hahn, David L.; Buhr, Kevin A.; Jacobs, Elizabeth A.; Sosman, James M.; Andreason, Molly J.; Wiegmann, Douglas A.; Tevaarwerk, Amye J.

2015-01-01

Purpose: Survivorship care plans for cancer survivors may facilitate provider-to-provider communication. Primary care provider (PCP) perspectives on care plan provision and use are limited, especially when care plans are generated by an electronic health record (EHR) system. We sought to examine PCPs' perspectives regarding EHR-generated care plans. Methods: PCPs (N = 160) who were members of the Wisconsin Research and Education Network listserv received a sample 10-page plan (WREN cohort). PCPs (n = 81) who had or were currently seeing survivors enrolled onto one of our survivorship clinical trials received a copy of the survivor's personalized care plan (University of Wisconsin [UW] cohort). Both cohorts received a survey after reviewing the plan. All plans were generated within an EHR. Results: Forty-six and 26 PCPs participated in the WREN and UW cohorts, respectively. PCPs regarded EHR-generated plans as useful in coordinating care (88%), understanding treatments (94%), understanding treatment adverse effects (89%), and supporting clinical decisions (82%). Few felt using EHR-generated plans would disrupt clinic workflow (14%) or take too much time (11%). Most (89%) preferred receiving the plan via EHR. PCPs reported consistent provision (81%) and standard location in the medical record (89%) as key factors facilitating their use of survivorship care plans. Important facilitators of care plan use included a more abbreviated plan, ideally one to three pages (32%), and/or a plan specifically tailored to PCP use (57%). Conclusion: Plans were viewed as useful for coordinating care and making clinical decisions. However, PCPs desired shorter, clinician-oriented plans, accessible within an EHR and delivered and located in a standardized manner. PMID:25804989

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

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

Cross-vendor evaluation of key user-defined clinical decision support capabilities: a scenario-based assessment of certified electronic health records with guidelines for future development

PubMed Central

Wright, Adam; Sittig, Dean F

2015-01-01

Objective Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems. Methods We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin. Results Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules. Conclusion Significant improvements in the EHR certification and implementation procedures are necessary. PMID:26104739

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.

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 capability to electronically exchange clinical information, 2011.

PubMed

Patel, Vaishali; Swain, Matthew J; King, Jennifer; Furukawa, Michael F

2013-10-01

To provide national estimates of physician capability to electronically share clinical information with other providers and to describe variation in exchange capability across states and electronic health record (EHR) vendors using the 2011 National Ambulatory Medical Care Survey Electronic Medical Record Supplement. Survey of a nationally representative sample of nonfederal office-based physicians who provide direct patient care. The survey was administered by mail with telephone follow-up and had a 61% weighted response rate. The overall sample consisted of 4326 respondents. We calculated estimates of electronic exchange capability at the national and state levels, and applied multivariate analyses to examine the association between the capability to exchange different types of clinical information and physician and practice characteristics. In 2011, 55% of physicians had computerized capability to send prescriptions electronically; 67% had the capability to view lab results electronically; 42% were able to incorporate lab results into their EHR; 35% were able to send lab orders electronically; and, 31% exchanged patient clinical summaries with other providers. The strongest predictor of exchange capability is adoption of an EHR. However, substantial variation exists across geography and EHR vendors in exchange capability, especially electronic exchange of clinical summaries. In 2011, a majority of office-based physicians could exchange lab and medication data, and approximately one-third could exchange clinical summaries with patients or other providers. EHRs serve as a key mechanism by which physicians can exchange clinical data, though physicians' capability to exchange varies by vendor and by state.

Evaluation of a Framework to Implement Electronic Health Record Systems Based on the openEHR Standard

NASA Astrophysics Data System (ADS)

Orellana, Diego A.; Salas, Alberto A.; Solarz, Pablo F.; Medina Ruiz, Luis; Rotger, Viviana I.

2016-04-01

The production of clinical information about each patient is constantly increasing, and it is noteworthy that the information is created in different formats and at diverse points of care, resulting in fragmented, incomplete, inaccurate and isolated, health information. The use of health information technology has been promoted as having a decisive impact to improve the efficiency, cost-effectiveness, quality and safety of medical care delivery. However in developing countries the utilization of health information technology is insufficient and lacking of standards among other situations. In the present work we evaluate the framework EHRGen, based on the openEHR standard, as mean to reach generation and availability of patient centered information. The framework has been evaluated through the provided tools for final users, that is, without intervention of computer experts. It makes easier to adopt the openEHR ideas and provides an open source basis with a set of services, although some limitations in its current state conspire against interoperability and usability. However, despite the described limitations respect to usability and semantic interoperability, EHRGen is, at least regionally, a considerable step toward EHR adoption and interoperability, so that it should be supported from academic and administrative institutions.

Community Vital Signs: Taking the Pulse of the Community While Caring for Patients.

PubMed

Hughes, Lauren S; Phillips, Robert L; DeVoe, Jennifer E; Bazemore, Andrew W

2016-01-01

In 2014 both the Institute of Medicine and the National Quality Forum recommended the inclusion of social determinants of health data in electronic health records (EHRs). Both entities primarily focus on collecting socioeconomic and health behavior data directly from individual patients. The burden of reliably, accurately, and consistently collecting such information is substantial, and it may take several years before a primary care team has actionable data available in its EHR. A more reliable and less burdensome approach to integrating clinical and social determinant data exists and is technologically feasible now. Community vital signs-aggregated community-level information about the neighborhoods in which our patients live, learn, work, and play-convey contextual social deprivation and associated chronic disease risks based on where patients live. Given widespread access to "big data" and geospatial technologies, community vital signs can be created by linking aggregated population health data with patient addresses in EHRs. These linked data, once imported into EHRs, are a readily available resource to help primary care practices understand the context in which their patients reside and achieve important health goals at the patient, population, and policy levels. © Copyright 2016 by the American Board of Family Medicine.

Use of large electronic health record databases for environmental epidemiology studies.

EPA Science Inventory

Background: Electronic health records (EHRs) are a ubiquitous component of the United States healthcare system and capture nearly all data collected in a clinic or hospital setting. EHR databases are attractive for secondary data analysis as they may contain detailed clinical rec...

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.

Modifications and integration of the electronic tracking board in a pediatric emergency department.

PubMed

Dexheimer, Judith W; Kennebeck, Stephanie

2013-07-01

Electronic health records (EHRs) are used for data storage; provider, laboratory, and patient communication; clinical decision support; procedure and medication orders; and decision support alerts. Clinical decision support is part of any EHR and is designed to help providers make better decisions. The emergency department (ED) poses a unique environment to the use of EHRs and clinical decision support. Used effectively, computerized tracking boards can help improve flow, communication, and the dissemination of pertinent visit information between providers and other departments in a busy ED. We discuss the unique modifications and decisions made in the implementation of an EHR and computerized tracking board in a pediatric ED. We discuss the changing views based on provider roles, customization to the user interface including the layout and colors, decision support, tracking board best practices collected from other institutions and colleagues, and a case study of using reminders on the electronic tracking board to drive pain reassessments.

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.

The role of electronic health records in clinical reasoning.

PubMed

Berndt, Markus; Fischer, Martin R

2018-05-16

Electronic health records (eHRs) play an increasingly important role in documentation and exchange of information in multi-and interdisciplinary patient care. Although eHRs are associated with mixed evidence in terms of effectiveness, they are undeniably the health record form of the future. This poses several learning opportunities and challenges for medical education. This review aims to connect the concept of eHRs to key competencies of physicians and elaborates current learning science perspectives on diagnostic and clinical reasoning based on a theoretical framework of scientific reasoning and argumentation. It concludes with an integrative vision of the use of eHRs, and the special role of the patient, for teaching and learning in medicine. © 2018 New York Academy of Sciences.

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

Development of the American College of Rheumatology’s Rheumatoid Arthritis Electronic Clinical Quality Measures

PubMed Central

Yazdany, Jinoos; Robbins, Mark; Schmajuk, Gabriela; Desai, Sonali; Lacaille, Diane; Neogi, Tuhina; Singh, Jasvinder A.; Genovese, Mark; Myslinski, Rachel; Fisk, Natalie; Francisco, Melissa; Newman, Eric

2017-01-01

Background Electronic clinical quality measures (eCQMs) rely on computer algorithms to extract data from electronic health records (EHRs). On behalf of the American College of Rheumatology (ACR), we sought to develop and test eCQMs for rheumatoid arthritis (RA). Methods Drawing from published ACR guidelines, a working group developed candidate RA process measures and subsequently assessed face validity through an interdisciplinary panel of health care stakeholders. A public comment period followed. Measures that passed these levels of review were electronically specified using the Quality Data Model, which provides standard nomenclature for data elements (category, datatype, value sets) obtained through an EHR. For each eCQM, 3 clinical sites using different EHR systems tested the scientific feasibility and validity of measures. Measures appropriate for accountability were presented for national endorsement. Results Expert panel validity ratings were high for all measures (median 8–9 out of 9). Health system performance on the eCQMs was 53.6% for RA disease activity assessment, 69.1% for functional status assessment, 93.1% for disease modifying drug (DMARD) use and 72.8% for tuberculosis screening. Kappa statistics, evaluating whether the eCQM validly captured data obtained from manual EHR chart review, demonstrated moderate to substantial agreement (0.54 for functional status assessment, 0.73 for tuberculosis screening, 0.84 for disease activity, and 0.85 for DMARD use). Conclusion Four eCQMs for RA have achieved national endorsement and are recommended for use in federal quality reporting programs. Implementation and further refinement of these measures is ongoing in the ACR’s registry, the Rheumatology Informatics System for Effectiveness (RISE). PMID:27564778

Sexual Orientation and Gender Identity Data Collection in Clinical Settings and in Electronic Health Records: A Key to Ending LGBT Health Disparities.

PubMed

Cahill, Sean; Makadon, Harvey

2014-03-01

The Institute of Medicine's (IOM's) 2011 report on the health of LGBT people pointed out that there are limited health data on these populations and that we need more research. It also described what we do know about LGBT health disparities, including lower rates of cervical cancer screening among lesbians, and mental health issues related to minority stress. Patient disclosure of LGBT identity enables provider-patient conversations about risk factors and can help us reduce and better understand disparities. It is essential to the success of Healthy People 2020's goal of eliminating LGBT health disparities. This is why the IOM's report recommended data collection in clinical settings and on electronic health records (EHRs). The Center for Medicare and Medicaid Services and the Office of the National Coordinator of Health Information Technology rejected including sexual orientation and gender identity (SOGI) questions in meaningful use guidelines for EHRs in 2012 but are considering this issue again in 2013. There is overwhelming community support for the routine collection of SOGI data in clinical settings, as evidenced by comments jointly submitted by 145 leading LGBT and HIV/AIDS organizations in January 2013. Gathering SOGI data in EHRs is supported by the 2011 IOM's report on LGBT health, Healthy People 2020, the Affordable Care Act, and the Joint Commission. Data collection has long been central to the quality assurance process. Preventive health care from providers knowledgeable of their patients' SOGI can lead to improved access, quality of care, and outcomes. Medical and nursing schools should expand their attention to LGBT health issues so that all clinicians can appropriately care for LGBT patients.

Evaluating the usability of speech recognition to create clinical documentation using a commercial electronic health record.

PubMed

Hodgson, Tobias; Magrabi, Farah; Coiera, Enrico

2018-05-01

To conduct a usability study exploring the value of using speech recognition (SR) for clinical documentation tasks within an electronic health record (EHR) system. Thirty-five emergency department clinicians completed a system usability scale (SUS) questionnaire. The study was undertaken after participants undertook randomly allocated clinical documentation tasks using keyboard and mouse (KBM) or SR. SUS scores were analyzed and the results with KBM were compared to SR results. Significant difference in SUS scores between EHR system use with and without SR were observed (KBM 67, SR 61; P = 0.045; CI, 0.1 to 12.0). Nineteen of 35 participants scored higher for EHR with KBM, 11 higher for EHR with SR and 5 gave the same score for both. Factor analysis showed no significant difference in scores for the sub-element of usability (EHR with KBM 65, EHR with SR 62; P = 0.255; CI, -2.6 to 9.5). Scores for the sub-element of learnability were significantly different (KBM 72, SR 55; P < 0.001; CI, 9.8 to 23.5). A significant correlation was found between the perceived usability of the two system configurations (EHR with KBM or SR) and the efficiency of documentation (time to document) (P = 0.002; CI, 10.5 to -0.1) but not with safety (number of errors) (P = 0.90; CI, -2.3 to 2.6). SR was associated with significantly reduced overall usability scores, even though it is often positioned as ease of use technology. SR was perceived to impose larger costs in terms of learnability via training and support requirements for EHR based documentation when compared to using KBM. Lower usability scores were significantly associated with longer documentation times. The usability of EHR systems with any input modality is an area that requires continued development. The addition of an SR component to an EHR system may cause a significant reduction in terms of perceived usability by clinicians. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Understanding Study Participants Views on Co-Creation of Data and Use of EHR in Clinical Studies.

PubMed

Scott Duncan, Therese; Hägglund, Maria

2018-01-01

In order to increase clinical trial participation, the reasons for participating need to be observed. Since there is rather inadequate information concerning how individuals such as patients, decides to participate in clinical trials semi-structured interviews have been done. Examining the use of EHR in clinical trials and co-creation of data, the result showed that it is important for the researches to have access to the patients' EHR and for the patients to contribute with their own ideas of research. Important aspects of further participation in clinical trials were that it should be fun and informative. The patients agreed on that the effort of participating could decrease with the use of electronically collection and self-reporting of data, e.g. through a patient portal.

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.

Hospital Readmission and Social Risk Factors Identified from Physician Notes.

PubMed

Navathe, Amol S; Zhong, Feiran; Lei, Victor J; Chang, Frank Y; Sordo, Margarita; Topaz, Maxim; Navathe, Shamkant B; Rocha, Roberto A; Zhou, Li

2018-04-01

To evaluate the prevalence of seven social factors using physician notes as compared to claims and structured electronic health records (EHRs) data and the resulting association with 30-day readmissions. A multihospital academic health system in southeastern Massachusetts. An observational study of 49,319 patients with cardiovascular disease admitted from January 1, 2011, to December 31, 2013, using multivariable logistic regression to adjust for patient characteristics. All-payer claims, EHR data, and physician notes extracted from a centralized clinical registry. All seven social characteristics were identified at the highest rates in physician notes. For example, we identified 14,872 patient admissions with poor social support in physician notes, increasing the prevalence from 0.4 percent using ICD-9 codes and structured EHR data to 16.0 percent. Compared to an 18.6 percent baseline readmission rate, risk-adjusted analysis showed higher readmission risk for patients with housing instability (readmission rate 24.5 percent; p < .001), depression (20.6 percent; p < .001), drug abuse (20.2 percent; p = .01), and poor social support (20.0 percent; p = .01). The seven social risk factors studied are substantially more prevalent than represented in administrative data. Automated methods for analyzing physician notes may enable better identification of patients with social needs. © Health Research and Educational Trust.

Security analysis of standards-driven communication protocols for healthcare scenarios.

PubMed

Masi, Massimiliano; Pugliese, Rosario; Tiezzi, Francesco

2012-12-01

The importance of the Electronic Health Record (EHR), that stores all healthcare-related data belonging to a patient, has been recognised in recent years by governments, institutions and industry. Initiatives like the Integrating the Healthcare Enterprise (IHE) have been developed for the definition of standard methodologies for secure and interoperable EHR exchanges among clinics and hospitals. Using the requisites specified by these initiatives, many large scale projects have been set up for enabling healthcare professionals to handle patients' EHRs. The success of applications developed in these contexts crucially depends on ensuring such security properties as confidentiality, authentication, and authorization. In this paper, we first propose a communication protocol, based on the IHE specifications, for authenticating healthcare professionals and assuring patients' safety. By means of a formal analysis carried out by using the specification language COWS and the model checker CMC, we reveal a security flaw in the protocol thus demonstrating that to simply adopt the international standards does not guarantee the absence of such type of flaws. We then propose how to emend the IHE specifications and modify the protocol accordingly. Finally, we show how to tailor our protocol for application to more critical scenarios with no assumptions on the communication channels. To demonstrate feasibility and effectiveness of our protocols we have fully implemented them.

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.

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.

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

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.

Usability Evaluation of Electronic Health Record System around Clinical Notes Usage-An Ethnographic Study.

PubMed

Rizvi, Rubina F; Marquard, Jenna L; Hultman, Gretchen M; Adam, Terrence J; Harder, Kathleen A; Melton, Genevieve B

2017-10-01

Background A substantial gap exists between current Electronic Health Record (EHR) usability and potential optimal usability. One of the fundamental reasons for this discrepancy is poor incorporation of a User-Centered Design (UCD) approach during the Graphical User Interface (GUI) development process. Objective To evaluate usability strengths and weaknesses of two widely implemented EHR GUIs for critical clinical notes usage tasks. Methods Twelve Internal Medicine resident physicians interacting with one of the two EHR systems (System-1 at Location-A and System-2 at Location-B) were observed by two usability evaluators employing an ethnographic approach. User comments and observer findings were analyzed for two critical tasks: (1) clinical notes entry and (2) related information-seeking tasks. Data were analyzed from two standpoints: (1) usability references categorized by usability evaluators as positive, negative, or equivocal and (2) usability impact of each feature measured through a 7-point severity rating scale. Findings were also validated by user responses to a post observation questionnaire. Results For clinical notes entry, System-1 surpassed System-2 with more positive (26% vs. 12%) than negative (12% vs. 34%) usability references. Greatest impact features on EHR usability (severity score pertaining to each feature) for clinical notes entry were: autopopulation (6), screen options (5.5), communication (5), copy pasting (4.5), error prevention (4.5), edit ability (4), and dictation and transcription (3.5). Both systems performed equally well on information-seeking tasks and features with greatest impacts on EHR usability were navigation for notes (7) and others (e.g., looking for ancillary data; 5.5). Ethnographic observations were supported by follow-up questionnaire responses. Conclusion This study provides usability-specific insights to inform future, improved, EHR interface that is better aligned with UCD approach.

