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Sample records for decision support systems clinical

  1. Clinical decision support systems.

    PubMed

    Beeler, Patrick Emanuel; Bates, David Westfall; Hug, Balthasar Luzius

    2014-01-01

    Clinical decision support (CDS) systems link patient data with an electronic knowledge base in order to improve decision-making and computerised physician order entry (CPOE) is a requirement to set up electronic CDS. The medical informatics literature suggests categorising CDS tools into medication dosing support, order facilitators, point-of-care alerts and reminders, relevant information display, expert systems and workflow support. To date, CDS has particularly been recognised for improving processes. CDS successfully fostered prevention of deep-vein thrombosis, improved adherence to guidelines, increased the use of vaccinations, and decreased the rate of serious medication errors. However, CDS may introduce errors, and therefore the term "e-iatrogenesis" has been proposed to address unintended consequences. At least two studies reported severe treatment delays due to CPOE and CDS. In addition, the phenomenon of "alert fatigue" - arising from a high number of CDS alerts of low clinical significance - may facilitate overriding of potentially critical notifications. The implementation of CDS needs to be carefully planned, CDS interventions should be thoroughly examined in pilot wards only, and then stepwise introduced. A crucial feature of CPOE in combination with CDS is speed, since time consumption has been found to be a major factor determining failure. In the near future, the specificity of alerts will be improved, notifications will be prioritised and offer detailed advice, customisation of CDS will play an increasing role, and finally, CDS is heading for patient-centred decision support. The most important research question remains whether CDS is able to improve patient outcomes beyond processes.

  2. Isabel, a clinical decision support system.

    PubMed

    Vardell, Emily; Moore, Mary

    2011-01-01

    A clinical decision support system (CDSS) is an interactive tool designed to assist clinicians in making decisions, such as determining a diagnosis. The Isabel Database is a CDSS featuring a clinical checklist and topic-specific knowledge components. This column contains an overview of the database, provides searching tips, and places Isabel within the context of the CDSS field. PMID:21534115

  3. Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.

    PubMed

    Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru

    2015-07-01

    Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting. PMID:26066306

  4. Semantic Interoperability in Clinical Decision Support Systems: A Systematic Review.

    PubMed

    Marco-Ruiz, Luis; Bellika, Johan Gustav

    2015-01-01

    The interoperability of Clinical Decision Support (CDS) systems with other health information systems has become one of the main limitations to their broad adoption. Semantic interoperability must be granted in order to share CDS modules across different health information systems. Currently, numerous standards for different purposes are available to enable the interoperability of CDS systems. We performed a literature review to identify and provide an overview of the available standards that enable CDS interoperability in the areas of clinical information, decision logic, terminology, and web service interfaces. PMID:26262260

  5. Clinical decision support for perioperative information management systems.

    PubMed

    Wanderer, Jonathan P; Ehrenfeld, Jesse M

    2013-12-01

    Clinical decision support (CDS) systems are being used to optimize the increasingly complex care that our health care system delivers. These systems have become increasingly important in the delivery of perioperative care for patients undergoing cardiac, thoracic, and vascular procedures. The adoption of perioperative information management systems (PIMS) has allowed these technologies to enter the operating room and support the clinical work flow of anesthesiologists and operational processes. Constructing effective CDS systems necessitates an understanding of operative work flow and technical considerations as well as achieving integration with existing information systems. In this review, we describe published examples of CDS for PIMS, including support for cardiopulmonary bypass separation physiological alarms, β-blocker guideline adherence, enhanced revenue capture for arterial line placement, and detection of hemodynamic monitoring gaps. Although these and other areas are amenable to CDS systems, the challenges of latency and data reliability represent fundamental limitations on the potential application of these tools to specific types of clinical issues. Ultimately, we expect that CDS will remain an important tool in our efforts to optimize the quality of care delivered.

  6. A Clinical Decision Support System for Breast Cancer Patients

    NASA Astrophysics Data System (ADS)

    Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.

    This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.

  7. Exploration Clinical Decision Support System: Medical Data Architecture

    NASA Technical Reports Server (NTRS)

    Lindsey, Tony; Shetye, Sandeep; Shaw, Tianna (Editor)

    2016-01-01

    The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear

  8. System-Agnostic Clinical Decision Support Services: Benefits and Challenges for Scalable Decision Support

    PubMed Central

    Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F

    2010-01-01

    System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors’ formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors’ experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems. PMID:21603281

  9. [Knowledge management system for laboratory work and clinical decision support].

    PubMed

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

    This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support.

  10. [Knowledge management system for laboratory work and clinical decision support].

    PubMed

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

    This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support

  11. Decision support for clinical laboratory capacity planning.

    PubMed

    van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M

    1995-01-01

    The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.

  12. Factors Predicting Oncology Care Providers' Behavioral Intention to Adopt Clinical Decision Support Systems

    ERIC Educational Resources Information Center

    Wolfenden, Andrew

    2012-01-01

    The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…

  13. Framework for securing personal health data in clinical decision support systems.

    PubMed

    Sandell, Protik

    2007-01-01

    If appropriate security mechanisms aren't in place, individuals and groups can get unauthorized access to personal health data residing in clinical decision support systems (CDSS). These concerns are well founded; there has been a dramatic increase in reports of security incidents. The paper provides a framework for securing personal health data in CDSS. The framework breaks down CDSS into data gathering, data management and data delivery functions. It then provides the vulnerabilities that can occur in clinical decision support activities and the measures that need to be taken to protect the data. The framework is applied to protect the confidentiality, integrity and availability of personal health data in a decision support system. Using the framework, project managers and architects can assess the potential risk of unauthorized data access in their decision support system. Moreover they can design systems and procedures to effectively secure personal health data.

  14. Knowledge bases, clinical decision support systems, and rapid learning in oncology.

    PubMed

    Yu, Peter Paul

    2015-03-01

    One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care.

  15. Mobile clinical decision support systems and applications: a literature and commercial review.

    PubMed

    Martínez-Pérez, Borja; de la Torre-Díez, Isabel; López-Coronado, Miguel; Sainz-de-Abajo, Beatriz; Robles, Montserrat; García-Gómez, Juan Miguel

    2014-01-01

    The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Ninety-two relevant papers and 192 commercial apps were found. Forty-four papers were focused only on mobile clinical decision support systems. One hundred seventy-one apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.

  16. Design and application of a generic clinical decision support system for multiscale data.

    PubMed

    Mattila, Jussi; Koikkalainen, Juha; Virkki, Arho; van Gils, Mark; Lötjönen, Jyrki

    2012-01-01

    Medical research and clinical practice are currently being redefined by the constantly increasing amounts of multiscale patient data. New methods are needed to translate them into knowledge that is applicable in healthcare. Multiscale modeling has emerged as a way to describe systems that are the source of experimental data. Usually, a multiscale model is built by combining distinct models of several scales, integrating, e.g., genetic, molecular, structural, and neuropsychological models into a composite representation. We present a novel generic clinical decision support system, which models a patient's disease state statistically from heterogeneous multiscale data. Its goal is to aid in diagnostic work by analyzing all available patient data and highlighting the relevant information to the clinician. The system is evaluated by applying it to several medical datasets and demonstrated by implementing a novel clinical decision support tool for early prediction of Alzheimer's disease.