A service oriented approach for guidelines-based clinical decision support using BPMN.

PubMed

Rodriguez-Loya, Salvador; Aziz, Ayesha; Chatwin, Chris

2014-01-01

Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS).

Semantic processing of EHR data for clinical research.

PubMed

Sun, Hong; Depraetere, Kristof; De Roo, Jos; Mels, Giovanni; De Vloed, Boris; Twagirumukiza, Marc; Colaert, Dirk

2015-12-01

There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data. Copyright © 2015 Elsevier Inc. All rights reserved.

Clinical Data Systems to Support Public Health Practice: A National Survey of Software and Storage Systems Among Local Health Departments.

PubMed

McCullough, J Mac; Goodin, Kate

2016-01-01

Numerous software and data storage systems are employed by local health departments (LHDs) to manage clinical and nonclinical data needs. Leveraging electronic systems may yield improvements in public health practice. However, information is lacking regarding current usage patterns among LHDs. To analyze clinical and nonclinical data storage and software types by LHDs. Data came from the 2015 Informatics Capacity and Needs Assessment Survey, conducted by Georgia Southern University in collaboration with the National Association of County and City Health Officials. A total of 324 LHDs from all 50 states completed the survey (response rate: 50%). Outcome measures included LHD's primary clinical service data system, nonclinical data system(s) used, and plans to adopt electronic clinical data system (if not already in use). Predictors of interest included jurisdiction size and governance type, and other informatics capacities within the LHD. Bivariate analyses were performed using χ and t tests. Up to 38.4% of LHDs reported using an electronic health record (EHR). Usage was common especially among LHDs that provide primary care and/or dental services. LHDs serving smaller populations and those with state-level governance were both less likely to use an EHR. Paper records were a common data storage approach for both clinical data (28.9%) and nonclinical data (59.4%). Among LHDs without an EHR, 84.7% reported implementation plans. Our findings suggest that LHDs are increasingly using EHRs as a clinical data storage solution and that more LHDs are likely to adopt EHRs in the foreseeable future. Yet use of paper records remains common. Correlates of electronic system usage emerged across a range of factors. Program- or system-specific needs may be barriers or facilitators to EHR adoption. Policy makers can tailor resources to address barriers specific to LHD size, governance, service portfolio, existing informatics capabilities, and other pertinent characteristics.

A new role for primary care teams in the United States after “Obamacare:” Track and improve health insurance coverage rates

PubMed Central

DeVoe, Jennifer; Angier, Heather; Hoopes, Megan; Gold, Rachel

2017-01-01

Maintaining continuous health insurance coverage is important. With recent expansions in access to coverage in the United States after “Obamacare,” primary care teams have a new role in helping to track and improve coverage rates and to provide outreach to patients. We describe efforts to longitudinally track health insurance rates using data from the electronic health record (EHR) of a primary care network and to use these data to support practice-based insurance outreach and assistance. Although we highlight a few examples from one network, we believe there is great potential for doing this type of work in a broad range of family medicine and community health clinics that provide continuity of care. By partnering with researchers through practice-based research networks and other similar collaboratives, primary care practices can greatly expand the use of EHR data and EHR-based tools targeting improvements in health insurance and quality health care. PMID:28966926

An open, component-based information infrastructure for integrated health information networks.

PubMed

Tsiknakis, Manolis; Katehakis, Dimitrios G; Orphanoudakis, Stelios C

2002-12-18

A fundamental requirement for achieving continuity of care is the seamless sharing of multimedia clinical information. Different technological approaches can be adopted for enabling the communication and sharing of health record segments. In the context of the emerging global information society, the creation of and access to the integrated electronic health record (I-EHR) of a citizen has been assigned high priority in many countries. This requirement is complementary to an overall requirement for the creation of a health information infrastructure (HII) to support the provision of a variety of health telematics and e-health services. In developing a regional or national HII, the components or building blocks that make up the overall information system ought to be defined and an appropriate component architecture specified. This paper discusses current international priorities and trends in developing the HII. It presents technological challenges and alternative approaches towards the creation of an I-EHR, being the aggregation of health data created during all interactions of an individual with the healthcare system. It also presents results from an ongoing Research and Development (R&D) effort towards the implementation of the HII in HYGEIAnet, the regional health information network of Crete, Greece, using a component-based software engineering approach. Critical design decisions and related trade-offs, involved in the process of component specification and development, are also discussed and the current state of development of an I-EHR service is presented. Finally, Human Computer Interaction (HCI) and security issues, which are important for the deployment and use of any I-EHR service, are considered.

Identifying clinical features in primary care electronic health record studies: methods for codelist development.

PubMed

Watson, Jessica; Nicholson, Brian D; Hamilton, Willie; Price, Sarah

2017-11-22

Analysis of routinely collected electronic health record (EHR) data from primary care is reliant on the creation of codelists to define clinical features of interest. To improve scientific rigour, transparency and replicability, we describe and demonstrate a standardised reproducible methodology for clinical codelist development. We describe a three-stage process for developing clinical codelists. First, the clear definition a priori of the clinical feature of interest using reliable clinical resources. Second, development of a list of potential codes using statistical software to comprehensively search all available codes. Third, a modified Delphi process to reach consensus between primary care practitioners on the most relevant codes, including the generation of an 'uncertainty' variable to allow sensitivity analysis. These methods are illustrated by developing a codelist for shortness of breath in a primary care EHR sample, including modifiable syntax for commonly used statistical software. The codelist was used to estimate the frequency of shortness of breath in a cohort of 28 216 patients aged over 18 years who received an incident diagnosis of lung cancer between 1 January 2000 and 30 November 2016 in the Clinical Practice Research Datalink (CPRD). Of 78 candidate codes, 29 were excluded as inappropriate. Complete agreement was reached for 44 (90%) of the remaining codes, with partial disagreement over 5 (10%). 13 091 episodes of shortness of breath were identified in the cohort of 28 216 patients. Sensitivity analysis demonstrates that codes with the greatest uncertainty tend to be rarely used in clinical practice. Although initially time consuming, using a rigorous and reproducible method for codelist generation 'future-proofs' findings and an auditable, modifiable syntax for codelist generation enables sharing and replication of EHR studies. Published codelists should be badged by quality and report the methods of codelist generation including: definitions and justifications associated with each codelist; the syntax or search method; the number of candidate codes identified; and the categorisation of codes after Delphi review. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

CER Hub: An informatics platform for conducting comparative effectiveness research using multi-institutional, heterogeneous, electronic clinical data.

PubMed

Hazlehurst, Brian L; Kurtz, Stephen E; Masica, Andrew; Stevens, Victor J; McBurnie, Mary Ann; Puro, Jon E; Vijayadeva, Vinutha; Au, David H; Brannon, Elissa D; Sittig, Dean F

2015-10-01

Comparative effectiveness research (CER) requires the capture and analysis of data from disparate sources, often from a variety of institutions with diverse electronic health record (EHR) implementations. In this paper we describe the CER Hub, a web-based informatics platform for developing and conducting research studies that combine comprehensive electronic clinical data from multiple health care organizations. The CER Hub platform implements a data processing pipeline that employs informatics standards for data representation and web-based tools for developing study-specific data processing applications, providing standardized access to the patient-centric electronic health record (EHR) across organizations. The CER Hub is being used to conduct two CER studies utilizing data from six geographically distributed and demographically diverse health systems. These foundational studies address the effectiveness of medications for controlling asthma and the effectiveness of smoking cessation services delivered in primary care. The CER Hub includes four key capabilities: the ability to process and analyze both free-text and coded clinical data in the EHR; a data processing environment supported by distributed data and study governance processes; a clinical data-interchange format for facilitating standardized extraction of clinical data from EHRs; and a library of shareable clinical data processing applications. CER requires coordinated and scalable methods for extracting, aggregating, and analyzing complex, multi-institutional clinical data. By offering a range of informatics tools integrated into a framework for conducting studies using EHR data, the CER Hub provides a solution to the challenges of multi-institutional research using electronic medical record data. Copyright © 2015. Published by Elsevier Ireland Ltd.

Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise.

PubMed

Militello, Laura G; Saleem, Jason J; Borders, Morgan R; Sushereba, Christen E; Haverkamp, Donald; Wolf, Steven P; Doebbeling, Bradley N

2016-03-01

Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration's EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability.

Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise

PubMed Central

Militello, Laura G.; Saleem, Jason J.; Borders, Morgan R.; Sushereba, Christen E.; Haverkamp, Donald; Wolf, Steven P.; Doebbeling, Bradley N.

2016-01-01

Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration’s EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability. PMID:26973441

Understanding Providers' Interaction with Graphical User Interface Pertaining to Clinical Document Usage in an Electronic Health Record System

ERIC Educational Resources Information Center

Rizvi, Rubina Fatima

2017-01-01

Despite high Electronic Health Record (EHR) system adoption rates by hospital and office-based practices, many users remain highly dissatisfied with the current state of EHRs. Sub-optimal EHR usability as a result of insufficient incorporation of User-Centered Design (UCD) approach during System Development Life Cycle process (SDLC) is considered…

Provider interaction with the electronic health record: the effects on patient-centered communication in medical encounters.

PubMed

Street, Richard L; Liu, Lin; Farber, Neil J; Chen, Yunan; Calvitti, Alan; Zuest, Danielle; Gabuzda, Mark T; Bell, Kristin; Gray, Barbara; Rick, Steven; Ashfaq, Shazia; Agha, Zia

2014-09-01

The computer with the electronic health record (EHR) is an additional 'interactant' in the medical consultation, as clinicians must simultaneously or in alternation engage patient and computer to provide medical care. Few studies have examined how clinicians' EHR workflow (e.g., gaze, keyboard activity, and silence) influences the quality of their communication, the patient's involvement in the encounter, and conversational control of the visit. Twenty-three primary care providers (PCPs) from USA Veterans Administration (VA) primary care clinics participated in the study. Up to 6 patients per PCP were recruited. The proportion of time PCPs spent gazing at the computer was captured in real time via video-recording. Mouse click/scrolling activity was captured through Morae, a usability software that logs mouse clicks and scrolling activity. Conversational silence was coded as the proportion of time in the visit when PCP and patient were not talking. After the visit, patients completed patient satisfaction measures. Trained coders independently viewed videos of the interactions and rated the degree to which PCPs were patient-centered (informative, supportive, partnering) and patients were involved in the consultation. Conversational control was measured as the proportion of time the PCP held the floor compared to the patient. The final sample included 125 consultations. PCPs who spent more time in the consultation gazing at the computer and whose visits had more conversational silence were rated lower in patient-centeredness. PCPs controlled more of the talk time in the visits that also had longer periods of mutual silence. PCPs were rated as having less effective communication when they spent more time looking at the computer and when there was more periods of silence in the consultation. Because PCPs increasingly are using the EHR in their consultations, more research is needed to determine effective ways that they can verbally engage patients while simultaneously managing data in the EHR. EHR activity consumes an increasing proportion of clinicians' time during consultations. To ensure effective communication with their patients, clinicians may benefit from using communication strategies that maintain the flow of conversation when working with the computer, as well as from learning EHR management skills that prevent extended periods of gaze at computer and long periods of silence. Next-generation EHR design must address better usability and clinical workflow integration, including facilitating patient-clinician communication. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Provider interaction with the electronic health record: The effects on patient-centered communication in medical encounters

PubMed Central

Street, Richard L.; Liu, Lin; Farber, Neil J.; Chen, Yunan; Calvitti, Alan; Zuest, Danielle; Gabuzda, Mark T.; Bell, Kristin; Gray, Barbara; Rick, Steven; Ashfaq, Shazia; Agha, Zia

2015-01-01

Objective The computer with the electronic health record (EHR) is an additional ‘interactant’ in the medical consultation, as clinicians must simultaneously or in alternation engage patient and computer to provide medical care. Few studies have examined how clinicians' EHR workflow (e.g., gaze, keyboard activity, and silence) influences the quality of their communication, the patient's involvement in the encounter, and conversational control of the visit. Methods Twenty-three primary care providers (PCPs) from USA Veterans Administration (VA) primary care clinics participated in the study. Up to 6 patients per PCP were recruited. The proportion of time PCPs spent gazing at the computer was captured in real time via video-recording. Mouse click/scrolling activity was captured through Morae, a usability software that logs mouse clicks and scrolling activity. Conversational silence was coded as the proportion of time in the visit when PCP and patient were not talking. After the visit, patients completed patient satisfaction measures. Trained coders independently viewed videos of the interactions and rated the degree to which PCPs were patient-centered (informative, supportive, partnering) and patients were involved in the consultation. Conversational control was measured as the proportion of time the PCP held the floor compared to the patient. Results The final sample included 125 consultations. PCPs who spent more time in the consultation gazing at the computer and whose visits had more conversational silence were rated lower inpatient-centeredness. PCPs controlled more of the talk time in the visits that also had longer periods of mutual silence. Conclusions PCPs were rated as having less effective communication when they spent more time looking at the computer and when there was more periods of silence in the consultation. Because PCPs increasingly are using the EHR in their consultations, more research is needed to determine effective ways that they can verbally engage patients while simultaneously managing data in the EHR. Practice implications EHR activity consumes an increasing proportion of clinicians' time during consultations. To ensure effective communication with their patients, clinicians may benefit from using communication strategies that maintain the flow of conversation when working with the computer, as well as from learning EHR management skills that prevent extended periods of gaze at computer and long periods of silence. Next-generation EHR design must address better usability and clinical workflow integration, including facilitating patient-clinician communication. PMID:24882086

A tutorial on activity-based costing of electronic health records.

PubMed

Federowicz, Marie H; Grossman, Mila N; Hayes, Bryant J; Riggs, Joseph

2010-01-01

As the American Recovery and Restoration Act of 2009 allocates $19 billion to health information technology, it will be useful for health care managers to project the true cost of implementing an electronic health record (EHR). This study presents a step-by-step guide for using activity-based costing (ABC) to estimate the cost of an EHR. ABC is a cost accounting method with a "top-down" approach for estimating the cost of a project or service within an organization. The total cost to implement an EHR includes obvious costs, such as licensing fees, and hidden costs, such as impact on productivity. Unlike other methods, ABC includes all of the organization's expenditures and is less likely to miss hidden costs. Although ABC is used considerably in manufacturing and other industries, it is a relatively new phenomenon in health care. ABC is a comprehensive approach that the health care field can use to analyze the cost-effectiveness of implementing EHRs. In this article, ABC is applied to a health clinic that recently implemented an EHR, and the clinic is found to be more productive after EHR implementation. This methodology can help health care administrators assess the impact of a stimulus investment on organizational performance.

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

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.

Better informed in clinical practice - a brief overview of dental informatics.

PubMed

Reynolds, P A; Harper, J; Dunne, S

2008-03-22

Uptake of dental informatics has been hampered by technical and user issues. Innovative systems have been developed, but usability issues have affected many. Advances in technology and artificial intelligence are now producing clinically useful systems, although issues still remain with adapting computer interfaces to the dental practice working environment. A dental electronic health record has become a priority in many countries, including the UK. However, experience shows that any dental electronic health record (EHR) system cannot be subordinate to, or a subset of, a medical record. Such a future dental EHR is likely to incorporate integrated care pathways. Future best dental practice will increasingly depend on computer-based support tools, although disagreement remains about the effectiveness of current support tools. Over the longer term, future dental informatics tools will incorporate dynamic, online evidence-based medicine (EBM) tools, and promise more adaptive, patient-focused and efficient dental care with educational advantages in training.

Improving Interoperability between Registries and EHRs

PubMed Central

Blumenthal, Seth

2018-01-01

National performance measurement needs clinical data that track the performance of multi disciplinary teams across episodes of care. Clinical registries are ideal platforms for this work due to their capture of structured, specific data across specialties. Because registries collect data at a national level, and registry data are captured in a consistent structure and format within each registry, registry data are useful for measurement and analysis “out of the box”. Registry business models are hampered by the cost of collecting data from EHRs and other source systems and abstracting or mapping them to fit registry data models. The National Quality Registry Network (NQRN) has launched Registries on FHIR, an initiative to lower barriers to achieving semantic interoperability between registries and source data systems. In 2017 Registries on FHIR conducted an information gathering campaign to learn where registries want better interoperability, and how to go about improving it. PMID:29888033

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.

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.

Know me - a journey in creating a personal electronic health record.

PubMed

Buckley, Amanda; Fox, Suzanne

2015-01-01

KnowMe is a patient created personal story of key life events both medical and non-medical that enables clinicians to understand what matters to the patient, not what's the matter with them. By shifting the Electronic Health Record (EHR) focus to knowing when a patient was at their best, what's important to them, their personal health goals, and care preferences, clinicians and patients can collaboratively work together in creating a treatment plan that aligns resources tailored to the their needs.