  17. Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

    PubMed Central

    2014-01-01

    Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health

  18. Multi-site evaluation of a clinical decision support system for radiation therapy

    NASA Astrophysics Data System (ADS)

    Deshpande, Ruchi; DeMarco, John; Kessel, Kerstin; Liu, Brent J.

    2016-03-01

    We have developed an imaging informatics based decision support system that learns from retrospective treatment plans to provide recommendations for healthy tissue sparing to prospective incoming patients. This system incorporates a model of best practices from previous cases, specific to tumor anatomy. Ultimately, our hope is to improve clinical workflow efficiency, patient outcomes and to increase clinician confidence in decision-making. The success of such a system depends greatly on the training dataset, which in this case, is the knowledge base that the data-mining algorithm employs. The size and heterogeneity of the database is essential for good performance. Since most institutions employ standard protocols and practices for treatment planning, the diversity of this database can be greatly increased by including data from different institutions. This work presents the results of incorporating cross-country, multi-institutional data into our decision support system for evaluation and testing.

  19. Integrating complex business processes for knowledge-driven clinical decision support systems.

    PubMed

    Kamaleswaran, Rishikesan; McGregor, Carolyn

    2012-01-01

    This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS. PMID:23366138

  20. Integrating complex business processes for knowledge-driven clinical decision support systems.

    PubMed

    Kamaleswaran, Rishikesan; McGregor, Carolyn

    2012-01-01

    This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

  1. The perils of meta-regression to identify clinical decision support system success factors

    PubMed Central

    Fillmore, Christopher L.; Rommel, Casey A.; Welch, Brandon M.; Zhang, Mingyuan; Kawamoto, Kensaku

    2016-01-01

    Clinical decision support interventions are typically heterogeneous in nature, making it difficult to identify why some interventions succeed while others do not. One approach to identify factors important to the success of health information systems is the use of meta-regression techniques, in which potential explanatory factors are correlated with the outcome of interest. This approach, however, can result in misleading conclusions due to several issues. In this manuscript, we present a cautionary case study in the context of clinical decision support systems to illustrate the limitations of this type of analysis. We then discuss implications and recommendations for future work aimed at identifying success factors of medical informatics interventions. In particular, we identify the need for head-to-head trials in which the importance of system features is directly evaluated in a prospective manner. PMID:25998518

  2. A shotgun wedding: business decision support meets clinical decision support.

    PubMed

    Oliveira, Jason

    2002-01-01

    By effectively closing the loop between the data, analytics, processes, and methods supporting business and clinical decision making, a healthcare organization closes the loop between its knowledge generation activities and its actions at the bedside: knowledge guiding actions, actions generating knowledge.

  3. A web-based intensive care clinical decision support system: from design to evaluation.

    PubMed

    Ozel, Deniz; Bilge, Ugur; Zayim, Nese; Cengiz, Melike

    2013-03-01

    The aim of this study is to develop and evaluate a web-based clinical decision support system (CDSS) containing clinical guidelines and protocols that will support intensive care unit (ICU) providers in making decisions more effectively and quickly. First, a survey was carried out with 38 physicians in order to determine their preferences, needs and concerns regarding decision support tools. After the survey, guidelines were prepared by a group of specialists in ICU, and a medical informatician converted the guidelines into algorithm forms. Ten CDSS were developed using the algorithms, and placed onto the Intensive Care Decision Support Website (ICDSW). In order to evaluation of the website, 15 physicians were asked to answer 10 questions in 10 different scenarios first using a paper-based approach, then with ICDSW. When the answers were analyzed, it was found that the answers given by using ICDSW were significantly better than the paper-based approach (p <  0.001). However, there was no significant difference in terms of the time needed to answer the questions (p =  0.138). The usability score of the website was 85.6 ±  8.89. The study demonstrated the successful implementation of an ICDSW within intensive care units.

  4. A secure communication using cascade chaotic computing systems on clinical decision support.

    PubMed

    Koksal, Ahmet Sertol; Er, Orhan; Evirgen, Hayrettin; Yumusak, Nejat

    2016-06-01

    Clinical decision support systems (C-DSS) provide supportive tools to the expert for the determination of the disease. Today, many of the support systems, which have been developed for a better and more accurate diagnosis, have reached a dynamic structure due to artificial intelligence techniques. However, in cases when important diagnosis studies should be performed in secret, a secure communication system is required. In this study, secure communication of a DSS is examined through a developed double layer chaotic communication system. The developed communication system consists of four main parts: random number generator, cascade chaotic calculation layer, PCM, and logical mixer layers. Thanks to this system, important patient data created by DSS will be conveyed to the center through a secure communication line.

  5. Mobile Clinical Decision Support Systems in Our Hands - Great Potential but also a Concern.

    PubMed

    Masic, Izet; Begic, Edin

    2016-01-01

    Due to the powerful computer resources as well as the availability of today's mobile devices, a special field of mobile systems for clinical decision support in medicine has been developed. The benefits of these applications (systems) are: availability of necessary hardware (mobile phones, tablets and phablets are widespread, and can be purchased at a relatively affordable price), availability of mobile applications (free or for a "small" amount of money) and also mobile applications are tailored for easy use and save time of clinicians in their daily work. In these systems lies a huge potential, and certainly a great economic benefit, so this issue must be approached multidisciplinary. PMID:27350467

  6. Mobile Clinical Decision Support Systems in Our Hands - Great Potential but also a Concern.

    PubMed

    Masic, Izet; Begic, Edin

    2016-01-01

    Due to the powerful computer resources as well as the availability of today's mobile devices, a special field of mobile systems for clinical decision support in medicine has been developed. The benefits of these applications (systems) are: availability of necessary hardware (mobile phones, tablets and phablets are widespread, and can be purchased at a relatively affordable price), availability of mobile applications (free or for a "small" amount of money) and also mobile applications are tailored for easy use and save time of clinicians in their daily work. In these systems lies a huge potential, and certainly a great economic benefit, so this issue must be approached multidisciplinary.