Development of an open metadata schema for prospective clinical research (openPCR) in China.

PubMed

Xu, W; Guan, Z; Sun, J; Wang, Z; Geng, Y

2014-01-01

In China, deployment of electronic data capture (EDC) and clinical data management system (CDMS) for clinical research (CR) is in its very early stage, and about 90% of clinical studies collected and submitted clinical data manually. This work aims to build an open metadata schema for Prospective Clinical Research (openPCR) in China based on openEHR archetypes, in order to help Chinese researchers easily create specific data entry templates for registration, study design and clinical data collection. Singapore Framework for Dublin Core Application Profiles (DCAP) is used to develop openPCR and four steps such as defining the core functional requirements and deducing the core metadata items, developing archetype models, defining metadata terms and creating archetype records, and finally developing implementation syntax are followed. The core functional requirements are divided into three categories: requirements for research registration, requirements for trial design, and requirements for case report form (CRF). 74 metadata items are identified and their Chinese authority names are created. The minimum metadata set of openPCR includes 3 documents, 6 sections, 26 top level data groups, 32 lower data groups and 74 data elements. The top level container in openPCR is composed of public document, internal document and clinical document archetypes. A hierarchical structure of openPCR is established according to Data Structure of Electronic Health Record Architecture and Data Standard of China (Chinese EHR Standard). Metadata attributes are grouped into six parts: identification, definition, representation, relation, usage guides, and administration. OpenPCR is an open metadata schema based on research registration standards, standards of the Clinical Data Interchange Standards Consortium (CDISC) and Chinese healthcare related standards, and is to be publicly available throughout China. It considers future integration of EHR and CR by adopting data structure and data terms in Chinese EHR Standard. Archetypes in openPCR are modularity models and can be separated, recombined, and reused. The authors recommend that the method to develop openPCR can be referenced by other countries when designing metadata schema of clinical research. In the next steps, openPCR should be used in a number of CR projects to test its applicability and to continuously improve its coverage. Besides, metadata schema for research protocol can be developed to structurize and standardize protocol, and syntactical interoperability of openPCR with other related standards can be considered.

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

Clinical research informatics and electronic health record data.

PubMed

Richesson, R L; Horvath, M M; Rusincovitch, S A

2014-08-15

The goal of this survey is to discuss the impact of the growing availability of electronic health record (EHR) data on the evolving field of Clinical Research Informatics (CRI), which is the union of biomedical research and informatics. Major challenges for the use of EHR-derived data for research include the lack of standard methods for ensuring that data quality, completeness, and provenance are sufficient to assess the appropriateness of its use for research. Areas that need continued emphasis include methods for integrating data from heterogeneous sources, guidelines (including explicit phenotype definitions) for using these data in both pragmatic clinical trials and observational investigations, strong data governance to better understand and control quality of enterprise data, and promotion of national standards for representing and using clinical data. The use of EHR data has become a priority in CRI. Awareness of underlying clinical data collection processes will be essential in order to leverage these data for clinical research and patient care, and will require multi-disciplinary teams representing clinical research, informatics, and healthcare operations. Considerations for the use of EHR data provide a starting point for practical applications and a CRI research agenda, which will be facilitated by CRI's key role in the infrastructure of a learning healthcare system.

Clinical Research Informatics and Electronic Health Record Data

PubMed Central

Horvath, M. M.; Rusincovitch, S. A.

2014-01-01

Summary Objectives The goal of this survey is to discuss the impact of the growing availability of electronic health record (EHR) data on the evolving field of Clinical Research Informatics (CRI), which is the union of biomedical research and informatics. Results Major challenges for the use of EHR-derived data for research include the lack of standard methods for ensuring that data quality, completeness, and provenance are sufficient to assess the appropriateness of its use for research. Areas that need continued emphasis include methods for integrating data from heterogeneous sources, guidelines (including explicit phenotype definitions) for using these data in both pragmatic clinical trials and observational investigations, strong data governance to better understand and control quality of enterprise data, and promotion of national standards for representing and using clinical data. Conclusions The use of EHR data has become a priority in CRI. Awareness of underlying clinical data collection processes will be essential in order to leverage these data for clinical research and patient care, and will require multi-disciplinary teams representing clinical research, informatics, and healthcare operations. Considerations for the use of EHR data provide a starting point for practical applications and a CRI research agenda, which will be facilitated by CRI’s key role in the infrastructure of a learning healthcare system. PMID:25123746

Common data elements for secondary use of electronic health record data for clinical trial execution and serious adverse event reporting.

PubMed

Bruland, Philipp; McGilchrist, Mark; Zapletal, Eric; Acosta, Dionisio; Proeve, Johann; Askin, Scott; Ganslandt, Thomas; Doods, Justin; Dugas, Martin

2016-11-22

Data capture is one of the most expensive phases during the conduct of a clinical trial and the increasing use of electronic health records (EHR) offers significant savings to clinical research. To facilitate these secondary uses of routinely collected patient data, it is beneficial to know what data elements are captured in clinical trials. Therefore our aim here is to determine the most commonly used data elements in clinical trials and their availability in hospital EHR systems. Case report forms for 23 clinical trials in differing disease areas were analyzed. Through an iterative and consensus-based process of medical informatics professionals from academia and trial experts from the European pharmaceutical industry, data elements were compiled for all disease areas and with special focus on the reporting of adverse events. Afterwards, data elements were identified and statistics acquired from hospital sites providing data to the EHR4CR project. The analysis identified 133 unique data elements. Fifty elements were congruent with a published data inventory for patient recruitment and 83 new elements were identified for clinical trial execution, including adverse event reporting. Demographic and laboratory elements lead the list of available elements in hospitals EHR systems. For the reporting of serious adverse events only very few elements could be identified in the patient records. Common data elements in clinical trials have been identified and their availability in hospital systems elucidated. Several elements, often those related to reimbursement, are frequently available whereas more specialized elements are ranked at the bottom of the data inventory list. Hospitals that want to obtain the benefits of reusing data for research from their EHR are now able to prioritize their efforts based on this common data element list.

Barriers to Electronic Health Record Adoption: a Systematic Literature Review.

PubMed

Kruse, Clemens Scott; Kristof, Caitlin; Jones, Beau; Mitchell, Erica; Martinez, Angelica

2016-12-01

Federal efforts and local initiatives to increase adoption and use of electronic health records (EHRs) continue, particularly since the enactment of the Health Information Technology for Economic and Clinical Health (HITECH) Act. Roughly one in four hospitals not adopted even a basic EHR system. A review of the barriers may help in understanding the factors deterring certain healthcare organizations from implementation. We wanted to assemble an updated and comprehensive list of adoption barriers of EHR systems in the United States. Authors searched CINAHL, MEDLINE, and Google Scholar, and accepted only articles relevant to our primary objective. Reviewers independently assessed the works highlighted by our search and selected several for review. Through multiple consensus meetings, authors tapered articles to a final selection most germane to the topic (n = 27). Each article was thoroughly examined by multiple authors in order to achieve greater validity. Authors identified 39 barriers to EHR adoption within the literature selected for the review. These barriers appeared 125 times in the literature; the most frequently mentioned barriers were regarding cost, technical concerns, technical support, and resistance to change. Despite federal and local incentives, the initial cost of adopting an EHR is a common existing barrier. The other most commonly mentioned barriers include technical support, technical concerns, and maintenance/ongoing costs. Policy makers should consider incentives that continue to reduce implementation cost, possibly aimed more directly at organizations that are known to have lower adoption rates, such as small hospitals in rural areas.

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.

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

Developing an acute-physical-examination template for a Tegional EHR system aimed at improving inexperienced physician's documentation.

PubMed

Lilholt, Lars; Haubro, Camilla Dremstrup; Møller, Jørn Munkhof; Aarøe, Jens; Højen, Anne Randorff; Gøeg, Kirstine Rosenbeck

2013-01-01

It is well-established that to increase acceptance of electronic clinical documentation tools, such as electronic health record (EHR) systems, it is important to have a strong relationship between those who document the clinical encounters and those who reaps the benefit of digitalized and more structured documentation. [1] Therefore, templates for EHR systems benefit from being closely related to clinical practice with a strong focus on primarily solving clinical problems. Clinical use as a driver for structured documentation has been the focus of the acute-physical-examination template (APET) development in the North Denmark Region. The template was developed through a participatory design where precision and clarity of documentation was prioritized as well as fast registration. The resulting template has approximately 700 easy accessible input possibilities and will be evaluated in clinical practice in the first quarter of 2013.

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.

Confidentiality, electronic health records, and the clinician.

PubMed

Graves, Stuart

2013-01-01

The advent of electronic health records (EHRs) to improve access and enable research in the everyday clinical world has simultaneously made medical information much more vulnerable to illicit, non-beneficent uses. This wealth of identified, aggregated data has and will attract attacks by domestic governments for surveillance and protection, foreign governments for espionage and sabotage, organized crime for illegal profits, and large corporations for "legal" profits. Against these powers with almost unlimited resources no security scheme is likely to prevail, so the design of such systems should include appropriate security measures. Unlike paper records, where the person maintaining and controlling the existence of the records also controls access to them, these two functions can be separated for EHRs. By giving physical control over access to individual records to their individual owners, the aggregate is dismantled, thereby protecting the nation's identified health information from large-scale data mining or tampering. Control over the existence and integrity of all the records--yet without the ability to examine their contents--would be left with larger institutions. This article discusses the implications of all of the above for the role of the clinician in assuring confidentiality (a cornerstone of clinical practice), for research and everyday practice, and for current security designs.

Does integrating nonurgent, clinically significant radiology alerts within the electronic health record impact closed-loop communication and follow-up?

PubMed

O'Connor, Stacy D; Dalal, Anuj K; Sahni, V Anik; Lacson, Ronilda; Khorasani, Ramin

2016-03-01

To assess whether integrating critical result management software--Alert Notification of Critical Results (ANCR)--with an electronic health record (EHR)-based results management application impacts closed-loop communication and follow-up of nonurgent, clinically significant radiology results by primary care providers (PCPs). This institutional review board-approved study was conducted at a large academic medical center. Postintervention, PCPs could acknowledge nonurgent, clinically significant ANCR-generated alerts ("alerts") within ANCR or the EHR. Primary outcome was the proportion of alerts acknowledged via EHR over a 24-month postintervention. Chart abstractions for a random sample of alerts 12 months preintervention and 24 months postintervention were reviewed, and the follow-up rate of actionable alerts (eg, performing follow-up imaging, administering antibiotics) was estimated. Pre- and postintervention rates were compared using the Fisher exact test. Postintervention follow-up rate was compared for EHR-acknowledged alerts vs ANCR. Five thousand nine hundred and thirty-one alerts were acknowledged by 171 PCPs, with 100% acknowledgement (consistent with expected ANCR functionality). PCPs acknowledged 16% (688 of 4428) of postintervention alerts in the EHR, with the remaining in ANCR. Follow-up was documented for 85 of 90 (94%; 95% CI, 88%-98%) preintervention and 79 of 84 (94%; 95% CI, 87%-97%) postintervention alerts (P > .99). Postintervention, 11 of 14 (79%; 95% CI, 52%-92%) alerts were acknowledged via EHR and 68 of 70 (97%; 95% CI, 90%-99%) in ANCR had follow-up (P = .03). Integrating ANCR and EHR provides an additional workflow for acknowledging nonurgent, clinically significant results without significant change in rates of closed-loop communication or follow-up of alerts. © 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.

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.

Cross-vendor evaluation of key user-defined clinical decision support capabilities: a scenario-based assessment of certified electronic health records with guidelines for future development.

PubMed

McCoy, Allison B; Wright, Adam; Sittig, Dean F

2015-09-01

Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems. We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin. Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules. Significant improvements in the EHR certification and implementation procedures are necessary. © 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.

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

Depression screening optimization in an academic rural setting.

PubMed

Aleem, Sohaib; Torrey, William C; Duncan, Mathew S; Hort, Shoshana J; Mecchella, John N

2015-01-01

Primary care plays a critical role in screening and management of depression. The purpose of this paper is to focus on leveraging the electronic health record (EHR) as well as work flow redesign to improve the efficiency and reliability of the process of depression screening in two adult primary care clinics of a rural academic institution in USA. The authors utilized various process improvement tools from lean six sigma methodology including project charter, swim lane process maps, critical to quality tree, process control charts, fishbone diagrams, frequency impact matrix, mistake proofing and monitoring plan in Define-Measure-Analyze-Improve-Control format. Interventions included change in depression screening tool, optimization of data entry in EHR. EHR data entry optimization; follow up of positive screen, staff training and EHR redesign. Depression screening rate for office-based primary care visits improved from 17.0 percent at baseline to 75.9 percent in the post-intervention control phase (p<0.001). Follow up of positive depression screen with Patient History Questionnaire-9 data collection remained above 90 percent. Duplication of depression screening increased from 0.6 percent initially to 11.7 percent and then decreased to 4.7 percent after optimization of data entry by patients and flow staff. Impact of interventions on clinical outcomes could not be evaluated. Successful implementation, sustainability and revision of a process improvement initiative to facilitate screening, follow up and management of depression in primary care requires accounting for voice of the process (performance metrics), system limitations and voice of the customer (staff and patients) to overcome various system, customer and human resource constraints.

Working at the intersection of context, culture, and technology: Provider perspectives on antimicrobial stewardship in the emergency department using electronic health record clinical decision support.

PubMed

Chung, Phillip; Scandlyn, Jean; Dayan, Peter S; Mistry, Rakesh D

2017-11-01

Antibiotic stewardship programs (ASPs) have not been fully developed for the emergency department (ED), in part the result of the barriers characteristic of this setting. Electronic health record-based clinical decision support (EHR CDS) represents a promising strategy to implement ASPs in the ED. We aimed to determine the cultural beliefs and structural barriers and facilitators to implementation of antimicrobial stewardship in the pediatric ED using EHR CDS. Interviews and focus groups were conducted with hospital and ED leadership, attending ED physicians, nurse practitioners, physician assistants, and residents at a single health system in Colorado. We reviewed and coded the data using constant comparative analysis and framework analysis until a final set of themes emerged. Two dominant perceptions shaped providers' perspectives on ASPs in the ED and EHR CDS: (1) maintaining workflow efficiency and (2) constrained decision-making autonomy. Clinicians identified structural barriers to ASPs, such as pace of the ED, and various beliefs that shaped patterns of practice, including accommodating the prescribing decisions of other providers and managing parental expectations. Recommendations to enhance uptake focused on designing a simple yet flexible user interface, providing clinicians with performance data, and on-boarding clinicians to enhance buy-in. Developing a successful ED-based ASP using EHR CDS should attend to technologic needs, the institutional context, and the cultural beliefs of practice associated with providers' antibiotic prescribing. Copyright © 2017 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

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

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.

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

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

Characterizing and Managing Missing Structured Data in Electronic Health Records: Data Analysis.

PubMed

Beaulieu-Jones, Brett K; Lavage, Daniel R; Snyder, John W; Moore, Jason H; Pendergrass, Sarah A; Bauer, Christopher R

2018-02-23

Missing data is a challenge for all studies; however, this is especially true for electronic health record (EHR)-based analyses. Failure to appropriately consider missing data can lead to biased results. While there has been extensive theoretical work on imputation, and many sophisticated methods are now available, it remains quite challenging for researchers to implement these methods appropriately. Here, we provide detailed procedures for when and how to conduct imputation of EHR laboratory results. The objective of this study was to demonstrate how the mechanism of missingness can be assessed, evaluate the performance of a variety of imputation methods, and describe some of the most frequent problems that can be encountered. We analyzed clinical laboratory measures from 602,366 patients in the EHR of Geisinger Health System in Pennsylvania, USA. Using these data, we constructed a representative set of complete cases and assessed the performance of 12 different imputation methods for missing data that was simulated based on 4 mechanisms of missingness (missing completely at random, missing not at random, missing at random, and real data modelling). Our results showed that several methods, including variations of Multivariate Imputation by Chained Equations (MICE) and softImpute, consistently imputed missing values with low error; however, only a subset of the MICE methods was suitable for multiple imputation. The analyses we describe provide an outline of considerations for dealing with missing EHR data, steps that researchers can perform to characterize missingness within their own data, and an evaluation of methods that can be applied to impute clinical data. While the performance of methods may vary between datasets, the process we describe can be generalized to the majority of structured data types that exist in EHRs, and all of our methods and code are publicly available. ©Brett K Beaulieu-Jones, Daniel R Lavage, John W Snyder, Jason H Moore, Sarah A Pendergrass, Christopher R Bauer. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 23.02.2018.

Advanced Natural Language Processing and Temporal Mining for Clinical Discovery

ERIC Educational Resources Information Center

Mehrabi, Saeed

2016-01-01

There has been vast and growing amount of healthcare data especially with the rapid adoption of electronic health records (EHRs) as a result of the HITECH act of 2009. It is estimated that around 80% of the clinical information resides in the unstructured narrative of an EHR. Recently, natural language processing (NLP) techniques have offered…

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.

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.

Evaluating the Usability of a Free Electronic Health Record for Training

PubMed Central

Hoyt, Robert; Adler, Kenneth; Ziesemer, Brandy; Palombo, Georgina

2013-01-01

The United States will need to train a large workforce of skilled health information technology (HIT) professionals in order to meet the US government's goal of universal electronic health records (EHRs) for all patients and widespread health information exchange. The Health Information Technology for Economic and Clinical Health (HITECH) Act established several HIT workforce educational programs to accomplish this goal. Recent studies have shown that EHR usability is a significant concern of physicians and is a potential obstacle to EHR adoption. It is important to have a highly usable EHR to train both clinicians and students. In this article, we report a qualitative-quantitative usability analysis of a web-based EHR for training health informatics and health information management students. PMID:23805062

Bridging the gap between the randomised clinical trial world and the real world by combination of population-based registry and electronic health record data: A case study in haemato-oncology.

PubMed

Kibbelaar, R E; Oortgiesen, B E; van der Wal-Oost, A M; Boslooper, K; Coebergh, J W; Veeger, N J G M; Joosten, P; Storm, H; van Roon, E N; Hoogendoorn, M

2017-11-01

Randomised clinical trials (RCTs) are considered the basis of evidence-based medicine. It is recognised more and more that application of RCT results in daily practice of clinical decision-making is limited because the RCT world does not correspond with the clinical real world. Recent strategies aiming at substitution of RCT databases by improved population-based registries (PBRs) or by improved electronic health record (EHR) systems to provide significant data for clinical science are discussed. A novel approach exemplified by the HemoBase haemato-oncology project is presented. In this approach, a PBR is combined with an advanced EHR, providing high-quality data for observational studies and support of best practice development. This PBR + EHR approach opens a perspective on randomised registry trials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visualization of CDA laboratory reports and long term trends as a possible EHR application for patients and physicians.

PubMed

Obenaus, Manuel; Burgsteiner, Harald

2014-01-01

To increase the patient's acceptance of electronic health records and understanding for their laboratory findings a web application was developed which presents all parameters and possible deviations of standard values in a clear way and visualizes the time based trend of all recorded parameters graphically. Documents corresponding to the Clinical document architecture (CDA) R2 laboratory reports standard and a rapid prototyping framework called Groovy on Grails were used. This work shows, that it is possible to create a useful, standards based tool for patients and physicians with comparatively few resources - an application that could be in similar form a part of an electronic Health Record (EHR) system like the Austrian electronic Health Record (ELGA).

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.

Genetic data and electronic health records: a discussion of ethical, logistical and technological considerations

PubMed Central

Shoenbill, Kimberly; Fost, Norman; Tachinardi, Umberto; Mendonca, Eneida A

2014-01-01

Objective The completion of sequencing the human genome in 2003 has spurred the production and collection of genetic data at ever increasing rates. Genetic data obtained for clinical purposes, as is true for all results of clinical tests, are expected to be included in patients’ medical records. With this explosion of information, questions of what, when, where and how to incorporate genetic data into electronic health records (EHRs) have reached a critical point. In order to answer these questions fully, this paper addresses the ethical, logistical and technological issues involved in incorporating these data into EHRs. Materials and methods This paper reviews journal articles, government documents and websites relevant to the ethics, genetics and informatics domains as they pertain to EHRs. Results and discussion The authors explore concerns and tasks facing health information technology (HIT) developers at the intersection of ethics, genetics, and technology as applied to EHR development. Conclusions By ensuring the efficient and effective incorporation of genetic data into EHRs, HIT developers will play a key role in facilitating the delivery of personalized medicine. PMID:23771953

Legal, ethical, and financial dilemmas in electronic health record adoption and use.

PubMed

Sittig, Dean F; Singh, Hardeep

2011-04-01

Electronic health records (EHRs) facilitate several innovations capable of reforming health care. Despite their promise, many currently unanswered legal, ethical, and financial questions threaten the widespread adoption and use of EHRs. Key legal dilemmas that must be addressed in the near-term pertain to the extent of clinicians' responsibilities for reviewing the entire computer-accessible clinical synopsis from multiple clinicians and institutions, the liabilities posed by overriding clinical decision support warnings and alerts, and mechanisms for clinicians to publically report potential EHR safety issues. Ethical dilemmas that need additional discussion relate to opt-out provisions that exclude patients from electronic record storage, sale of deidentified patient data by EHR vendors, adolescent control of access to their data, and use of electronic data repositories to redesign the nation's health care delivery and payment mechanisms on the basis of statistical analyses. Finally, one overwhelming financial question is who should pay for EHR implementation because most users and current owners of these systems will not receive the majority of benefits. The authors recommend that key stakeholders begin discussing these issues in a national forum. These actions can help identify and prioritize solutions to the key legal, ethical, and financial dilemmas discussed, so that widespread, safe, effective, interoperable EHRs can help transform health care.

Public health nurse perceptions of Omaha System data visualization.

PubMed

Lee, Seonah; Kim, Era; Monsen, Karen A

2015-10-01

Electronic health records (EHRs) provide many benefits related to the storage, deployment, and retrieval of large amounts of patient data. However, EHRs have not fully met the need to reuse data for decision making on follow-up care plans. Visualization offers new ways to present health data, especially in EHRs. Well-designed data visualization allows clinicians to communicate information efficiently and effectively, contributing to improved interpretation of clinical data and better patient care monitoring and decision making. Public health nurse (PHN) perceptions of Omaha System data visualization prototypes for use in EHRs have not been evaluated. To visualize PHN-generated Omaha System data and assess PHN perceptions regarding the visual validity, helpfulness, usefulness, and importance of the visualizations, including interactive functionality. Time-oriented visualization for problems and outcomes and Matrix visualization for problems and interventions were developed using PHN-generated Omaha System data to help PHNs consume data and plan care at the point of care. Eleven PHNs evaluated prototype visualizations. Overall PHNs response to visualizations was positive, and feedback for improvement was provided. This study demonstrated the potential for using visualization techniques within EHRs to summarize Omaha System patient data for clinicians. Further research is needed to improve and refine these visualizations and assess the potential to incorporate visualizations within clinical EHRs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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.

Graphical overview and navigation of electronic health records in a prototyping environment using Google Earth and openEHR archetypes.

PubMed

Sundvall, Erik; Nyström, Mikael; Forss, Mattias; Chen, Rong; Petersson, Håkan; Ahlfeldt, Hans

2007-01-01

This paper describes selected earlier approaches to graphically relating events to each other and to time; some new combinations are also suggested. These are then combined into a unified prototyping environment for visualization and navigation of electronic health records. Google Earth (GE) is used for handling display and interaction of clinical information stored using openEHR data structures and 'archetypes'. The strength of the approach comes from GE's sophisticated handling of detail levels, from coarse overviews to fine-grained details that has been combined with linear, polar and region-based views of clinical events related to time. The system should be easy to learn since all the visualization styles can use the same navigation. The structured and multifaceted approach to handling time that is possible with archetyped openEHR data lends itself well to visualizing and integration with openEHR components is provided in the environment.

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

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

Opening the Duke electronic health record to apps: Implementing SMART on FHIR.

PubMed

Bloomfield, Richard A; Polo-Wood, Felipe; Mandel, Joshua C; Mandl, Kenneth D

2017-03-01

Recognizing a need for our EHR to be highly interoperable, our team at Duke Health enabled our Epic-based electronic health record to be compatible with the Boston Children's project called Substitutable Medical Apps and Reusable Technologies (SMART), which employed Health Level Seven International's (HL7) Fast Healthcare Interoperability Resources (FHIR), commonly known as SMART on FHIR. We created a custom SMART on FHIR-compatible server infrastructure written in Node.js that served two primary functions. First, it handled API management activities such rate-limiting, authorization, auditing, logging, and analytics. Second, it retrieved the EHR data and made it available in a FHIR-compatible format. Finally, we made required changes to the EHR user interface to allow us to integrate several compatible apps into the provider- and patient-facing EHR workflows. After integrating SMART on FHIR into our Epic-based EHR, we demonstrated several types of apps running on the infrastructure. This included both provider- and patient-facing apps as well as apps that are closed source, open source and internally-developed. We integrated the apps into the testing environment of our desktop EHR as well as our patient portal. We also demonstrated the integration of a native iOS app. In this paper, we demonstrate the successful implementation of the SMART and FHIR technologies on our Epic-based EHR and subsequent integration of several compatible provider- and patient-facing apps. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

“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

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.

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.

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.

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.

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.

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

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

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.

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.

Rheumatology Informatics System for Effectiveness: A National Informatics-Enabled Registry for Quality Improvement.

PubMed

Yazdany, Jinoos; Bansback, Nick; Clowse, Megan; Collier, Deborah; Law, Karen; Liao, Katherine P; Michaud, Kaleb; Morgan, Esi M; Oates, James C; Orozco, Catalina; Reimold, Andreas; Simard, Julia F; Myslinski, Rachel; Kazi, Salahuddin

2016-12-01

The Rheumatology Informatics System for Effectiveness (RISE) is a national electronic health record (EHR)-enabled registry. RISE passively collects data from EHRs of participating practices, provides advanced quality measurement and data analytic capacities, and fulfills national quality reporting requirements. Here we report the registry's architecture and initial data, and we demonstrate how RISE is being used to improve the quality of care. RISE is a certified Centers for Medicare and Medicaid Services Qualified Clinical Data Registry, allowing collection of data without individual patient informed consent. We analyzed data between October 1, 2014 and September 30, 2015 to characterize initial practices and patients captured in RISE. We also analyzed medication use among rheumatoid arthritis (RA) patients and performance on several quality measures. Across 55 sites, 312 clinicians contributed data to RISE; 72% were in group practice, 21% in solo practice, and 7% were part of a larger health system. Sites contributed data on 239,302 individuals. Among the subset with RA, 34.4% of patients were taking a biologic or targeted synthetic disease-modifying antirheumatic drug (DMARD) at their last encounter, and 66.7% were receiving a nonbiologic DMARD. Examples of quality measures include that 55.2% had a disease activity score recorded, 53.6% a functional status score, and 91.0% were taking a DMARD in the last year. RISE provides critical infrastructure for improving the quality of care in rheumatology and is a unique data source to generate new knowledge. Data validation and mapping are ongoing and RISE is available to the research and clinical communities to advance rheumatology. © 2016, American College of Rheumatology.

75 FR 36157 - Establishment of the Temporary Certification Program for Health Information Technology

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-24

...This final rule establishes a temporary certification program for the purposes of testing and certifying health information technology. This final rule is established under the authority granted to the National Coordinator for Health Information Technology (the National Coordinator) by section 3001(c)(5) of the Public Health Service Act (PHSA), as added by the Health Information Technology for Economic and Clinical Health (HITECH) Act. The National Coordinator will utilize the temporary certification program to authorize organizations to test and certify Complete Electronic Health Records (EHRs) and/or EHR Modules, thereby making Certified EHR Technology available prior to the date on which health care providers seeking incentive payments available under the Medicare and Medicaid EHR Incentive Programs may begin demonstrating meaningful use of Certified EHR Technology.

A platform for exploration into chaining of web services for clinical data transformation and reasoning

PubMed Central

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. PMID:28269882

Developing a National-Level Concept Dictionary for EHR Implementations in Kenya.

PubMed

Keny, Aggrey; Wanyee, Steven; Kwaro, Daniel; Mulwa, Edwin; Were, Martin C

2015-01-01

The increasing adoption of Electronic Health Records (EHR) by developing countries comes with the need to develop common terminology standards to assure semantic interoperability. In Kenya, where the Ministry of Health has rolled out an EHR at 646 sites, several challenges have emerged including variable dictionaries across implementations, inability to easily share data across systems, lack of expertise in dictionary management, lack of central coordination and custody of a terminology service, inadequately defined policies and processes, insufficient infrastructure, among others. A Concept Working Group was constituted to address these challenges. The country settled on a common Kenya data dictionary, initially derived as a subset of the Columbia International eHealth Laboratory (CIEL)/Millennium Villages Project (MVP) dictionary. The initial dictionary scope largely focuses on clinical needs. Processes and policies around dictionary management are being guided by the framework developed by Bakhshi-Raiez et al. Technical and infrastructure-based approaches are also underway to streamline workflow for dictionary management and distribution across implementations. Kenya's approach on comprehensive common dictionary can serve as a model for other countries in similar settings.

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.

Collaborative eHealth Meets Security: Privacy-Enhancing Patient Profile Management.

PubMed

Sanchez-Guerrero, Rosa; Mendoza, Florina Almenarez; Diaz-Sanchez, Daniel; Cabarcos, Patricia Arias; Lopez, Andres Marin

2017-11-01

Collaborative healthcare environments offer potential benefits, including enhancing the healthcare quality delivered to patients and reducing costs. As a direct consequence, sharing of electronic health records (EHRs) among healthcare providers has experienced a noteworthy growth in the last years, since it enables physicians to remotely monitor patients' health and enables individuals to manage their own health data more easily. However, these scenarios face significant challenges regarding security and privacy of the extremely sensitive information contained in EHRs. Thus, a flexible, efficient, and standards-based solution is indispensable to guarantee selective identity information disclosure and preserve patient's privacy. We propose a privacy-aware profile management approach that empowers the patient role, enabling him to bring together various healthcare providers as well as user-generated claims into an unique credential. User profiles are represented through an adaptive Merkle Tree, for which we formalize the underlying mathematical model. Furthermore, performance of the proposed solution is empirically validated through simulation experiments.

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.

Big Data Analytics for Genomic Medicine

PubMed Central

He, Karen Y.; Ge, Dongliang; He, Max M.

2017-01-01

Genomic medicine attempts to build individualized strategies for diagnostic or therapeutic decision-making by utilizing patients’ genomic information. Big Data analytics uncovers hidden patterns, unknown correlations, and other insights through examining large-scale various data sets. While integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a Big Data infrastructure exhibit challenges, they also provide a feasible opportunity to develop an efficient and effective approach to identify clinically actionable genetic variants for individualized diagnosis and therapy. In this paper, we review the challenges of manipulating large-scale next-generation sequencing (NGS) data and diverse clinical data derived from the EHRs for genomic medicine. We introduce possible solutions for different challenges in manipulating, managing, and analyzing genomic and clinical data to implement genomic medicine. Additionally, we also present a practical Big Data toolset for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs. PMID:28212287

Big Data Analytics for Genomic Medicine.

PubMed

He, Karen Y; Ge, Dongliang; He, Max M

2017-02-15

Genomic medicine attempts to build individualized strategies for diagnostic or therapeutic decision-making by utilizing patients' genomic information. Big Data analytics uncovers hidden patterns, unknown correlations, and other insights through examining large-scale various data sets. While integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a Big Data infrastructure exhibit challenges, they also provide a feasible opportunity to develop an efficient and effective approach to identify clinically actionable genetic variants for individualized diagnosis and therapy. In this paper, we review the challenges of manipulating large-scale next-generation sequencing (NGS) data and diverse clinical data derived from the EHRs for genomic medicine. We introduce possible solutions for different challenges in manipulating, managing, and analyzing genomic and clinical data to implement genomic medicine. Additionally, we also present a practical Big Data toolset for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs.

The journey of primary care practices to meaningful use: a Colorado Beacon Consortium study.

PubMed

Fernald, Douglas H; Wearner, Robyn; Dickinson, W Perry

2013-01-01

The Health Information Technology for Economic and Clinical Health Act of 2009 provides for incentive payments through Medicare and Medicaid for clinicians who implement electronic health records (EHRs) and use this technology meaningfully to improve patient care. There are few comprehensive descriptions of how primary care practices achieve the meaningful use of clinical data, including the formal stage 1 meaningful use requirements. Evaluation of the Colorado Beacon Consortium project included iterative qualitative analysis of practice narratives, provider and staff interviews, and separate focus groups with quality improvement (QI) advisors and staff from the regional health information exchange (HIE). Most practices described significant realignment of practice priorities and aims, which often required substantial education and training of physicians and staff. Re-engineering office processes, data collection protocols, EHRs, staff roles, and practice culture comprised the primary effort and commitment to attest to stage 1 meaningful use and subsequent meaningful use of clinical data. While realizing important benefits, practices bore a significant burden in learning the true capabilities of their EHRs with little effective support from vendors. Attestation was an important initial milestone in the process, but practices faced substantial ongoing work to use their data meaningfully for patient care and QI. Key resources were instrumental to these practices: local technical EHR expertise; collaborative learning mechanisms; and regular contact and support from QI advisors. Meeting the stage 1 requirements for incentives under Medicare and Medicaid meaningful use criteria is the first waypoint in a longer journey by primary care practices to the meaningful use of electronic data to continuously improve the care and health of their patients. The intensive re-engineering effort for stage 1 yielded practice changes consistent with larger practice aims and goals. While many of these practices are now poised to use data meaningfully, faster progress will likely come with continued local QI and technical support and planned community-wide learning.

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

Survey of patient and public perceptions of electronic health records for healthcare, policy and research: study protocol.

PubMed

Luchenski, Serena; Balasanthiran, Anjali; Marston, Cicely; Sasaki, Kaori; Majeed, Azeem; Bell, Derek; Reed, Julie E

2012-05-23

Immediate access to patients' complete health records via electronic databases could improve healthcare and facilitate health research. However, the possible benefits of a national electronic health records (EHR) system must be balanced against public concerns about data security and personal privacy. Successful development of EHR requires better understanding of the views of the public and those most affected by EHR: users of the National Health Service. This study aims to explore the correlation between personal healthcare experience (including number of healthcare contacts and number and type of longer term conditions) and views relating to development of EHR for healthcare, health services planning and policy and health research. A multi-site cross-sectional self-complete questionnaire designed and piloted for use in waiting rooms was administered to patients from randomly selected outpatients' clinics at a university teaching hospital (431 beds) and general practice surgeries from the four primary care trusts within the catchment area of the hospital. All patients entering the selected outpatients clinics and general practice surgeries were invited to take part in the survey during August-September 2011. Statistical analyses will be conducted using descriptive techniques to present respondents' overall views about electronic health records and logistic regression to explore associations between these views and participants' personal circumstances, experiences, sociodemographics and more specific views about electronic health records. The study design and implementation were successful, resulting in unusually high response rates and overall recruitment (85.5%, 5336 responses). Rates for face-to-face recruitment in previous work are variable, but typically lower (mean 76.7%, SD 20). We discuss details of how we collected the data to provide insight into how we obtained this unusually high response rate.