  7. The NIAID Division of AIDS enterprise information system: integrated decision support for global clinical research programs

    PubMed Central

    Gupta, Nitin; Varghese, Suresh; Virkar, Hemant

    2011-01-01

    The National Institute of Allergy and Infectious Diseases (NIAID) Division of AIDS (DAIDS) Enterprise Information System (DAIDS-ES) is a web-based system that supports NIAID in the scientific, strategic, and tactical management of its global clinical research programs for HIV/AIDS vaccines, prevention, and therapeutics. Different from most commercial clinical trials information systems, which are typically protocol-driven, the DAIDS-ES was built to exchange information with those types of systems and integrate it in ways that help scientific program directors lead the research effort and keep pace with the complex and ever-changing global HIV/AIDS pandemic. Whereas commercially available clinical trials support systems are not usually disease-focused, DAIDS-ES was specifically designed to capture and incorporate unique scientific, demographic, and logistical aspects of HIV/AIDS treatment, prevention, and vaccine research in order to provide a rich source of information to guide informed decision-making. Sharing data across its internal components and with external systems, using defined vocabularies, open standards and flexible interfaces, the DAIDS-ES enables NIAID, its global collaborators and stakeholders, access to timely, quality information about NIAID-supported clinical trials which is utilized to: (1) analyze the research portfolio, assess capacity, identify opportunities, and avoid redundancies; (2) help support study safety, quality, ethics, and regulatory compliance; (3) conduct evidence-based policy analysis and business process re-engineering for improved efficiency. This report summarizes how the DAIDS-ES was conceptualized, how it differs from typical clinical trial support systems, the rationale for key design choices, and examples of how it is being used to advance the efficiency and effectiveness of NIAID's HIV/AIDS clinical research programs. PMID:21816958

  8. The NIAID Division of AIDS enterprise information system: integrated decision support for global clinical research programs.

    PubMed

    Kagan, Jonathan M; Gupta, Nitin; Varghese, Suresh; Virkar, Hemant

    2011-12-01

    The National Institute of Allergy and Infectious Diseases (NIAID) Division of AIDS (DAIDS) Enterprise Information System (DAIDS-ES) is a web-based system that supports NIAID in the scientific, strategic, and tactical management of its global clinical research programs for HIV/AIDS vaccines, prevention, and therapeutics. Different from most commercial clinical trials information systems, which are typically protocol-driven, the DAIDS-ES was built to exchange information with those types of systems and integrate it in ways that help scientific program directors lead the research effort and keep pace with the complex and ever-changing global HIV/AIDS pandemic. Whereas commercially available clinical trials support systems are not usually disease-focused, DAIDS-ES was specifically designed to capture and incorporate unique scientific, demographic, and logistical aspects of HIV/AIDS treatment, prevention, and vaccine research in order to provide a rich source of information to guide informed decision-making. Sharing data across its internal components and with external systems, using defined vocabularies, open standards and flexible interfaces, the DAIDS-ES enables NIAID, its global collaborators and stakeholders, access to timely, quality information about NIAID-supported clinical trials which is utilized to: (1) analyze the research portfolio, assess capacity, identify opportunities, and avoid redundancies; (2) help support study safety, quality, ethics, and regulatory compliance; (3) conduct evidence-based policy analysis and business process re-engineering for improved efficiency. This report summarizes how the DAIDS-ES was conceptualized, how it differs from typical clinical trial support systems, the rationale for key design choices, and examples of how it is being used to advance the efficiency and effectiveness of NIAID's HIV/AIDS clinical research programs.

  9. Decision support systems for clinical radiological practice — towards the next generation

    PubMed Central

    Stivaros, S M; Gledson, A; Nenadic, G; Zeng, X-J; Keane, J; Jackson, A

    2010-01-01

    The huge amount of information that needs to be assimilated in order to keep pace with the continued advances in modern medical practice can form an insurmountable obstacle to the individual clinician. Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted the need for computer systems to provide the radiological community with support for academic as well as clinical/translational applications. This article provides an overview of the underlying design and functionality of radiological decision support systems with examples tracing the development and evolution of such systems over the past 40 years. More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. Additionally, we have identified particular failings in our current methodologies for data dissemination within the medical domain that must be overcome if the next generation of decision support systems is to be implemented successfully. PMID:20965900

  10. Decision support systems for clinical radiological practice -- towards the next generation.

    PubMed

    Stivaros, S M; Gledson, A; Nenadic, G; Zeng, X-J; Keane, J; Jackson, A

    2010-11-01

    The huge amount of information that needs to be assimilated in order to keep pace with the continued advances in modern medical practice can form an insurmountable obstacle to the individual clinician. Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted the need for computer systems to provide the radiological community with support for academic as well as clinical/translational applications. This article provides an overview of the underlying design and functionality of radiological decision support systems with examples tracing the development and evolution of such systems over the past 40 years. More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. Additionally, we have identified particular failings in our current methodologies for data dissemination within the medical domain that must be overcome if the next generation of decision support systems is to be implemented successfully.

  11. Constructing Clinical Decision Support Systems for Adverse Drug Event Prevention: A Knowledge-based Approach.

    PubMed

    Koutkias, Vassilis; Kilintzis, Vassilis; Stalidis, George; Lazou, Katerina; Collyda, Chrysa; Chazard, Emmanuel; McNair, Peter; Beuscart, Regis; Maglaveras, Nicos

    2010-11-13

    A knowledge-based approach is proposed that is employed for the construction of a framework suitable for the management and effective use of knowledge on Adverse Drug Event (ADE) prevention. The framework has as its core part a Knowledge Base (KB) comprised of rule-based knowledge sources, that is accompanied by the necessary inference and query mechanisms to provide healthcare professionals and patients with decision support services in clinical practice, in terms of alerts and recommendations on preventable ADEs. The relevant Knowledge Based System (KBS) is developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the foundations of the framework, its knowledge model and KB structure, as well as recent progress as regards the population of the KB, the implementation of the KBS, and results on the KBS verification in decision support operation.

  12. Test Case Selection in Pre-Deployment Testing of Complex Clinical Decision Support Systems

    PubMed Central

    Tso, Geoffrey J.; Yuen, Kaeli; Martins, Susana; Tu, Samson W.; Ashcraft, Michael; Heidenreich, Paul; Hoffman, Brian B.; Goldstein, Mary K.

    2016-01-01

    Clinical decision support (CDS) systems with complex logic are being developed. Ensuring the quality of CDS is imperative, but there is no consensus on testing standards. We tested ATHENA-HTN CDS after encoding updated hypertension guidelines into the system. A logic flow and a complexity analysis of the encoding were performed to guide testing. 100 test cases were selected to test the major pathways in the CDS logic flow, and the effectiveness of the testing was analyzed. The encoding contained 26 decision points and 3120 possible output combinations. The 100 cases selected tested all of the major pathways in the logic, but only 1% of the possible output combinations. Test case selection is one of the most challenging aspects in CDS testing and has a major impact on testing coverage. A test selection strategy should take into account the complexity of the system, identification of major logic pathways, and available resources. PMID:27570678

  13. Test Case Selection in Pre-Deployment Testing of Complex Clinical Decision Support Systems.

    PubMed

    Tso, Geoffrey J; Yuen, Kaeli; Martins, Susana; Tu, Samson W; Ashcraft, Michael; Heidenreich, Paul; Hoffman, Brian B; Goldstein, Mary K

    2016-01-01

    Clinical decision support (CDS) systems with complex logic are being developed. Ensuring the quality of CDS is imperative, but there is no consensus on testing standards. We tested ATHENA-HTN CDS after encoding updated hypertension guidelines into the system. A logic flow and a complexity analysis of the encoding were performed to guide testing. 100 test cases were selected to test the major pathways in the CDS logic flow, and the effectiveness of the testing was analyzed. The encoding contained 26 decision points and 3120 possible output combinations. The 100 cases selected tested all of the major pathways in the logic, but only 1% of the possible output combinations. Test case selection is one of the most challenging aspects in CDS testing and has a major impact on testing coverage. A test selection strategy should take into account the complexity of the system, identification of major logic pathways, and available resources. PMID:27570678

  14. Computerized Clinical Decision Support: Contributions from 2014

    PubMed Central

    Koutkias, V.