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.

Removal of paper-based health records from Norwegian hospitals: effects on clinical workflow.

PubMed

Lium, Jan Tore; Faxvaag, Arild

2006-01-01

Several Norwegian hospitals have, plan, or are in the process of removing the paper-based health record from clinical workflow. To assess the impact on usage and satisfaction of electronic health record (EHR) systems, we conducted a survey among physicians, nurses and medical secretaries at selected departments from six Norwegian hospitals. The main feature of the questionnaire is the description of a set of tasks commonly performed at hospitals, and respondents were asked to rate their usage and change of ease compared to previous routines for each tasks. There were 24 tasks for physicians, 19 for nurses and 23 for medical secretaries. In total, 64 physicians, 128 nurses and 57 medical secretaries responded, corresponding to a response rate of 68%, 58% and 84% respectively. Results showed a large degree of use among medical secretaries, while physicians and nurses displayed a more modest degree of use. Possibly suggesting that the EHR systems among clinicians still is considered more of an administrative system. Among the two latter groups, tasks regarding information retrieval were used more extensively than tasks regarding generating and storing information. Also, we observed large differences between hospitals and higher satisfaction with the part of the system handling regular electronic data than scanned document images. Even though the increase in use among clinicians after removing the paper based record were mainly in tasks where respondents had no choice other than use the electronic health record, the attitude towards EHR-systems were mainly positive. Thus, while removing the paper based record has yet to promote new ways of working, we see it as an important step towards the EHR system of tomorrow. Several Norwegian hospitals have shown that it is possible.

Costs and benefits of health information technology.

PubMed

Shekelle, Paul G; Morton, Sally C; Keeler, Emmett B

2006-04-01

An evidence report was prepared to assess the evidence base regarding benefits and costs of health information technology (HIT) systems, that is, the value of discrete HIT functions and systems in various healthcare settings, particularly those providing pediatric care. PubMed, the Cochrane Controlled Clinical Trials Register, and the Cochrane Database of Reviews of Effectiveness (DARE) were electronically searched for articles published since 1995. Several reports prepared by private industry were also reviewed. Of 855 studies screened, 256 were included in the final analyses. These included systematic reviews, meta-analyses, studies that tested a hypothesis, and predictive analyses. Each article was reviewed independently by two reviewers; disagreement was resolved by consensus. Of the 256 studies, 156 concerned decision support, 84 assessed the electronic medical record, and 30 were about computerized physician order entry (categories are not mutually exclusive). One hundred twenty four of the studies assessed the effect of the HIT system in the outpatient or ambulatory setting; 82 assessed its use in the hospital or inpatient setting. Ninety-seven studies used a randomized design. There were 11 other controlled clinical trials, 33 studies using a pre-post design, and 20 studies using a time series. Another 17 were case studies with a concurrent control. Of the 211 hypothesis-testing studies, 82 contained at least some cost data. We identified no study or collection of studies, outside of those from a handful of HIT leaders, that would allow a reader to make a determination about the generalizable knowledge of the study's reported benefit. Beside these studies from HIT leaders, no other research assessed HIT systems that had comprehensive functionality and included data on costs, relevant information on organizational context and process change, and data on implementation. A small body of literature supports a role for HIT in improving the quality of pediatric care. Insufficient data were available on the costs or cost-effectiveness of implementing such systems. The ability of Electronic Health Records (EHRs) to improve the quality of care in ambulatory care settings was demonstrated in a small series of studies conducted at four sites (three U.S. medical centers and one in the Netherlands). The studies demonstrated improvements in provider performance when clinical information management and decision support tools were made available within an EHR system, particularly when the EHRs had the capacity to store data with high fidelity, to make those data readily accessible, and to help translate them into context-specific information that can empower providers in their work. Despite the heterogeneity in the analytic methods used, all cost-benefit analyses predicted substantial savings from EHR (and health care information exchange and interoperability) implementation: The quantifiable benefits are projected to outweigh the investment costs. However, the predicted time needed to break even varied from three to as many as 13 years. HIT has the potential to enable a dramatic transformation in the delivery of health care, making it safer, more effective, and more efficient. Some organizations have already realized major gains through the implementation of multifunctional, interoperable HIT systems built around an EHR. However, widespread implementation of HIT has been limited by a lack of generalizable knowledge about what types of HIT and implementation methods will improve care and manage costs for specific health organizations. The reporting of HIT development and implementation requires fuller descriptions of both the intervention and the organizational/economic environment in which it is implemented.

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

Impact of Medical Scribes on Physician and Patient Satisfaction in Primary Care.

PubMed

Pozdnyakova, Anastasia; Laiteerapong, Neda; Volerman, Anna; Feld, Lauren D; Wan, Wen; Burnet, Deborah L; Lee, Wei Wei

2018-04-26

Use of electronic health records (EHRs) is associated with physician stress and burnout. While emergency departments and subspecialists have used scribes to address this issue, little is known about the impact of scribes in academic primary care. Assess the impact of a scribe on physician and patient satisfaction at an academic general internal medicine (GIM) clinic. Prospective, pre-post-pilot study. During the 3-month pilot, physicians had clinic sessions with and without a scribe. We assessed changes in (1) physician workplace satisfaction and burnout, (2) time spent on EHR documentation, and (3) patient satisfaction. Six GIM faculty and a convenience sample of their patients (N = 325) at an academic GIM clinic. A 21-item pre- and 44-item post-pilot survey assessed physician workplace satisfaction and burnout. Physicians used logs to record time spent on EHR documentation outside of clinic hours. A 27-item post-visit survey assessed patient satisfaction during visits with and without the scribe. Of six physicians, 100% were satisfied with clinic workflow post-pilot (vs. 33% pre-pilot), and 83% were satisfied with EHR use post-pilot (vs. 17% pre-pilot). Physician burnout was low at baseline and did not change post-pilot. Mean time spent on post-clinic EHR documentation decreased from 1.65 to 0.76 h per clinic session (p = 0.02). Patient satisfaction was not different between patients who had clinic visits with vs. without scribe overall or by age, gender, and race. Compared to patients 65 years or older, younger patients were more likely to report that the physician was more attentive and provided more education during visits with the scribe present (p = 0.03 and 0.02, respectively). Male patients were more likely to report that they disliked having a scribe (p = 0.03). In an academic GIM setting, employment of a scribe was associated with improved physician satisfaction without compromising patient satisfaction.

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.

Creating ISO/EN 13606 archetypes based on clinical information needs.

PubMed

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

2011-01-01

Archetypes model individual EHR contents and build the basis of the dual-model approach used in the ISO/EN 13606 EHR architecture. We present an approach to create archetypes using an iterative development process. It includes automated generation of electronic case report forms from archetypes. We evaluated our approach by developing 128 archetypes which represent 446 clinical information items from the diabetes domain.

Lightweight application for generating clinical research information systems: MAGIC.

PubMed

Leskošek, Brane; Pajntar, Marjan

2015-12-01

Our purpose was to build and test a lightweight solution for generating clinical research information systems (CRIS) that would allow non-IT professionals with basic knowledge of computer usage to quickly define and build a ready-to-use, safe and secure web-based clinical research system for data management. We use the acronym MAGIC (Medical Application Generator InteraCtive) for the system. The generated CRIS should be very easy to build and use, so a common LAMP (Linux Apache MySQL Perl) platform was used, which also enables short development cycles. The application was built and tested using eXtreme Programming (XP) principles by a small development team consisting of one informatics specialist, one physician and one graphical designer/programmer. The parameter and graphical user interface (GUI) definitions for the CRIS can be made by non-IT professionals using an intuitive English-language-like formalism called application definition language (ADL). From these definitions, the MAGIC builds an end-user CRIS that can be used on a wide variety of platforms (from standard workstations to hand-held devices). A working example of a national health-care-quality assessment program is presented to illustrate this process. The lightweight application for generating CRIS (MAGIC) has proven to be useful for both clinical and analytical users in real working environment. To achieve better performance and interoperability, we are planning to recompile the application using XML schemas (XSD) in HL7 CDA or openEHR archetypes formats used for parameters definition and for data interchange between different information systems.

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.

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.

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.

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.

Adapting practice-based intervention research to electronic environments: opportunities and complexities at two institutions.

PubMed

Stille, Christopher J; Lockhart, Steven A; Maertens, Julie A; Madden, Christi A; Darden, Paul M

2015-01-01

Primary care practice-based research has become more complex with increased use of electronic health records (EHRs). Little has been reported about changes in study planning and execution that are required as practices change from paper-based to electronic-based environments. We describe the evolution of a pediatric practice-based intervention study as it was adapted for use in the electronic environment, to enable other practice-based researchers to plan efficient, effective studies. We adapted a paper-based pediatric office-level intervention to enhance parent-provider communication about subspecialty referrals for use in two practice-based research networks (PBRNs) with partially and fully electronic environments. We documented the process of adaptation and its effect on study feasibility and efficiency, resource use, and administrative and regulatory complexities, as the study was implemented in the two networks. Considerable time and money was required to adapt the paper-based study to the electronic environment, requiring extra meetings with institutional EHR-, regulatory-, and administrative teams, and increased practice training. Institutional unfamiliarity with using EHRs in practice-based research, and the consequent need to develop new policies, were major contributors to delays. Adapting intervention tools to the EHR and minimizing practice disruptions was challenging, but resulted in several efficiencies as compared with a paper-based project. In particular, recruitment and tracking of subjects and data collection were easier and more efficient. Practice-based intervention research in an electronic environment adds considerable cost and time at the outset of a study, especially for centers unfamiliar with such research. Efficiencies generated have the potential of easing the work of study enrollment, subject tracking, and data collection.

Implications of electronic health record downtime: an analysis of patient safety event reports.

PubMed

Larsen, Ethan; Fong, Allan; Wernz, Christian; Ratwani, Raj M

2018-02-01

We sought to understand the types of clinical processes, such as image and medication ordering, that are disrupted during electronic health record (EHR) downtime periods by analyzing the narratives of patient safety event report data. From a database of 80 381 event reports, 76 reports were identified as explicitly describing a safety event associated with an EHR downtime period. These reports were analyzed and categorized based on a developed code book to identify the clinical processes that were impacted by downtime. We also examined whether downtime procedures were in place and followed. The reports were coded into categories related to their reported clinical process: Laboratory, Medication, Imaging, Registration, Patient Handoff, Documentation, History Viewing, Delay of Procedure, and General. A majority of reports (48.7%, n = 37) were associated with lab orders and results, followed by medication ordering and administration (14.5%, n = 11). Incidents commonly involved patient identification and communication of clinical information. A majority of reports (46%, n = 35) indicated that downtime procedures either were not followed or were not in place. Only 27.6% of incidents (n = 21) indicated that downtime procedures were successfully executed. Patient safety report data offer a lens into EHR downtime-related safety hazards. Important areas of risk during EHR downtime periods were patient identification and communication of clinical information; these should be a focus of downtime procedure planning to reduce safety hazards. EHR downtime events pose patient safety hazards, and we highlight critical areas for downtime procedure improvement. © 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

Patient characteristics associated with venous thromboembolic events: a cohort study using pooled electronic health record data

PubMed Central

Foster, Wendy; Gilder, Jason; Love, Thomas E; Jain, Anil K

2012-01-01

Objective To demonstrate the potential of de-identified clinical data from multiple healthcare systems using different electronic health records (EHR) to be efficiently used for very large retrospective cohort studies. Materials and methods Data of 959 030 patients, pooled from multiple different healthcare systems with distinct EHR, were obtained. Data were standardized and normalized using common ontologies, searchable through a HIPAA-compliant, patient de-identified web application (Explore; Explorys Inc). Patients were 26 years or older seen in multiple healthcare systems from 1999 to 2011 with data from EHR. Results Comparing obese, tall subjects with normal body mass index, short subjects, the venous thromboembolic events (VTE) OR was 1.83 (95% CI 1.76 to 1.91) for women and 1.21 (1.10 to 1.32) for men. Weight had more effect then height on VTE. Compared with Caucasian, Hispanic/Latino subjects had a much lower risk of VTE (female OR 0.47, 0.41 to 0.55; male OR 0.24, 0.20 to 0.28) and African-Americans a substantially higher risk (female OR 1.83, 1.76 to 1.91; male OR 1.58, 1.50 to 1.66). This 13-year retrospective study of almost one million patients was performed over approximately 125 h in 11 weeks, part time by the five authors. Discussion As research informatics tools develop and more clinical data become available in EHR, it is important to study and understand unique opportunities for clinical research informatics to transform the scale and resources needed to perform certain types of clinical research. Conclusions With the right clinical research informatics tools and EHR data, some types of very large cohort studies can be completed with minimal resources. PMID:22759621

TextHunter – A User Friendly Tool for Extracting Generic Concepts from Free Text in Clinical Research

PubMed Central

Jackson MSc, Richard G.; Ball, Michael; Patel, Rashmi; Hayes, Richard D.; Dobson, Richard J.B.; Stewart, Robert

2014-01-01

Observational research using data from electronic health records (EHR) is a rapidly growing area, which promises both increased sample size and data richness - therefore unprecedented study power. However, in many medical domains, large amounts of potentially valuable data are contained within the free text clinical narrative. Manually reviewing free text to obtain desired information is an inefficient use of researcher time and skill. Previous work has demonstrated the feasibility of applying Natural Language Processing (NLP) to extract information. However, in real world research environments, the demand for NLP skills outweighs supply, creating a bottleneck in the secondary exploitation of the EHR. To address this, we present TextHunter, a tool for the creation of training data, construction of concept extraction machine learning models and their application to documents. Using confidence thresholds to ensure high precision (>90%), we achieved recall measurements as high as 99% in real world use cases. PMID:25954379

A Novel Patient Recruitment Strategy: Patient Selection Directly from the Community through Linkage to Clinical Data.

PubMed

Zimmerman, Lindsay P; Goel, Satyender; Sathar, Shazia; Gladfelter, Charon E; Onate, Alejandra; Kane, Lindsey L; Sital, Shelly; Phua, Jasmin; Davis, Paris; Margellos-Anast, Helen; Meltzer, David O; Polonsky, Tamar S; Shah, Raj C; Trick, William E; Ahmad, Faraz S; Kho, Abel N

2018-01-01

This article presents and describes our methods in developing a novel strategy for recruitment of underrepresented, community-based participants, for pragmatic research studies leveraging routinely collected electronic health record (EHR) data. We designed a new approach for recruiting eligible patients from the community, while also leveraging affiliated health systems to extract clinical data for community participants. The strategy involves methods for data collection, linkage, and tracking. In this workflow, potential participants are identified in the community and surveyed regarding eligibility. These data are then encrypted and deidentified via a hashing algorithm for linkage of the community participant back to a record at a clinical site. The linkage allows for eligibility verification and automated follow-up. Longitudinal data are collected by querying the EHR data and surveying the community participant directly. We discuss this strategy within the context of two national research projects, a clinical trial and an observational cohort study. The community-based recruitment strategy is a novel, low-touch, clinical trial enrollment method to engage a diverse set of participants. Direct outreach to community participants, while utilizing EHR data for clinical information and follow-up, allows for efficient recruitment and follow-up strategies. This new strategy for recruitment links data reported from community participants to clinical data in the EHR and allows for eligibility verification and automated follow-up. The workflow has the potential to improve recruitment efficiency and engage traditionally underrepresented individuals in research. Schattauer GmbH Stuttgart.

Interoperable Archetypes With a Three Folded Terminology Governance.

PubMed

Pederson, Rune; Ellingsen, Gunnar

2015-01-01

The use of openEHR archetypes increases the interoperability of clinical terminology, and in doing so improves upon the availability of clinical terminology for both primary and secondary purposes. Where clinical terminology is employed in the EPR system, research reports conflicting a results for the use of structuring and standardization as measurements of success. In order to elucidate this concept, this paper focuses on the effort to establish a national repository for openEHR based archetypes in Norway where clinical terminology could be included with benefit for interoperability three folded.

Differences in Sociocognitive Beliefs between Involved and Noninvolved Employees during the Implementation of an Electronic Health Record System

PubMed Central

Stanczyk, Nicola Esther; Crutzen, Rik; Sewuster, Nikki; Schotanus, Elwin; Mulders, Merijn; Cremers, Henricus Paul

2017-01-01

Background Electronic health records (EHRs) can improve quality and efficiency in patient care. However, the intention to work with such a new system is often relatively low among employees because the work processes of the healthcare organization may change. Involving employees in an EHR implementation may increase their beliefs and perceived capabilities concerning the new system. The current study aimed to assess the role of involvement and its effects on sociocognitive beliefs regarding the implementation of a new EHR system. Methods The study was performed in June 2015 among all eligible employees of a hospital in the Netherlands. Both involved and noninvolved employees were invited to complete a paper-based questionnaire concerning their sociocognitive beliefs (i.e., attitude, social influence, self-efficacy, and intention) related to the EHR implementation. Independent sample t-tests were used to assess potential differences in sociocognitive beliefs between employees who were involved in the implementation process and those who were not. Effect sizes (Cohen's d) were calculated to indicate the standardized difference between the means. Results A total of 359 participants completed the paper-based questionnaire and were included in the analyses. Involved employees (n = 94) reported significantly higher levels of attitude (p < .001, d = .62), perceived self-efficacy (p = .01, d = .31), social support (p < .001, d = .68), and a higher intention to work with the new EHR system (p < .001, d = .60), compared with the group of employees who were not involved in the implementation process (n = 265). Conclusion Involving employees during an EHR implementation appears to enhance employees’ sociocognitive beliefs and increases their intention to work with the new system. PMID:28566986

Differences in Sociocognitive Beliefs between Involved and Noninvolved Employees during the Implementation of an Electronic Health Record System.

PubMed

Stanczyk, Nicola Esther; Crutzen, Rik; Sewuster, Nikki; Schotanus, Elwin; Mulders, Merijn; Cremers, Henricus Paul

2017-01-01

Electronic health records (EHRs) can improve quality and efficiency in patient care. However, the intention to work with such a new system is often relatively low among employees because the work processes of the healthcare organization may change. Involving employees in an EHR implementation may increase their beliefs and perceived capabilities concerning the new system. The current study aimed to assess the role of involvement and its effects on sociocognitive beliefs regarding the implementation of a new EHR system. The study was performed in June 2015 among all eligible employees of a hospital in the Netherlands. Both involved and noninvolved employees were invited to complete a paper-based questionnaire concerning their sociocognitive beliefs (i.e., attitude, social influence, self-efficacy, and intention) related to the EHR implementation. Independent sample t-tests were used to assess potential differences in sociocognitive beliefs between employees who were involved in the implementation process and those who were not. Effect sizes (Cohen's d ) were calculated to indicate the standardized difference between the means. A total of 359 participants completed the paper-based questionnaire and were included in the analyses. Involved employees ( n = 94) reported significantly higher levels of attitude ( p < .001, d = .62), perceived self-efficacy ( p = .01, d = .31), social support ( p < .001, d = .68), and a higher intention to work with the new EHR system ( p < .001, d = .60), compared with the group of employees who were not involved in the implementation process ( n = 265). Involving employees during an EHR implementation appears to enhance employees' sociocognitive beliefs and increases their intention to work with the new system.

Electronic health records: critical success factors in implementation.

PubMed

Safdari, Reza; Ghazisaeidi, Marjan; Jebraeily, Mohamad

2015-04-01

EHR implementation results in the improved quality of care, customer-orientation and timely access to complete information. Despite the potential benefits of EHR, its implementation is a difficult and complex task whose success depends on many factors. The purpose of this research is indeed to identify the key success factors of EHR. This is a cross-sectional survey conducted with participation of 340 work forces from different types of job from Hospitals of TUMS in 2014. Data were collected using a self-structured questionnaire which was estimated as both reliable and valid. The data were analyzed by SPSS software descriptive statistics and analytical statistics. 58.2% of respondents were female and their mean age and work experience were 37.7 and 11.2 years, respectively and most respondents (52.5%) was bachelor. In terms of job, the maximum rate was related to nursing (33 %) and physician (21 %). the main category of critical success factors in Implementation EHRs, the highest rate related to Project Management (4.62) and lowest related to Organizational factors (3.98). success in implementation EHRs requirement more centralization to project management and human factors. Therefore must be Creating to EHR roadmap implementation, establishment teamwork to participation of end-users and select prepare leadership, users obtains sufficient training to use of system and also prepare support from maintain and promotion system.

A virtual platform for electronic health record (EHR) education for nursing students: moving from in-house solutions to the cloud.

PubMed

Kushniruk, Andre W; Kuo, Mu-Hsing; Parapini, Eric; Borycki, Elizabeth M

2014-01-01

There is a need to develop cost effective ways to bring hands-on education about essential information technologies, such as electronic health record (EHR) systems to nursing students, nursing faculty and practitioners. This is especially the case as worldwide there is an increased deployment of these systems and they are transforming the practice of healthcare. However, due to technical, financial and knowledge limitations, many nursing schools and programs do not have an adequate way to bring such technology into their classes and curricula. In this paper we describe an approach to developing Web-based EHR education that allows students from any Web-accessible location to access and work with real EHR systems remotely over the Internet for learning purposes. In this paper we describe our work in moving this approach to a cloud-based solution to allow access to EHRs for educational purposes from any location with Web access and to do so in a way that is both educationally sound and cost effective.

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.

The Challenges of Data Quality Evaluation in a Joint Data Warehouse

PubMed Central

Bae, Charles J.; Griffith, Sandra; Fan, Youran; Dunphy, Cheryl; Thompson, Nicolas; Urchek, John; Parchman, Alandra; Katzan, Irene L.

2015-01-01

Introduction: The use of clinically derived data from electronic health records (EHRs) and other electronic clinical systems can greatly facilitate clinical research as well as operational and quality initiatives. One approach for making these data available is to incorporate data from different sources into a joint data warehouse. When using such a data warehouse, it is important to understand the quality of the data. The primary objective of this study was to determine the completeness and concordance of common types of clinical data available in the Knowledge Program (KP) joint data warehouse, which contains feeds from several electronic systems including the EHR. Methods: A manual review was performed of specific data elements for 250 patients from an EHR, and these were compared with corresponding elements in the KP data warehouse. Completeness and concordance were calculated for five categories of data including demographics, vital signs, laboratory results, diagnoses, and medications. Results: In general, data elements for demographics, vital signs, diagnoses, and laboratory results were present in more cases in the source EHR compared to the KP. When data elements were available in both sources, there was a high concordance. In contrast, the KP data warehouse documented a higher prevalence of deaths and medications compared to the EHR. Discussion: Several factors contributed to the discrepancies between data in the KP and the EHR—including the start date and frequency of data feeds updates into the KP, inability to transfer data located in nonstructured formats (e.g., free text or scanned documents), as well as incomplete and missing data variables in the source EHR. Conclusion: When evaluating the quality of a data warehouse with multiple data sources, assessing completeness and concordance between data set and source data may be better than designating one to be a gold standard. This will allow the user to optimize the method and timing of data transfer in order to capture data with better accuracy. PMID:26290882

Health Technology Integration for Clinical, Patient Records and Financial Management Related to the Military

DTIC Science & Technology

2012-09-01

approaches for nurses regarding the usage of a newly-implemented electronic health records (EHR) system at a large hospital. The study compares the...standard classroom training had no measureable effect on training outcomes. Our second key finding is that nurses with higher levels of education and...Staff Training, Nurse Training, Web-Based Training, EHR Training, Health Information Technology, HIT Health Technology Integration for Clinical

Evaluating the data completeness in the Electronic Health Record after the Implementation of an Outpatient Electronic Health Record.

PubMed

Soto, Mauricio; Capurro, Daniel; Catalán, Silvia

2015-01-01

Electronic health records (EHRs) present an opportunity for quality improvement in health organitations, particularly at the primary health level. However, EHR implementation impacts clinical workflows, and physicians frequently prefer to document in a non-structured way, which ultimately hinders the ability to measure quality indicators. We present an assessment of data completeness-a key data quality indicator-during the first 12 months after the implementation of an EHR at a teaching outpatient center in Santiago, Chile.

A Document-Based EHR System That Controls the Disclosure of Clinical Documents Using an Access Control List File Based on the HL7 CDA Header.

PubMed

Takeda, Toshihiro; Ueda, Kanayo; Nakagawa, Akito; Manabe, Shirou; Okada, Katsuki; Mihara, Naoki; Matsumura, Yasushi

2017-01-01

Electronic health record (EHR) systems are necessary for the sharing of medical information between care delivery organizations (CDOs). We developed a document-based EHR system in which all of the PDF documents that are stored in our electronic medical record system can be disclosed to selected target CDOs. An access control list (ACL) file was designed based on the HL7 CDA header to manage the information that is disclosed.

Aspects of the Patient-centered Medical Home currently in place: initial findings from preparing the personal physician for practice.

PubMed

Carney, Patricia A; Eiff, M Patrice; Saultz, John W; Douglass, Alan B; Tillotson, Carrie J; Crane, Steven D; Jones, Samuel M; Green, Larry A

2009-10-01

The Patient-centered Medical Home (PCMH) is a central concept in the evolving debate about American health care reform. We studied family medicine residency training programs' continuity clinics to assess baseline status of implementing PCMH components and to compare implementation status between community-based and university training programs. We conducted a survey 24 continuity clinics in 14 residency programs that are part of the Preparing the Personal Physicians for Practice (P(4)) program. We asked questions about aspects of P(4) that had been already implemented at the beginning of the P(4) program. We defined high implementation as aspects that were present in >50% of clinics and low implementation as those present in <50% of clinics. We compared features at university-based and community-based clinics. High areas of implementation were having an electronic health record (EHR), fully secured remote access, electronic patient notes/scheduling/billing, chronic disease management registries, and open-access scheduling. Low areas of implementation included hospital EHR with computerized physician order entry, asynchronous communication with patients, ongoing population-based QA using EHR, use of preventive registries, and practice-based research using EHR. Few differences were noted between university- and community-based residency programs. Many features of the PCMH were already established at baseline in programs participating in P(4).

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

An EHR Prototype Using Structured ISO/EN 13606 Documents to Respond to Identified Clinical Information Needs of Diabetes Specialists: A Controlled Study on Feasibility and Impact

PubMed Central

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

2012-01-01

Cross-institutional longitudinal Electronic Health Records (EHR), as introduced in Austria at the moment, increase the challenge of information overload of healthcare professionals. We developed an innovative cross-institutional EHR query prototype that offers extended query options, including searching for specific information items or sets of information items. The available query options were derived from a systematic analysis of information needs of diabetes specialists during patient encounters. The prototype operates in an IHE-XDS-based environment where ISO/EN 13606-structured documents are available. We conducted a controlled study with seven diabetes specialists to assess the feasibility and impact of this EHR query prototype on efficient retrieving of patient information to answer typical clinical questions. The controlled study showed that the specialists were quicker and more successful (measured in percentage of expected information items found) in finding patient information compared to the standard full-document search options. The participants also appreciated the extended query options. PMID:23304308

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.

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.

Exploring the sociotechnical intersection of patient safety and electronic health record implementation

PubMed Central

Meeks, Derek W; Takian, Amirhossein; Sittig, Dean F; Singh, Hardeep; Barber, Nick

2014-01-01

Objective The intersection of electronic health records (EHR) and patient safety is complex. To examine the applicability of two previously developed conceptual models comprehensively to understand safety implications of EHR implementation in the English National Health Service (NHS). Methods We conducted a secondary analysis of interview data from a 30-month longitudinal, prospective, case study-based evaluation of EHR implementation in 12 NHS hospitals. We used a framework analysis approach to apply conceptual models developed by Sittig and Singh to understand better EHR implementation and use: an eight-dimension sociotechnical model and a three-phase patient safety model (safe technology, safe use of technology, and use of technology to improve safety). Results The intersection of patient safety and EHR implementation and use was characterized by risks involving technology (hardware and software, clinical content, and human–computer interfaces), the interaction of technology with non-technological factors, and improper or unsafe use of technology. Our data support that patient safety improvement activities as well as patient safety hazards change as an organization evolves from concerns about safe EHR functionality, ensuring safe and appropriate EHR use, to using the EHR itself to provide ongoing surveillance and monitoring of patient safety. Discussion We demonstrate the face validity of two models for understanding the sociotechnical aspects of safe EHR implementation and the complex interactions of technology within a healthcare system evolving from paper to integrated EHR. Conclusions Using sociotechnical models, including those presented in this paper, may be beneficial to help stakeholders understand, synthesize, and anticipate risks at the intersection of patient safety and health information technology. PMID:24052536

Exploring the sociotechnical intersection of patient safety and electronic health record implementation.

PubMed

Meeks, Derek W; Takian, Amirhossein; Sittig, Dean F; Singh, Hardeep; Barber, Nick

2014-02-01

The intersection of electronic health records (EHR) and patient safety is complex. To examine the applicability of two previously developed conceptual models comprehensively to understand safety implications of EHR implementation in the English National Health Service (NHS). We conducted a secondary analysis of interview data from a 30-month longitudinal, prospective, case study-based evaluation of EHR implementation in 12 NHS hospitals. We used a framework analysis approach to apply conceptual models developed by Sittig and Singh to understand better EHR implementation and use: an eight-dimension sociotechnical model and a three-phase patient safety model (safe technology, safe use of technology, and use of technology to improve safety). The intersection of patient safety and EHR implementation and use was characterized by risks involving technology (hardware and software, clinical content, and human-computer interfaces), the interaction of technology with non-technological factors, and improper or unsafe use of technology. Our data support that patient safety improvement activities as well as patient safety hazards change as an organization evolves from concerns about safe EHR functionality, ensuring safe and appropriate EHR use, to using the EHR itself to provide ongoing surveillance and monitoring of patient safety. We demonstrate the face validity of two models for understanding the sociotechnical aspects of safe EHR implementation and the complex interactions of technology within a healthcare system evolving from paper to integrated EHR. Using sociotechnical models, including those presented in this paper, may be beneficial to help stakeholders understand, synthesize, and anticipate risks at the intersection of patient safety and health information technology.

Patient-generated Digital Images after Pediatric Ambulatory Surgery.

PubMed

Miller, Matthew W; Ross, Rachael K; Voight, Christina; Brouwer, Heather; Karavite, Dean J; Gerber, Jeffrey S; Grundmeier, Robert W; Coffin, Susan E

2016-07-06

To describe the use of digital images captured by parents or guardians and sent to clinicians for assessment of wounds after pediatric ambulatory surgery. Subjects with digital images of post-operative wounds were identified as part of an on-going cohort study of infections after ambulatory surgery within a large pediatric healthcare system. We performed a structured review of the electronic health record (EHR) to determine how digital images were documented in the EHR and used in clinical care. We identified 166 patients whose parent or guardian reported sending a digital image of the wound to the clinician after surgery. A corresponding digital image was located in the EHR in only 121 of these encounters. A change in clinical management was documented in 20% of these encounters, including referral for in-person evaluation of the wound and antibiotic prescription. Clinical teams have developed ad hoc workflows to use digital images to evaluate post-operative pediatric surgical patients. Because the use of digital images to support follow-up care after ambulatory surgery is likely to increase, it is important that high-quality images are captured and documented appropriately in the EHR to ensure privacy, security, and a high-level of care.

Patient-Generated Digital Images after Pediatric Ambulatory Surgery

PubMed Central

Ross, Rachael K.; Voight, Christina; Brouwer, Heather; Karavite, Dean J.; Gerber, Jeffrey S.; Grundmeier, Robert W.; Coffin, Susan E.

2016-01-01

Summary Objective To describe the use of digital images captured by parents or guardians and sent to clinicians for assessment of wounds after pediatric ambulatory surgery. Methods Subjects with digital images of post-operative wounds were identified as part of an ongoing cohort study of infections after ambulatory surgery within a large pediatric healthcare system. We performed a structured review of the electronic health record (EHR) to determine how digital images were documented in the EHR and used in clinical care. Results We identified 166 patients whose parent or guardian reported sending a digital image of the wound to the clinician after surgery. A corresponding digital image was located in the EHR in only 121 of these encounters. A change in clinical management was documented in 20% of these encounters, including referral for in-person evaluation of the wound and antibiotic prescription. Conclusion Clinical teams have developed ad hoc workflows to use digital images to evaluate post-operative pediatric surgical patients. Because the use of digital images to support follow-up care after ambulatory surgery is likely to increase, it is important that high-quality images are captured and documented appropriately in the EHR to ensure privacy, security, and a high-level of care. PMID:27452477

Perceived critical success factors of electronic health record system implementation in a dental clinic context: An organisational management perspective.