    2015-01-01

    Summary Objective To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Results Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. Conclusions As health information technologies spread more and more meaningfully, CDSSs are improving to answer users’ needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term. PMID:26293858

  15. An extended SQL for temporal data management in clinical decision-support systems.

    PubMed

    Das, A K; Tu, S W; Purcell, G P; Musen, M A

    1992-01-01

    We are developing a database implementation to support temporal data management for the T-HELPER physician workstation, an advice system for protocol-based care of patients who have HIV disease. To understand the requirements for the temporal database, we have analyzed the types of temporal predicates found in clinical-trial protocols. We extend the standard relational data model in three ways to support these querying requirements. First, we incorporate timestamps into the two-dimensional relational table to store the temporal dimension of both instant- and interval-based data. Second, we develop a set of operations on timepoints and intervals to manipulate timestamped data. Third, we modify the relational query language SQL so that its underlying algebra supports the specified operations on timestamps in relational tables. We show that our temporal extension to SQL meets the temporal data-management needs of protocol-directed decision support.

  16. [Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

    PubMed

    Wu, Dehua

    2016-01-01

    The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian. PMID:26946752

  17. [Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

    PubMed

    Wu, Dehua

    2016-01-01

    The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.

  18. A clinical decision support system with an integrated EMR for diagnosis of peripheral neuropathy.

    PubMed

    Kunhimangalam, Reeda; Ovallath, Sujith; Joseph, Paul K

    2014-04-01

    The prevalence of peripheral neuropathy in general population is ever increasing. The diagnosis and classification of peripheral neuropathies is often difficult as it involves careful clinical and electro-diagnostic examination by an expert neurologist. In developing countries a large percentage of the disease remains undiagnosed due to lack of adequate number of experts. In this study a novel clinical decision support system has been developed using a fuzzy expert system. The study was done to provide a solution to the demand of systems that can improve health care by accurate diagnosis in limited time, in the absence of specialists. It employs a graphical user interface and a fuzzy logic controller with rule viewer for identification of the type of peripheral neuropathy. An integrated medical records database is also developed for the storage and retrieval of the data. The system consists of 24 input fields, which includes the clinical values of the diagnostic test and the clinical symptoms. The output field is the disease diagnosis, whether it is Motor (Demyelinating/Axonopathy) neuropathy, sensory (Demyelinating/Axonopathy) neuropathy, mixed type or a normal case. The results obtained were compared with the expert's opinion and the system showed 93.27 % accuracy. The study aims at showing that Fuzzy Expert Systems may prove useful in providing diagnostic and predictive medical opinions. It enables the clinicians to arrive at a better diagnosis as it keeps the expert knowledge in an intelligent system to be used efficiently and effectively.

  19. Enabling cross-platform clinical decision support through Web-based decision support in commercial electronic health record systems: proposal and evaluation of initial prototype implementations.

    PubMed

    Zhang, Mingyuan; Velasco, Ferdinand T; Musser, R Clayton; Kawamoto, Kensaku

    2013-01-01

    Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale.

  20. Enabling cross-platform clinical decision support through Web-based decision support in commercial electronic health record systems: proposal and evaluation of initial prototype implementations.

    PubMed

    Zhang, Mingyuan; Velasco, Ferdinand T; Musser, R Clayton; Kawamoto, Kensaku

    2013-01-01

    Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426

  1. Decision Support Systems in Libraries.

    ERIC Educational Resources Information Center

    Heindel, Allan; Napier, H. Albert

    Following a review of the contributions of computers and managerial science/operations research to the management of libraries, this paper introduces the concept of decision support systems. DSS, a blending of these techniques, can lead to more effective decisions by library managers. A case study of the utilization of a DSS in the budgeting…

  2. Development and impact of computerised decision support systems for clinical management of depression: A systematic review.

    PubMed

    Triñanes, Yolanda; Atienza, Gerardo; Louro-González, Arturo; de-las-Heras-Liñero, Elena; Alvarez-Ariza, María; Palao, Diego J

    2015-01-01

    One of the proposals for improving clinical practice is to introduce computerised decision support systems (CDSS) and integrate these with electronic medical records. Accordingly, this study sought to systematically review evidence on the effectiveness of CDSS in the management of depression. A search was performed in Medline, EMBASE and PsycInfo, in order to do this. The quality of quantitative studies was assessed using the SIGN method, and qualitative studies using the CASPe checklist. Seven studies were identified (3 randomised clinical trials, 3 non-randomised trials, and one qualitative study). The CDSS assessed incorporated content drawn from guidelines and other evidence-based products. In general, the CDSS had a positive impact on different aspects, such as the screening and diagnosis, treatment, improvement in depressive symptoms and quality of life, and referral of patients. The use of CDSS could thus serve to optimise care of depression in various scenarios by providing recommendations based on the best evidence available and facilitating decision-making in clinical practice. PMID:25500093

  3. Development and impact of computerised decision support systems for clinical management of depression: A systematic review.

    PubMed

    Triñanes, Yolanda; Atienza, Gerardo; Louro-González, Arturo; de-las-Heras-Liñero, Elena; Alvarez-Ariza, María; Palao, Diego J

    2015-01-01

    One of the proposals for improving clinical practice is to introduce computerised decision support systems (CDSS) and integrate these with electronic medical records. Accordingly, this study sought to systematically review evidence on the effectiveness of CDSS in the management of depression. A search was performed in Medline, EMBASE and PsycInfo, in order to do this. The quality of quantitative studies was assessed using the SIGN method, and qualitative studies using the CASPe checklist. Seven studies were identified (3 randomised clinical trials, 3 non-randomised trials, and one qualitative study). The CDSS assessed incorporated content drawn from guidelines and other evidence-based products. In general, the CDSS had a positive impact on different aspects, such as the screening and diagnosis, treatment, improvement in depressive symptoms and quality of life, and referral of patients. The use of CDSS could thus serve to optimise care of depression in various scenarios by providing recommendations based on the best evidence available and facilitating decision-making in clinical practice.

  4. Integration and Evaluation of Clinical Decision Support Systems for Diagnosis Idopathics Pulmonary Fibrosis (IPF)

    PubMed Central

    Chae, Youngmoon; Jeon, Sungwan

    2010-01-01

    Objectives The purpose of this study was to develop clinical decision support systems (CDSS) that are integrated with hospital information systems for the differential diagnosis of idiopathic pulmonary fibrosis (IPF). Methods The integrated CDSS were validated and evaluated by physicians. Knowledge modeling for diagnosing IPF was performed by knowledge working groups, composed of radiologists and respiratory specialists. In order to develop the model for CDSS diagnosis, the clinical cases were collected from 290 cases from Seoul National University Hospital and Sevrance Hospital of Yonsei University. For the evaluation of integrated CDSS, interviews were conducted with respiratory specialists and radiologist 2 weeks after applying CDSSs in clinical settings. The CDSS was integrated with the computer vision system (CVS) and diffuse parenchymal lung diseases (DPLD), CDSS developed in our previous project. Results Eighteen cases diagnosed as IPF were applied to the collection of diagnostic knowledge and the refined knowledge, the former diagnosed 1 case (6%) and the latter diagnosed 14 cases (78%). Therefore, the refined knowledge performed better than collected knowledge. The validation results of integrated CDSSs showed that 81 cases (74.3%) were diagnosed correctly. Conclusions There were 109 cases of IPF diagnosed and initiated on treatment. The significance of this study is in developing integrated CDSS with PACS by acquiring and redefining the knowledge needed for IPF diagnosis. In addition, it is significant for the integration of CDSS to verification and clinical evaluation. PMID:21818445

  5. Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine.

    PubMed

    Castaneda, Christian; Nalley, Kip; Mannion, Ciaran; Bhattacharyya, Pritish; Blake, Patrick; Pecora, Andrew; Goy, Andre; Suh, K Stephen

    2015-01-01

    , and logistical concerns. Ensuring data security and protection of patient rights while simultaneously facilitating standardization is paramount to maintaining public support. The capabilities of supercomputing need to be applied strategically. A standardized, methodological implementation must be applied to developed artificial intelligence systems with the ability to integrate data and information into clinically relevant knowledge. Ultimately, the integration of bioinformatics and clinical data in a clinical decision support system promises precision medicine and cost effective and personalized patient care.

  6. The Utilization of a Clinical Decision Support System to Manage Adult Type 2 Diabetes: A Correlational Study

    ERIC Educational Resources Information Center

    Faught, I. Charie

    2012-01-01

    While the Institute of Medicine (2001) has promoted health information technology to improve the process of care such as compliance with clinical practice guidelines and quicker access to clinical information, diagnostic tests, and treatment results, very little was known about how a clinical decision support system can contribute to diabetes…

  7. Evaluating acceptance and user experience of a guideline-based clinical decision support system execution platform.

    PubMed

    Buenestado, David; Elorz, Javier; Pérez-Yarza, Eduardo G; Iruetaguena, Ander; Segundo, Unai; Barrena, Raúl; Pikatza, Juan M

    2013-04-01

    This study aims to determine what the initial disposition of physicians towards the use of Clinical Decision Support Systems (CDSS) based on Computerised Clinical Guidelines and Protocols (CCGP) is; and whether their prolonged utilisation has a positive effect on their intention to adopt them in the future. For a period of 3 months, 8 volunteer paediatricians monitored each up to 10 asthmatic patients using two CCGPs deployed in the-GuidesMed CDSS. A Technology Acceptance Model (TAM) questionnaire was supplied to them before and after using the system. Results from both questionnaires are analysed searching for significant improvements in opinion between them. An additional survey was performed to analyse the usability of the system. It was found that initial disposition of physicians towards e-GuidesMed is good. Improvement between the pre and post iterations of the TAM questionnaire has been found to be statistically significant. Nonetheless, slightly lower values in the Compatibility and Habit variables show that participants perceive possible difficulties to integrate e-GuidesMed into their daily routine. The variable Facilitators shows the highest correlation with the Intention to Use. Usability of the system has also been rated very high and, in this regard, no fundamental flaw has been detected. Initial views towards e-GuidesMed are positive, and become reinforced after continued utilisation of the system. In order to achieve an effective implementation, it becomes essential to facilitate conditions to integrate the system into the physician's daily routine.

  8. Clinical decision support systems for brain tumor characterization using advanced magnetic resonance imaging techniques.

    PubMed

    Tsolaki, Evangelia; Kousi, Evanthia; Svolos, Patricia; Kapsalaki, Efthychia; Theodorou, Kyriaki; Kappas, Constastine; Tsougos, Ioannis

    2014-04-28

    In recent years, advanced magnetic resonance imaging (MRI) techniques, such as magnetic resonance spectroscopy, diffusion weighted imaging, diffusion tensor imaging and perfusion weighted imaging have been used in order to resolve demanding diagnostic problems such as brain tumor characterization and grading, as these techniques offer a more detailed and non-invasive evaluation of the area under study. In the last decade a great effort has been made to import and utilize intelligent systems in the so-called clinical decision support systems (CDSS) for automatic processing, classification, evaluation and representation of MRI data in order for advanced MRI techniques to become a part of the clinical routine, since the amount of data from the aforementioned techniques has gradually increased. Hence, the purpose of the current review article is two-fold. The first is to review and evaluate the progress that has been made towards the utilization of CDSS based on data from advanced MRI techniques. The second is to analyze and propose the future work that has to be done, based on the existing problems and challenges, especially taking into account the new imaging techniques and parameters that can be introduced into intelligent systems to significantly improve their diagnostic specificity and clinical application.

  9. [From library to clinical decision support systems: access of general practitioner to quality information].

    PubMed

    Fauquert, B

    2012-09-01

    Since 2003, the following tools have been implemented in Belgium for improving the access of general practioners to the EBM literature: the Digital Library for Health and the evidence-linker of the CEBAM, the portal EBMPracticeNet.be and the multidimensional electronic clinical decision support EBMeDS. The aim of this article is to show the progress achieved in the information dissemination toward the belgian general practioners, particularly the access from the electronic health record. From the literature published these last years, the opportunities cited by the users are for using EBM and the strong willingness for using these literature access in the future; the limits are the medical data coding, the irrelevance of the search results, the alerts fatigue induced by EBMeDS. The achievements done and planned for the new EBMPracticeNet guidelines portal and the EBMeDS system are explained in the aim of informing belgian healthcare professionals. These projects are claiming for lauching a participatory process in the production and dissemination of EBM information. The discussion is focused on the belgian healthcare system advantages, the solutions for a reasonable implementation of these projects and for increasing the place of an evidence-based information in the healthcare decision process. Finally the input of these projects to the continuing medical education and to the healthcare quality are discussed, in a context of multifactorial interaction healthcare design (complexity design).