PubMed

Sidek, Yusof Haji; Martins, Jorge Tiago

2017-11-01

Electronic health records (EHR) make health care more efficient. They improve the quality of care by making patients' medical history more accessible. However, little is known about the factors contributing to the successful EHR implementation in dental clinics. This article aims to identify the perceived critical success factors of EHR system implementation in a dental clinic context. We used Grounded Theory to analyse data collected in the context of Brunei's national EHR - the Healthcare Information and Management System (Bru-HIMS). Data analysis followed the stages of open, axial and selective coding. Six perceived critical success factors emerged: usability of the system, emergent behaviours, requirements analysis, training, change management, and project organisation. The study identified a mismatch between end-users and product owner/vendor perspectives. Workflow changes were significant challenges to clinicians' confident use, particularly as the system offered limited modularity and configurability. Recommendations are made for all the parties involved in healthcare information systems implementation to manage the change process by agreeing system goals and functionalities through wider consensual debate, and participated supporting strategies realised through common commitment. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Clinician preferences for verbal communication compared to EHR documentation in the ICU

PubMed Central

Collins, S.A.; Bakken, S.; Vawdrey, D.K.; Coiera, E.; Currie, L

2011-01-01

Background Effective communication is essential to safe and efficient patient care. Additionally, many health information technology (HIT) developments, innovations, and standards aim to implement processes to improve data quality and integrity of electronic health records (EHR) for the purpose of clinical information exchange and communication. Objective We aimed to understand the current patterns and perceptions of communication of common goals in the ICU using the distributed cognition and clinical communication space theoretical frameworks. Methods We conducted a focus group and 5 interviews with ICU clinicians and observed 59.5 hours of interdisciplinary ICU morning rounds. Results Clinicians used an EHR system, which included electronic documentation and computerized provider order entry (CPOE), and paper artifacts for documentation; yet, preferred the verbal communication space as a method of information exchange because they perceived that the documentation was often not updated or efficient for information retrieval. These perceptions that the EHR is a “shift behind” may lead to a further reliance on verbal information exchange, which is a valuable clinical communication activity, yet, is subject to information loss. Conclusions Electronic documentation tools that, in real time, capture information that is currently verbally communicated may increase the effectiveness of communication. PMID:23616870

Retrospective checking of compliance with practice guidelines for acute stroke care: a novel experiment using openEHR’s Guideline Definition Language

PubMed Central

2014-01-01

Background Providing scalable clinical decision support (CDS) across institutions that use different electronic health record (EHR) systems has been a challenge for medical informatics researchers. The lack of commonly shared EHR models and terminology bindings has been recognised as a major barrier to sharing CDS content among different organisations. The openEHR Guideline Definition Language (GDL) expresses CDS content based on openEHR archetypes and can support any clinical terminologies or natural languages. Our aim was to explore in an experimental setting the practicability of GDL and its underlying archetype formalism. A further aim was to report on the artefacts produced by this new technological approach in this particular experiment. We modelled and automatically executed compliance checking rules from clinical practice guidelines for acute stroke care. Methods We extracted rules from the European clinical practice guidelines as well as from treatment contraindications for acute stroke care and represented them using GDL. Then we executed the rules retrospectively on 49 mock patient cases to check the cases’ compliance with the guidelines, and manually validated the execution results. We used openEHR archetypes, GDL rules, the openEHR reference information model, reference terminologies and the Data Archetype Definition Language. We utilised the open-sourced GDL Editor for authoring GDL rules, the international archetype repository for reusing archetypes, the open-sourced Ocean Archetype Editor for authoring or modifying archetypes and the CDS Workbench for executing GDL rules on patient data. Results We successfully represented clinical rules about 14 out of 19 contraindications for thrombolysis and other aspects of acute stroke care with 80 GDL rules. These rules are based on 14 reused international archetypes (one of which was modified), 2 newly created archetypes and 51 terminology bindings (to three terminologies). Our manual compliance checks for 49 mock patients were a complete match versus the automated compliance results. Conclusions Shareable guideline knowledge for use in automated retrospective checking of guideline compliance may be achievable using GDL. Whether the same GDL rules can be used for at-the-point-of-care CDS remains unknown. PMID:24886468

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

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.

Disease Heritability Inferred from Familial Relationships Reported in Medical Records.

PubMed

Polubriaginof, Fernanda C G; Vanguri, Rami; Quinnies, Kayla; Belbin, Gillian M; Yahi, Alexandre; Salmasian, Hojjat; Lorberbaum, Tal; Nwankwo, Victor; Li, Li; Shervey, Mark M; Glowe, Patricia; Ionita-Laza, Iuliana; Simmerling, Mary; Hripcsak, George; Bakken, Suzanne; Goldstein, David; Kiryluk, Krzysztof; Kenny, Eimear E; Dudley, Joel; Vawdrey, David K; Tatonetti, Nicholas P

2018-05-15

Heritability is essential for understanding the biological causes of disease but requires laborious patient recruitment and phenotype ascertainment. Electronic health records (EHRs) passively capture a wide range of clinically relevant data and provide a resource for studying the heritability of traits that are not typically accessible. EHRs contain next-of-kin information collected via patient emergency contact forms, but until now, these data have gone unused in research. We mined emergency contact data at three academic medical centers and identified 7.4 million familial relationships while maintaining patient privacy. Identified relationships were consistent with genetically derived relatedness. We used EHR data to compute heritability estimates for 500 disease phenotypes. Overall, estimates were consistent with the literature and between sites. Inconsistencies were indicative of limitations and opportunities unique to EHR research. These analyses provide a validation of the use of EHRs for genetics and disease research. Copyright © 2018 Elsevier Inc. All rights reserved.

Restructuring an EHR system and the Medical Markup Language (MML) standard to improve interoperability by archetype technology.

PubMed

Kobayashi, Shinji; Kume, Naoto; Yoshihara, Hiroyuki

2015-01-01

In 2001, we developed an EHR system for regional healthcare information inter-exchange and to provide individual patient data to patients. This system was adopted in three regions in Japan. We also developed a Medical Markup Language (MML) standard for inter- and intra-hospital communications. The system was built on a legacy platform, however, and had not been appropriately maintained or updated to meet clinical requirements. To improve future maintenance costs, we reconstructed the EHR system using archetype technology on the Ruby on Rails platform, and generated MML equivalent forms from archetypes. The system was deployed as a cloud-based system for preliminary use as a regional EHR. The system now has the capability to catch up with new requirements, maintaining semantic interoperability with archetype technology. It is also more flexible than the legacy EHR system.

Ethics and the electronic health record in dental school clinics.

PubMed

Cederberg, Robert A; Valenza, John A

2012-05-01

Electronic health records (EHRs) are a major development in the practice of dentistry, and dental schools and dental curricula have benefitted from this technology. Patient data entry, storage, retrieval, transmission, and archiving have been streamlined, and the potential for teledentistry and improvement in epidemiological research is beginning to be realized. However, maintaining patient health information in an electronic form has also changed the environment in dental education, setting up potential ethical dilemmas for students and faculty members. The purpose of this article is to explore some of the ethical issues related to EHRs, the advantages and concerns related to the use of computers in the dental operatory, the impact of the EHR on the doctor-patient relationship, the introduction of web-based EHRs, the link between technology and ethics, and potential solutions for the management of ethical concerns related to EHRs in dental schools.

Dental care providers' and patients' perceptions of the effect of health information technology in the dental care setting.

PubMed

Asan, Onur; Ye, Zhan; Acharya, Amit

2013-09-01

The use of electronic health records (EHRs) in dental care and their effect on dental care provider-patient interaction have not been studied sufficiently. The authors conducted a study to explore dental care providers' interactions with EHRs during patient visits, how these interactions influence dental care provider-patient communication, and the providers' and patients' perception of EHR use in the dental clinic setting during patient visits. The authors collected survey and interview data from patients and providers at three dental clinics in a health care system. The authors used qualitative and quantitative methods to analyze data obtained from patients and dental care providers. The provider survey results showed significant differences in perceptions of EHR use in patient visits across dental care provider groups (dentists, dental hygienists and dental assistants). Patient survey results indicated that some patients experienced a certain level of frustration and distraction because of providers' use of EHRs during the visit. The provider survey results indicated that there are different perceptions across provider groups about EHRs and the effect of computer use on communication with patients. Dental assistants generally reported more negative effects on communication with patients owing to computer use. Interview results also indicated that dental care providers may not feel comfortable interacting with the EHR without having any verbal or eye contact with patients during the patient's dental visit. A new design for dental operatories and locations of computer screens within the operatories should be undertaken to prevent negative nonverbal communication such as loss of eye contact or forcing the provider and patient to sit back to back, as well as to enhance patient education and information sharing.

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records.

PubMed

Peissig, Peggy L; Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries.

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

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.

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

Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application

PubMed Central

Schwei, Kelsey M; Kadolph, Christopher; Finamore, Joseph; Cancel, Efrain; McCarty, Catherine A; Okorie, Asha; Thomas, Kate L; Allen Pacheco, Jennifer; Pathak, Jyotishman; Ellis, Stephen B; Denny, Joshua C; Rasmussen, Luke V; Tromp, Gerard; Williams, Marc S; Vrabec, Tamara R; Brilliant, Murray H

2017-01-01

Background The capture and integration of structured ophthalmologic data into electronic health records (EHRs) has historically been a challenge. However, the importance of this activity for patient care and research is critical. Objective The purpose of this study was to develop a prototype of a context-driven dynamic extensible markup language (XML) ophthalmologic data capture application for research and clinical care that could be easily integrated into an EHR system. Methods Stakeholders in the medical, research, and informatics fields were interviewed and surveyed to determine data and system requirements for ophthalmologic data capture. On the basis of these requirements, an ophthalmology data capture application was developed to collect and store discrete data elements with important graphical information. Results The context-driven data entry application supports several features, including ink-over drawing capability for documenting eye abnormalities, context-based Web controls that guide data entry based on preestablished dependencies, and an adaptable database or XML schema that stores Web form specifications and allows for immediate changes in form layout or content. The application utilizes Web services to enable data integration with a variety of EHRs for retrieval and storage of patient data. Conclusions This paper describes the development process used to create a context-driven dynamic XML data capture application for optometry and ophthalmology. The list of ophthalmologic data elements identified as important for care and research can be used as a baseline list for future ophthalmologic data collection activities. PMID:28903894

Ubiquitous-Severance Hospital Project: Implementation and Results

PubMed Central

Chang, Bung-Chul; Kim, Young-A; Kim, Jee Hea; Jung, Hae Kyung; Kang, Eun Hae; Kang, Hee Suk; Lee, Hyung Il; Kim, Yong Ook; Yoo, Sun Kook; Sunwoo, Ilnam; An, Seo Yong; Jeong, Hye Jeong

2010-01-01

Objectives The purpose of this study was to review an implementation of u-Severance information system with focus on electronic hospital records (EHR) and to suggest future improvements. Methods Clinical Data Repository (CDR) of u-Severance involved implementing electronic medical records (EMR) as the basis of EHR and the management of individual health records. EHR were implemented with service enhancements extending to the clinical decision support system (CDSS) and expanding the knowledge base for research with a repository for clinical data and medical care information. Results The EMR system of Yonsei University Health Systems (YUHS) consists of HP integrity superdome servers using MS SQL as a database management system and MS Windows as its operating system. Conclusions YUHS is a high-performing medical institution with regards to efficient management and customer satisfaction; however, after 5 years of implementation of u-Severance system, several limitations with regards to expandability and security have been identified. PMID:21818425

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.

Ubiquitous-severance hospital project: implementation and results.

PubMed

Chang, Bung-Chul; Kim, Nam-Hyun; Kim, Young-A; Kim, Jee Hea; Jung, Hae Kyung; Kang, Eun Hae; Kang, Hee Suk; Lee, Hyung Il; Kim, Yong Ook; Yoo, Sun Kook; Sunwoo, Ilnam; An, Seo Yong; Jeong, Hye Jeong

2010-03-01

The purpose of this study was to review an implementation of u-Severance information system with focus on electronic hospital records (EHR) and to suggest future improvements. Clinical Data Repository (CDR) of u-Severance involved implementing electronic medical records (EMR) as the basis of EHR and the management of individual health records. EHR were implemented with service enhancements extending to the clinical decision support system (CDSS) and expanding the knowledge base for research with a repository for clinical data and medical care information. The EMR system of Yonsei University Health Systems (YUHS) consists of HP integrity superdome servers using MS SQL as a database management system and MS Windows as its operating system. YUHS is a high-performing medical institution with regards to efficient management and customer satisfaction; however, after 5 years of implementation of u-Severance system, several limitations with regards to expandability and security have been identified.

Patient Electronic Health Records as a Means to Approach Genetic Research in Gastroenterology

PubMed Central

Ananthakrishnan, Ashwin N; Lieberman, David

2015-01-01

Electronic health records (EHR) are being increasingly utilized and form a unique source of extensive data gathered during routine clinical care. Through use of codified and free text concepts identified using clinical informatics tools, disease labels can be assigned with a high degree of accuracy. Analysis linking such EHR-assigned disease labels to a biospecimen repository has demonstrated that genetic associations identified in prospective cohorts can be replicated with adequate statistical power, and novel phenotypic associations identified. In addition, genetic discovery research can be performed utilizing clinical, laboratory, and procedure data obtained during care. Challenges with such research include the need to tackle variability in quality and quantity of EHR data and importance of maintaining patient privacy and data security. With appropriate safeguards, this novel and emerging field of research offers considerable promise and potential to further scientific research in gastroenterology efficiently, cost-effectively, and with engagement of patients and communities. PMID:26073373

Interoperability of Electronic Health Records: A Physician-Driven Redesign.

PubMed

Miller, Holly; Johns, Lucy

2018-01-01

PURPOSE: Electronic health records (EHRs), now used by hundreds of thousands of providers and encouraged by federal policy, have the potential to improve quality and decrease costs in health care. But interoperability, although technically feasible among different EHR systems, is the weak link in the chain of logic. Interoperability is inhibited by poor understanding, by suboptimal implementation, and at times by a disinclination to dilute market share or patient base on the part of vendors or providers, respectively. The intent of this project has been to develop a series of practicable recommendations that, if followed by EHR vendors and users, can promote and enhance interoperability, helping EHRs reach their potential. METHODOLOGY: A group of 11 physicians, one nurse, and one health policy consultant, practicing from California to Massachusetts, has developed a document titled "Feature and Function Recommendations To Optimize Clinician Usability of Direct Interoperability To Enhance Patient Care" that offers recommendations from the clinician point of view. This report introduces some of these recommendations and suggests their implications for policy and the "virtualization" of EHRs. CONCLUSION: Widespread adoption of even a few of these recommendations by designers and vendors would enable a major advance toward the "Triple Aim" of improving the patient experience, improving the health of populations, and reducing per capita costs.

Claims-based studies of oral glucose-lowering medications can achieve balance in critical clinical variables only observed in electronic health records.

PubMed

Patorno, Elisabetta; Gopalakrishnan, Chandrasekar; Franklin, Jessica M; Brodovicz, Kimberly G; Masso-Gonzalez, Elvira; Bartels, Dorothee B; Liu, Jun; Schneeweiss, Sebastian

2018-04-01

To evaluate the extent to which balance in unmeasured characteristics of patients with type 2 diabetes (T2DM) was achieved in claims data, by comparing against more detailed information from linked electronic health records (EHR) data. Within a large US commercial insurance database and using a cohort design, we identified patients with T2DM initiating linagliptin or a comparator agent within class (ie, another dipeptidyl peptidase-4 inhibitor) or outside class (ie, pioglitazone or a sulphonylurea) between May 2011 and December 2012. We focused on comparators used at a similar stage of diabetes to linagliptin. For each comparison, 1:1 propensity score (PS) matching was used to balance >100 baseline claims-based characteristics, including proxies of diabetes severity and duration. Additional clinical data from EHR were available for a subset of patients. We assessed representativeness of the claims-EHR-linked subset, evaluated the balance of claims- and EHR-based covariates before and after PS-matching via standardized differences (SDs), and quantified the potential bias associated with observed imbalances. From a claims-based study population of 166 613 patients with T2DM, 7219 (4.3%) patients were linked to their EHR data. Claims-based characteristics in the EHR-linked and EHR-unlinked patients were similar (SD < 0.1), confirming the representativeness of the EHR-linked subset. The balance of claims-based and EHR-based patient characteristics appeared to be reasonable before PS-matching and generally improved in the PS-matched population, to be SD < 0.1 for most patient characteristics and SD < 0.2 for select laboratory results and body mass index categories, which was not large enough to cause meaningful confounding. In the context of pharmacoepidemiological research on diabetes therapy, choosing appropriate comparison groups paired with a new-user design and 1:1 PS matching on many proxies of diabetes severity and duration improves balance in covariates typically unmeasured in administrative claims datasets, to the extent that residual confounding is unlikely. © 2017 John Wiley & Sons Ltd.

Fine-grained Database Field Search Using Attribute-Based Encryption for E-Healthcare Clouds.

PubMed

Guo, Cheng; Zhuang, Ruhan; Jie, Yingmo; Ren, Yizhi; Wu, Ting; Choo, Kim-Kwang Raymond

2016-11-01

An effectively designed e-healthcare system can significantly enhance the quality of access and experience of healthcare users, including facilitating medical and healthcare providers in ensuring a smooth delivery of services. Ensuring the security of patients' electronic health records (EHRs) in the e-healthcare system is an active research area. EHRs may be outsourced to a third-party, such as a community healthcare cloud service provider for storage due to cost-saving measures. Generally, encrypting the EHRs when they are stored in the system (i.e. data-at-rest) or prior to outsourcing the data is used to ensure data confidentiality. Searchable encryption (SE) scheme is a promising technique that can ensure the protection of private information without compromising on performance. In this paper, we propose a novel framework for controlling access to EHRs stored in semi-trusted cloud servers (e.g. a private cloud or a community cloud). To achieve fine-grained access control for EHRs, we leverage the ciphertext-policy attribute-based encryption (CP-ABE) technique to encrypt tables published by hospitals, including patients' EHRs, and the table is stored in the database with the primary key being the patient's unique identity. Our framework can enable different users with different privileges to search on different database fields. Differ from previous attempts to secure outsourcing of data, we emphasize the control of the searches of the fields within the database. We demonstrate the utility of the scheme by evaluating the scheme using datasets from the University of California, Irvine.

Digitally enabled patients, professionals and providers: making the case for an electronic health record in mental health services.

PubMed

Richardson, Jonathan; McDonald, Joe

2016-10-01

The move to a digital health service may improve some components of health systems: information, communication and documentation of care. This article gives a brief definition and history of what is meant by an electronic health record (EHR). There is some evidence of benefits in a number of areas, including legibility, accuracy and the secondary use of information, but there is a need for further research, which may need to use different methodologies to analyse the impact an EHR has on patients, professionals and providers.

Usability Testing of a Complex Clinical Decision Support Tool in the Emergency Department: Lessons Learned.

PubMed

Press, Anne; McCullagh, Lauren; Khan, Sundas; Schachter, Andy; Pardo, Salvatore; McGinn, Thomas

2015-09-10

As the electronic health record (EHR) becomes the preferred documentation tool across medical practices, health care organizations are pushing for clinical decision support systems (CDSS) to help bring clinical decision support (CDS) tools to the forefront of patient-physician interactions. A CDSS is integrated into the EHR and allows physicians to easily utilize CDS tools. However, often CDSS are integrated into the EHR without an initial phase of usability testing, resulting in poor adoption rates. Usability testing is important because it evaluates a CDSS by testing it on actual users. This paper outlines the usability phase of a study, which will test the impact of integration of the Wells CDSS for pulmonary embolism (PE) diagnosis into a large urban emergency department, where workflow is often chaotic and high stakes decisions are frequently made. We hypothesize that conducting usability testing prior to integration of the Wells score into an emergency room EHR will result in increased adoption rates by physicians. The objective of the study was to conduct usability testing for the integration of the Wells clinical prediction rule into a tertiary care center's emergency department EHR. We conducted usability testing of a CDS tool in the emergency department EHR. The CDS tool consisted of the Wells rule for PE in the form of a calculator and was triggered off computed tomography (CT) orders or patients' chief complaint. The study was conducted at a tertiary hospital in Queens, New York. There were seven residents that were recruited and participated in two phases of usability testing. The usability testing employed a "think aloud" method and "near-live" clinical simulation, where care providers interacted with standardized patients enacting a clinical scenario. Both phases were audiotaped, video-taped, and had screen-capture software activated for onscreen recordings. Phase I: Data from the "think-aloud" phase of the study showed an overall positive outlook on the Wells tool in assessing a patient for a PE diagnosis. Subjects described the tool as "well-organized" and "better than clinical judgment". Changes were made to improve tool placement into the EHR to make it optimal for decision-making, auto-populating boxes, and minimizing click fatigue. Phase II: After incorporating the changes noted in Phase 1, the participants noted tool improvements. There was less toggling between screens, they had all the clinical information required to complete the tool, and were able to complete the patient visit efficiently. However, an optimal location for triggering the tool remained controversial. This study successfully combined "think-aloud" protocol analysis with "near-live" clinical simulations in a usability evaluation of a CDS tool that will be implemented into the emergency room environment. Both methods proved useful in the assessment of the CDS tool and allowed us to refine tool usability and workflow.

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

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.

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.

Real World Data in Adaptive Biomedical Innovation: A Framework for Generating Evidence Fit for Decision-Making.

PubMed

Schneeweiss, S; Eichler, H-G; Garcia-Altes, A; Chinn, C; Eggimann, A-V; Garner, S; Goettsch, W; Lim, R; Löbker, W; Martin, D; Müller, T; Park, B J; Platt, R; Priddy, S; Ruhl, M; Spooner, A; Vannieuwenhuyse, B; Willke, R J

2016-12-01

Analyses of healthcare databases (claims, electronic health records [EHRs]) are useful supplements to clinical trials for generating evidence on the effectiveness, harm, use, and value of medical products in routine care. A constant stream of data from the routine operation of modern healthcare systems, which can be analyzed in rapid cycles, enables incremental evidence development to support accelerated and appropriate access to innovative medicines. Evidentiary needs by regulators, Health Technology Assessment, payers, clinicians, and patients after marketing authorization comprise (1) monitoring of medication performance in routine care, including the materialized effectiveness, harm, and value; (2) identifying new patient strata with added value or unacceptable harms; and (3) monitoring targeted utilization. Adaptive biomedical innovation (ABI) with rapid cycle database analytics is successfully enabled if evidence is meaningful, valid, expedited, and transparent. These principles will bring rigor and credibility to current efforts to increase research efficiency while upholding evidentiary standards required for effective decision-making in healthcare. © 2016 American Society for Clinical Pharmacology and Therapeutics.

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.

A qualitative study of Swedes' opinions about shared electronic health records.

PubMed

Lehnbom, Elin C; McLachlan, Andrew J; Brien, Jo-anne E

2013-01-01

European countries are world-leading in the development and implementation of e-Health. In Sweden, all primary healthcare centres and most hospitals use digital records. Some regions use the same software which allows for clinical information to be shared (regionally shared EHRs), but there is a movement towards making all EHRs inter-operable to allow for a National Patient Summary (NPS). The aim of this study was to explore the opinions of Swedish consumers and health professionals about shared EHRs and the NPS. Semi-structered phone interviews were conducted with consumers and health professionals. The majority of interviewed health professionals were currently using regionally shared EHRs. In their experience, having access to regionally shared EHRs facilitated a holistic patient approach, assisted in patient follow-up, and reduced inappropriate (over)prescribing. Consumers had a poor level of knowledge about shared EHRs and the NPS. Unlike health professionals, consumers perceived a NPS to be of great value. The findings indicate that there was a discrepancy between health professionals and consumers' knowledge of, and the perceived need for, a NPS.

A thematic review and a policy-analysis agenda of Electronic Health Records in the Greek National Health System.

PubMed

Emmanouilidou, Maria; Burke, Maria

2013-01-01

The increasing pressure to improve healthcare outcomes and reduce costs is driving the current agenda of governments at worldwide level and calls for a fundamental reform of the status quo of health systems. This is especially the case with the Greek NHS (National Health System), a system in continuous crisis, and with the recent ongoing financial turbulence under intensive scrutiny. Technological innovations and Electronic Health Records (EHR) in particular, are recognised as key enablers in mitigating the existing burdens of healthcare. As a result, EHR is considered a core component in technology-driven reform processes. Nonetheless, the successful implementation and adoption of EHR proves to be a challenging task due to a mixture of technological, organisational and political issues. Drawing upon experiences within the European Union (EU) healthcare setting and the Greek NHS the paper proposes a conceptual framework as a policy-analysis agenda for EHR interventions in Greece. While the context of discussion is Greece, the paper aims to also derive useful insights to healthcare policy-makers around the globe. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Dense Annotation of Free-Text Critical Care Discharge Summaries from an Indian Hospital and Associated Performance of a Clinical NLP Annotator.

PubMed

Ramanan, S V; Radhakrishna, Kedar; Waghmare, Abijeet; Raj, Tony; Nathan, Senthil P; Sreerama, Sai Madhukar; Sampath, Sriram

2016-08-01

Electronic Health Record (EHR) use in India is generally poor, and structured clinical information is mostly lacking. This work is the first attempt aimed at evaluating unstructured text mining for extracting relevant clinical information from Indian clinical records. We annotated a corpus of 250 discharge summaries from an Intensive Care Unit (ICU) in India, with markups for diseases, procedures, and lab parameters, their attributes, as well as key demographic information and administrative variables such as patient outcomes. In this process, we have constructed guidelines for an annotation scheme useful to clinicians in the Indian context. We evaluated the performance of an NLP engine, Cocoa, on a cohort of these Indian clinical records. We have produced an annotated corpus of roughly 90 thousand words, which to our knowledge is the first tagged clinical corpus from India. Cocoa was evaluated on a test corpus of 50 documents. The overlap F-scores across the major categories, namely disease/symptoms, procedures, laboratory parameters and outcomes, are 0.856, 0.834, 0.961 and 0.872 respectively. These results are competitive with results from recent shared tasks based on US records. The annotated corpus and associated results from the Cocoa engine indicate that unstructured text mining is a viable method for cohort analysis in the Indian clinical context, where structured EHR records are largely absent.

Impact of an electronic health record operating room management system in ophthalmology on documentation time, surgical volume, and staffing.

PubMed

Sanders, David S; Read-Brown, Sarah; Tu, Daniel C; Lambert, William E; Choi, Dongseok; Almario, Bella M; Yackel, Thomas R; Brown, Anna S; Chiang, Michael F

2014-05-01

Although electronic health record (EHR) systems have potential benefits, such as improved safety and quality of care, most ophthalmology practices in the United States have not adopted these systems. Concerns persist regarding potential negative impacts on clinical workflow. In particular, the impact of EHR operating room (OR) management systems on clinical efficiency in the ophthalmic surgery setting is unknown. To determine the impact of an EHR OR management system on intraoperative nursing documentation time, surgical volume, and staffing requirements. For documentation time and circulating nurses per procedure, a prospective cohort design was used between January 10, 2012, and January 10, 2013. For surgical volume and overall staffing requirements, a case series design was used between January 29, 2011, and January 28, 2013. This study involved ophthalmic OR nurses (n = 13) and surgeons (n = 25) at an academic medical center. Electronic health record OR management system implementation. (1) Documentation time (percentage of operating time documenting [POTD], absolute documentation time in minutes), (2) surgical volume (procedures/time), and (3) staffing requirements (full-time equivalents, circulating nurses/procedure). Outcomes were measured during a baseline period when paper documentation was used and during the early (first 3 months) and late (4-12 months) periods after EHR implementation. There was a worsening in total POTD in the early EHR period (83%) vs paper baseline (41%) (P < .001). This improved to baseline levels by the late EHR period (46%, P = .28), although POTD in the cataract group remained worse than at baseline (64%, P < .001). There was a worsening in absolute mean documentation time in the early EHR period (16.7 minutes) vs paper baseline (7.5 minutes) (P < .001). This improved in the late EHR period (9.2 minutes) but remained worse than in the paper baseline (P < .001). While cataract procedures required more circulating nurses in the early EHR (mean, 1.9 nurses/procedure) and late EHR (mean, 1.5 nurses/procedure) periods than in the paper baseline (mean, 1.0 nurses/procedure) (P < .001), overall staffing requirements and surgical volume were not significantly different between the periods. Electronic health record OR management system implementation was associated with worsening of intraoperative nursing documentation time especially in shorter procedures. However, it is possible to implement an EHR OR management system without serious negative impacts on surgical volume and staffing requirements.

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.

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.

Intelligent Mortality Reporting with FHIR

PubMed Central

Hoffman, Ryan A.; Wu, Hang; Venugopalan, Janani; Braun, Paula; Wang, May D.

2017-01-01

One pressing need in the area of public health is timely, accurate, and complete reporting of deaths and the conditions leading up to them. Fast Healthcare Interoperability Resources (FHIR) is a new HL7 interoperability standard for electronic health record (EHR), while Sustainable Medical Applications and Reusable Technologies (SMART)-on-FHIR enables third-party app development that can work “out of the box”. This research demonstrates the feasibility of developing SMART-on-FHIR applications to enable medical professionals to perform timely and accurate death reporting within multiple different jurisdictions of US. We explored how the information on a standard certificate of death can be mapped to resources defined in the FHIR standard (DSTU2). We also demonstrated analytics for potentially improving the accuracy and completeness of mortality reporting data. PMID:28804791

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.

EHR based Genetic Testing Knowledge Base (iGTKB) Development

PubMed Central

2015-01-01

Background The gap between a large growing number of genetic tests and a suboptimal clinical workflow of incorporating these tests into regular clinical practice poses barriers to effective reliance on advanced genetic technologies to improve quality of healthcare. A promising solution to fill this gap is to develop an intelligent genetic test recommendation system that not only can provide a comprehensive view of genetic tests as education resources, but also can recommend the most appropriate genetic tests to patients based on clinical evidence. In this study, we developed an EHR based Genetic Testing Knowledge Base for Individualized Medicine (iGTKB). Methods We extracted genetic testing information and patient medical records from EHR systems at Mayo Clinic. Clinical features have been semi-automatically annotated from the clinical notes by applying a Natural Language Processing (NLP) tool, MedTagger suite. To prioritize clinical features for each genetic test, we compared odds ratio across four population groups. Genetic tests, genetic disorders and clinical features with their odds ratios have been applied to establish iGTKB, which is to be integrated into the Genetic Testing Ontology (GTO). Results Overall, there are five genetic tests operated with sample size greater than 100 in 2013 at Mayo Clinic. A total of 1,450 patients who was tested by one of the five genetic tests have been selected. We assembled 243 clinical features from the Human Phenotype Ontology (HPO) for these five genetic tests. There are 60 clinical features with at least one mention in clinical notes of patients taking the test. Twenty-eight clinical features with high odds ratio (greater than 1) have been selected as dominant features and deposited into iGTKB with their associated information about genetic tests and genetic disorders. Conclusions In this study, we developed an EHR based genetic testing knowledge base, iGTKB. iGTKB will be integrated into the GTO by providing relevant clinical evidence, and ultimately to support development of genetic testing recommendation system, iGenetics. PMID:26606281

EHR based Genetic Testing Knowledge Base (iGTKB) Development.

PubMed

Zhu, Qian; Liu, Hongfang; Chute, Christopher G; Ferber, Matthew

2015-01-01

The gap between a large growing number of genetic tests and a suboptimal clinical workflow of incorporating these tests into regular clinical practice poses barriers to effective reliance on advanced genetic technologies to improve quality of healthcare. A promising solution to fill this gap is to develop an intelligent genetic test recommendation system that not only can provide a comprehensive view of genetic tests as education resources, but also can recommend the most appropriate genetic tests to patients based on clinical evidence. In this study, we developed an EHR based Genetic Testing Knowledge Base for Individualized Medicine (iGTKB). We extracted genetic testing information and patient medical records from EHR systems at Mayo Clinic. Clinical features have been semi-automatically annotated from the clinical notes by applying a Natural Language Processing (NLP) tool, MedTagger suite. To prioritize clinical features for each genetic test, we compared odds ratio across four population groups. Genetic tests, genetic disorders and clinical features with their odds ratios have been applied to establish iGTKB, which is to be integrated into the Genetic Testing Ontology (GTO). Overall, there are five genetic tests operated with sample size greater than 100 in 2013 at Mayo Clinic. A total of 1,450 patients who was tested by one of the five genetic tests have been selected. We assembled 243 clinical features from the Human Phenotype Ontology (HPO) for these five genetic tests. There are 60 clinical features with at least one mention in clinical notes of patients taking the test. Twenty-eight clinical features with high odds ratio (greater than 1) have been selected as dominant features and deposited into iGTKB with their associated information about genetic tests and genetic disorders. In this study, we developed an EHR based genetic testing knowledge base, iGTKB. iGTKB will be integrated into the GTO by providing relevant clinical evidence, and ultimately to support development of genetic testing recommendation system, iGenetics.

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

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

The value of vendor-reported ambulatory EHR benefits data.

PubMed

Thompson, Douglas; Classen, David; Garrido, Terhilda; Bisordi, Joseph; Novogoratz, Scott; Zywiak, Walt

2007-04-01

Implementation of an electronic health record is expensive and labor-intensive. For this reason, providers often seek information about possible benefits to help them decide whether to implement an EHR. Our study found that a benefits database maintained by an ambulatory clinical systems vendor provided information that is useful, but that also has limitations.

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.

Electronic health record impact on productivity and efficiency in an academic pediatric ophthalmology practice.

PubMed

Redd, Travis K; Read-Brown, Sarah; Choi, Dongseok; Yackel, Thomas R; Tu, Daniel C; Chiang, Michael F

2014-12-01

To measure the effect of electronic health record (EHR) implementation on productivity and efficiency in the pediatric ophthalmology division at an academic medical center. Four established providers were selected from the pediatric ophthalmology division at the Oregon Health & Science University Casey Eye Institute. Clinical volume was compared before and after EHR implementation for each provider. Time elapsed from chart open to completion (OTC time) and the proportion of charts completed during business hours were monitored for 3 years following implementation. Overall there was an 11% decrease in clinical volume following EHR implementation, which was not statistically significant (P = 0.18). The mean OTC time ranged from 5.5 to 28.3 hours among providers in this study, and trends over time were variable among the four providers. Forty-four percent of all charts were closed outside normal business hours (30% on weekdays, 14% on weekends). EHR implementation was associated with a negative impact on productivity and efficiency in our pediatric ophthalmology division. Copyright © 2014 American Association for Pediatric Ophthalmology and Strabismus. Published by Elsevier Inc. All rights reserved.

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

PubMed Central

Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

Objective There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. Materials and methods We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. Results An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. Discussion A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. Conclusion We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries. PMID:22319176

Computers in the examination room and the electronic health record: physicians' perceived impact on clinical encounters before and after full installation and implementation.

PubMed

Doyle, Richard J; Wang, Nina; Anthony, David; Borkan, Jeffrey; Shield, Renee R; Goldman, Roberta E

2012-10-01

We compared physicians' self-reported attitudes and behaviours regarding electronic health record (EHR) use before and after installation of computers in patient examination rooms and transition to full implementation of an EHR in a family medicine training practice to identify anticipated and observed effects these changes would have on physicians' practices and clinical encounters. We conducted two individual qualitative interviews with family physicians. The first interview was before and second interview was 8 months later after full implementation of an EHR and computer installation in the examination rooms. Data were analysed through project team discussions and subsequent coding with qualitative analysis software. At the first interviews, physicians frequently expressed concerns about the potential negative effect of the EHR on quality of care and physician-patient interaction, adequacy of their skills in EHR use and privacy and confidentiality concerns. Nevertheless, most physicians also anticipated multiple benefits, including improved accessibility of patient data and online health information. In the second interviews, physicians reported that their concerns did not persist. Many anticipated benefits were realized, appearing to facilitate collaborative physician-patient relationships. Physicians reported a greater teaching role with patients and sharing online medical information and treatment plan decisions. Before computer installation and full EHR implementation, physicians expressed concerns about the impact of computer use on patient care. After installation and implementation, however, many concerns were mitigated. Using computers in the examination rooms to document and access patients' records along with online medical information and decision-making tools appears to contribute to improved physician-patient communication and collaboration.