  10. Thinking Processes in Social Workers' Use of a Clinical Decision Support System: A Qualitative Study

    ERIC Educational Resources Information Center

    Monnickendam, Menachem; Savaya, Riki; Waysman, Mark

    2005-01-01

    The authors examined the thinking processes in the use of a decision support system (DSS) by social workers in a human services agency to determine whether they used the system to improve their case reasoning. Information was obtained from in-depth interviews with eight social workers who used a DSS in their work and from content analysis of…

  11. icuARM-An ICU Clinical Decision Support System Using Association Rule Mining

    PubMed Central

    Chanani, Nikhil; Venugopalan, Janani; Maher, Kevin; Wang, May Dongmei

    2013-01-01

    The rapid development of biomedical monitoring technologies has enabled modern intensive care units (ICUs) to gather vast amounts of multimodal measurement data about their patients. However, processing large volumes of complex data in real-time has become a big challenge. Together with ICU physicians, we have designed and developed an ICU clinical decision support system icuARM based on associate rule mining (ARM), and a publicly available research database MIMIC-II (Multi-parameter Intelligent Monitoring in Intensive Care II) that contains more than 40,000 ICU records for 30,000+patients. icuARM is constructed with multiple association rules and an easy-to-use graphical user interface (GUI) for care providers to perform real-time data and information mining in the ICU setting. To validate icuARM, we have investigated the associations between patients' conditions such as comorbidities, demographics, and medications and their ICU outcomes such as ICU length of stay. Coagulopathy surfaced as the most dangerous co-morbidity that leads to the highest possibility (54.1%) of prolonged ICU stay. In addition, women who are older than 50 years have the highest possibility (38.8%) of prolonged ICU stay. For clinical conditions treatable with multiple drugs, icuARM suggests that medication choice can be optimized based on patient-specific characteristics. Overall, icuARM can provide valuable insights for ICU physicians to tailor a patient's treatment based on his or her clinical status in real time. PMID:27170860

  12. Cost-Effectiveness of an Electronic Medical Record Based Clinical Decision Support System

    PubMed Central

    Gilmer, Todd P; O'Connor, Patrick J; Sperl-Hillen, JoAnn M; Rush, William A; Johnson, Paul E; Amundson, Gerald H; Asche, Stephen E; Ekstrom, Heidi L

    2012-01-01

    Background and Objective Medical groups have invested billions of dollars in electronic medical records (EMRs), but few studies have examined the cost-effectiveness of EMR-based clinical decision support (CDS). This study examined the cost-effectiveness of EMR-based CDS for adults with diabetes from the perspective of the health care system. Data Sources/Setting Clinical outcome and cost data from a randomized clinical trial of EMR-based CDS were used as inputs into a diabetes simulation model. The simulation cohort included 1,092 patients with diabetes with A1c above goal at baseline. Study Design The United Kingdom Prospective Diabetes Study Outcomes Model, a validated simulation model of diabetes, was used to evaluate remaining life years, quality-adjusted life years (QALYs), and health care costs over patient lifetimes (40-year time horizon) from the health system perspective. Principal Findings Patients in the intervention group had significantly lowered A1c (0.26 percent, p = .014) relative to patients in the control arm. Intervention costs were $120 (SE = 45) per patient in the first year and $76 (SE = 45) per patient in the following years. In the base case analysis, EMR-based CDS increased lifetime QALYs by 0.04 (SE = 0.01) and increased lifetime costs by $112 (SE = 660), resulting in an incremental cost-effectiveness ratio of $3,017 per QALY. The cost-effectiveness of EMR-based CDS persisted in one-way, two-way, and probabilistic sensitivity analyses. Conclusions Widespread adoption of sophisticated EMR-based CDS has the potential to modestly improve the quality of care for patients with chronic conditions without substantially increasing costs to the health care system. PMID:22578085

  13. 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

  14. Personalizing Drug Selection Using Advanced Clinical Decision Support

    PubMed Central

    Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A.; Glauser, Tracy

    2009-01-01

    This article describes the process of developing an advanced pharmacogenetics clinical decision support at one of the United States’ leading pediatric academic medical centers. This system, called CHRISTINE, combines clinical and genetic data to identify the optimal drug therapy when treating patients with epilepsy or Attention Deficit Hyperactivity Disorder. In the discussion a description of clinical decision support systems is provided, along with an overview of neurocognitive computing and how it is applied in this setting. PMID:19898682

  15. An Automated System for Generating Situation-Specific Decision Support in Clinical Order Entry from Local Empirical Data

    ERIC Educational Resources Information Center

    Klann, Jeffrey G.

    2011-01-01

    Clinical Decision Support is one of the only aspects of health information technology that has demonstrated decreased costs and increased quality in healthcare delivery, yet it is extremely expensive and time-consuming to create, maintain, and localize. Consequently, a majority of health care systems do not utilize it, and even when it is…

  16. ClinicalAccess: a clinical decision support tool.

    PubMed

    Crowell, Karen; Vardell, Emily

    2015-01-01

    ClinicalAccess is a new clinical decision support tool that uses a question-and-answer format to mirror clinical decision-making strategies. The unique format of ClinicalAccess delivers concise, authoritative answers to more than 120,000 clinical questions. This column presents a review of the product, a sample search, and a comparison with other point-of-care search engines.

  17. The Effect of Level of Patient Acuity, Critical Care Experience, and ACLS Certification on Clinical Decision Making: Implications for Computer Decision Support Systems

    PubMed Central

    Henry, Suzanne Bakken

    1990-01-01

    This study examined the effect of patient acuity, critical care experience, and ACLS certification on clinical decision making. Each subject (N=68) completed two computerized clinical simulations. Ventricular tachycardia (VT) represented the high acuity situation and atrial flutter (AF) the lower acuity situation. Clinical decision making was measured by proficiency score, patient outcome (cure/die), and amount of data collected. In the AF simulation, proficiency scores were higher (p=.000), more dysrhythmias were cured (p<.005), and more data were collected (p=.040) than in the VT simulation. Experienced and inexperienced nurses did not differ on proficiency score, however, inexperienced nurses collected more data (p=.048) and cured fewer atrial flutter simulations (p=.04). ACLS certified nurses had higher proficiency scores (p=.033) and collected less data (p=.048). Clinical decision making on two simulations was affected by patient acuity, critical care experience, and ACLS certification. These findings have implications for the design and implementation of clinical decision support systems.

  18. Usability of clinical decision support system as a facilitator for learning the assistive technology adaptation process.

    PubMed

    Danial-Saad, Alexandra; Kuflik, Tsvi; Weiss, Patrice L Tamar; Schreuer, Naomi

    2016-01-01

    The aim of this study was to evaluate the usability of Ontology Supported Computerized Assistive Technology Recommender (OSCAR), a Clinical Decision Support System (CDSS) for the assistive technology adaptation process, its impact on learning the matching process, and to determine the relationship between its usability and learnability. Two groups of expert and novice clinicians (total, n = 26) took part in this study. Each group filled out system usability scale (SUS) to evaluate OSCAR's usability. The novice group completed a learning questionnaire to assess OSCAR's effect on their ability to learn the matching process. Both groups rated OSCAR's usability as "very good", (M [SUS] = 80.7, SD = 11.6, median = 83.7) by the novices, and (M [SUS] = 81.2, SD = 6.8, median = 81.2) by the experts. The Mann-Whitney results indicated that no significant differences were found between the expert and novice groups in terms of OSCAR's usability. A significant positive correlation existed between the usability of OSCAR and the ability to learn the adaptation process (rs = 0.46, p = 0.04). Usability is an important factor in the acceptance of a system. The successful application of user-centered design principles during the development of OSCAR may serve as a case study that models the significant elements to be considered, theoretically and practically in developing other systems. Implications for Rehabilitation Creating a CDSS with a focus on its usability is an important factor for its acceptance by its users. Successful usability outcomes can impact the learning process of the subject matter in general, and the AT prescription process in particular. The successful application of User-Centered Design principles during the development of OSCAR may serve as a case study that models the significant elements to be considered, theoretically and practically. The study emphasizes the importance of close collaboration between the developers and

  19. User Centered Clinical Decision Support Tools

    PubMed Central

    Sofianou, A.; Kannry, J.; Mann, D.M.; McGinn, T.G.

    2014-01-01

    Summary Background Dissemination and adoption of clinical decision support (CDS) tools is a major initiative of the Affordable Care Act’s Meaningful Use program. Adoption of CDS tools is multipronged with personal, organizational, and clinical settings factoring into the successful utilization rates. Specifically, the diffusion of innovation theory implies that ‘early adopters’ are more inclined to use CDS tools and younger physicians tend to be ranked in this category. Objective This study examined the differences in adoption of CDS tools across providers’ training level. Participants From November 2010 to 2011, 168 residents and attendings from an academic medical institution were enrolled into a randomized controlled trial. Intervention The intervention arm had access to the CDS tool through the electronic health record (EHR) system during strep and pneumonia patient visits. Main Measures The EHR system recorded details on how intervention arm interacted with the CDS tool including acceptance of the initial CDS alert, completion of risk-score calculators and the signing of medication order sets. Using the EHR data, the study performed bivariate tests and general estimating equation (GEE) modeling to examine the differences in adoption of the CDS tool across residents and attendings. Key Results The completion rates of the CDS calculator and medication order sets were higher amongst first year residents compared to all other training levels. Attendings were the less likely to accept the initial step of the CDS tool (29.3%) or complete the medication order sets (22.4%) that guided their prescription decisions, resulting in attendings ordering more antibiotics (37.1%) during an CDS encounter compared to residents. Conclusion There is variation in adoption of CDS tools across training levels. Attendings tended to accept the tool less but ordered more medications. CDS tools should be tailored to clinicians’ training levels. PMID:25589914

  20. Cost-Effectiveness of Clinical Decision Support System in Improving Maternal Health Care in Ghana

    PubMed Central

    Dalaba, Maxwell Ayindenaba; Akweongo, Patricia; Aborigo, Raymond Akawire; Saronga, Happiness Pius; Williams, John; Blank, Antje; Kaltschmidt, Jens; Sauerborn, Rainer; Loukanova, Svetla

    2015-01-01

    Objective This paper investigated the cost-effectiveness of a computer-assisted Clinical Decision Support System (CDSS) in the identification of maternal complications in Ghana. Methods A cost-effectiveness analysis was performed in a before- and after-intervention study. Analysis was conducted from the provider’s perspective. The intervention area was the Kassena- Nankana district where computer-assisted CDSS was used by midwives in maternal care in six selected health centres. Six selected health centers in the Builsa district served as the non-intervention group, where the normal Ghana Health Service activities were being carried out. Results Computer-assisted CDSS increased the detection of pregnancy complications during antenatal care (ANC) in the intervention health centres (before-intervention= 9 /1,000 ANC attendance; after-intervention= 12/1,000 ANC attendance; P-value=0.010). In the intervention health centres, there was a decrease in the number of complications during labour by 1.1%, though the difference was not statistically significant (before-intervention =107/1,000 labour clients; after-intervention= 96/1,000 labour clients; P-value=0.305). Also, at the intervention health centres, the average cost per pregnancy complication detected during ANC (cost –effectiveness ratio) decreased from US$17,017.58 (before-intervention) to US$15,207.5 (after-intervention). Incremental cost –effectiveness ratio (ICER) was estimated at US$1,142. Considering only additional costs (cost of computer-assisted CDSS), cost per pregnancy complication detected was US$285. Conclusions Computer –assisted CDSS has the potential to identify complications during pregnancy and marginal reduction in labour complications. Implementing computer-assisted CDSS is more costly but more effective in the detection of pregnancy complications compared to routine maternal care, hence making the decision to implement CDSS very complex. Policy makers should however be guided by whether

  1. Decision Technology Systems: A Vehicle to Consolidate Decision Making Support.

    ERIC Educational Resources Information Center

    Forgionne, Guisseppi A.

    1991-01-01

    Discussion of management decision making and the support needed to manage successfully highlights a Decision Technology System (DTS) that integrates other information systems. Topics discussed include computer information systems (CISs); knowledge gateways; the decision-making process; decision support systems (DSS); expert systems; and facility…

  2. Evaluation of User Interface and Workflow Design of a Bedside Nursing Clinical Decision Support System

    PubMed Central

    Yuan, Michael Juntao; Finley, George Mike; Mills, Christy; Johnson, Ron Kim

    2013-01-01

    Background Clinical decision support systems (CDSS) are important tools to improve health care outcomes and reduce preventable medical adverse events. However, the effectiveness and success of CDSS depend on their implementation context and usability in complex health care settings. As a result, usability design and validation, especially in real world clinical settings, are crucial aspects of successful CDSS implementations. Objective Our objective was to develop a novel CDSS to help frontline nurses better manage critical symptom changes in hospitalized patients, hence reducing preventable failure to rescue cases. A robust user interface and implementation strategy that fit into existing workflows was key for the success of the CDSS. Methods Guided by a formal usability evaluation framework, UFuRT (user, function, representation, and task analysis), we developed a high-level specification of the product that captures key usability requirements and is flexible to implement. We interviewed users of the proposed CDSS to identify requirements, listed functions, and operations the system must perform. We then designed visual and workflow representations of the product to perform the operations. The user interface and workflow design were evaluated via heuristic and end user performance evaluation. The heuristic evaluation was done after the first prototype, and its results were incorporated into the product before the end user evaluation was conducted. First, we recruited 4 evaluators with strong domain expertise to study the initial prototype. Heuristic violations were coded and rated for severity. Second, after development of the system, we assembled a panel of nurses, consisting of 3 licensed vocational nurses and 7 registered nurses, to evaluate the user interface and workflow via simulated use cases. We recorded whether each session was successfully completed and its completion time. Each nurse was asked to use the National Aeronautics and Space Administration

  3. Clinical information system services and capabilities desired for scalable, standards-based, service-oriented decision support: consensus assessment of the Health Level 7 clinical decision support Work Group.

    PubMed

    Kawamoto, Kensaku; Jacobs, Jason; Welch, Brandon M; Huser, Vojtech; Paterno, Marilyn D; Del Fiol, Guilherme; Shields, David; Strasberg, Howard R; Haug, Peter J; Liu, Zhijing; Jenders, Robert A; Rowed, David W; Chertcoff, Daryl; Fehre, Karsten; Adlassnig, Klaus-Peter; Curtis, A Clayton

    2012-01-01

    A standards-based, service-oriented architecture for clinical decision support (CDS) has the potential to significantly enhance CDS scalability and robustness. To enable such a CDS architecture, the Health Level 7 CDS Work Group reviewed the literature, hosted multi-stakeholder discussions, and consulted domain experts to identify and prioritize the services and capabilities required from clinical information systems (CISs) to enable service-oriented CDS. In addition, relevant available standards were identified. Through this process, ten CIS services and eight CIS capabilities were identified as being important for enabling scalable, service-oriented CDS. In particular, through a survey of 46 domain experts, five services and capabilities were identified as being especially critical: 1) the use of standard information models and terminologies; 2) the ability to leverage a Decision Support Service (DSS); 3) support for a clinical data query service; 4) support for an event subscription and notification service; and 5) support for a user communication service.

  4. Clinical Information System Services and Capabilities Desired for Scalable, Standards-Based, Service-oriented Decision Support: Consensus Assessment of the Health Level 7 Clinical Decision Support Work Group

    PubMed Central

    Kawamoto, Kensaku; Jacobs, Jason; Welch, Brandon M.; Huser, Vojtech; Paterno, Marilyn D.; Del Fiol, Guilherme; Shields, David; Strasberg, Howard R.; Haug, Peter J.; Liu, Zhijing; Jenders, Robert A.; Rowed, David W.; Chertcoff, Daryl; Fehre, Karsten; Adlassnig, Klaus-Peter; Curtis, A. Clayton

    2012-01-01

    A standards-based, service-oriented architecture for clinical decision support (CDS) has the potential to significantly enhance CDS scalability and robustness. To enable such a CDS architecture, the Health Level 7 CDS Work Group reviewed the literature, hosted multi-stakeholder discussions, and consulted domain experts to identify and prioritize the services and capabilities required from clinical information systems (CISs) to enable service-oriented CDS. In addition, relevant available standards were identified. Through this process, ten CIS services and eight CIS capabilities were identified as being important for enabling scalable, service-oriented CDS. In particular, through a survey of 46 domain experts, five services and capabilities were identified as being especially critical: 1) the use of standard information models and terminologies; 2) the ability to leverage a Decision Support Service (DSS); 3) support for a clinical data query service; 4) support for an event subscription and notification service; and 5) support for a user communication service. PMID:23304315

  5. Clinical Decision Support Tools: The Evolution of a Revolution.

    PubMed

    Mould, D R; D'Haens, G; Upton, R N

    2016-04-01

    Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug monitoring. In the treatment of inflammatory bowel disease patients with infliximab, dashboards may reduce therapeutic failures and treatment costs. The history and future development of modern Bayesian dashboard systems is described. PMID:26785109

  6. Design and Development of a Sharable Clinical Decision Support System Based on a Semantic Web Service Framework.

    PubMed

    Zhang, Yi-Fan; Gou, Ling; Tian, Yu; Li, Tian-Chang; Zhang, Mao; Li, Jing-Song

    2016-05-01

    Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain.

  7. Design and Development of a Sharable Clinical Decision Support System Based on a Semantic Web Service Framework.

    PubMed

    Zhang, Yi-Fan; Gou, Ling; Tian, Yu; Li, Tian-Chang; Zhang, Mao; Li, Jing-Song

    2016-05-01

    Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain. PMID:27002818

  8. AALIM: a cardiac clinical decision support system powered by advanced multi-modal analytics.

    PubMed

    Amir, Arnon; Beymer, David; Grace, Julia; Greenspan, Hayit; Gruhl, Daniel; Hobbs, Allen; Pohl, Kilian; Syeda-Mahmood, Tanveer; Terdiman, Joseph; Wang, Fei

    2010-01-01

    Modern Electronic Medical Record (EMR) systems often integrate large amounts of data from multiple disparate sources. To do so, EMR systems must align the data to create consistency between these sources. The data should also be presented in a manner that allows a clinician to quickly understand the complete condition and history of a patient's health. We develop the AALIM system to address these issues using advanced multimodal analytics. First, it extracts and computes multiple features and cues from the patient records and medical tests. This additional metadata facilitates more accurate alignment of the various modalities, enables consistency check and empowers a clear, concise presentation of the patient's complete health information. The system further provides a multimodal search for similar cases within the EMR system, and derives related conditions and drugs information from them. We applied our approach to cardiac data from a major medical care organization and found that it produced results with sufficient quality to assist the clinician making appropriate clinical decisions.

  9. The process of development of a prioritization tool for a clinical decision support build within a computerized provider order entry system: Experiences from St Luke's Health System.

    PubMed

    Wolf, Matthew; Miller, Suzanne; DeJong, Doug; House, John A; Dirks, Carl; Beasley, Brent

    2016-09-01

    To establish a process for the development of a prioritization tool for a clinical decision support build within a computerized provider order entry system and concurrently to prioritize alerts for Saint Luke's Health System. The process of prioritizing clinical decision support alerts included (a) consensus sessions to establish a prioritization process and identify clinical decision support alerts through a modified Delphi process and (b) a clinical decision support survey to validate the results. All members of our health system's physician quality organization, Saint Luke's Care as well as clinicians, administrators, and pharmacy staff throughout Saint Luke's Health System, were invited to participate in this confidential survey. The consensus sessions yielded a prioritization process through alert contextualization and associated Likert-type scales. Utilizing this process, the clinical decision support survey polled the opinions of 850 clinicians with a 64.7 percent response rate. Three of the top rated alerts were approved for the pre-implementation build at Saint Luke's Health System: Acute Myocardial Infarction Core Measure Sets, Deep Vein Thrombosis Prophylaxis within 4 h, and Criteria for Sepsis. This study establishes a process for developing a prioritization tool for a clinical decision support build within a computerized provider order entry system that may be applicable to similar institutions. PMID:25814483

  10. Strategic Decision Making and Group Decision Support Systems.

    ERIC Educational Resources Information Center

    McGrath, Michael Robert

    1986-01-01

    Institutional strategic decisions require the participation of every individual with a significant stake in the solution, and group decision support systems are being developed to respond to the political and consensual problems of collective decision-making. (MSE)

  11. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker-researcher partnership systematic review

    PubMed Central

    2010-01-01

    Background Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit. Methods The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system. Results Data will be summarized using descriptive summary

  12. Comparative outcome studies of clinical decision support software: limitations to the practice of evidence-based system acquisition.

    PubMed

    Dhiman, Gaurav Jay; Amber, Kyle T; Goodman, Kenneth W

    2015-04-01

    Clinical decision support systems (CDSSs) assist clinicians with patient diagnosis and treatment. However, inadequate attention has been paid to the process of selecting and buying systems. The diversity of CDSSs, coupled with research obstacles, marketplace limitations, and legal impediments, has thwarted comparative outcome studies and reduced the availability of reliable information and advice for purchasers. We review these limitations and recommend several comparative studies, which were conducted in phases; studies conducted in phases and focused on limited outcomes of safety, efficacy, and implementation in varied clinical settings. Additionally, we recommend the increased availability of guidance tools to assist purchasers with evidence-based purchases. Transparency is necessary in purchasers' reporting of system defects and vendors' disclosure of marketing conflicts of interest to support methodologically sound studies. Taken together, these measures can foster the evolution of evidence-based tools that, in turn, will enable and empower system purchasers to make wise choices and improve the care of patients. PMID:25665704

  13. Computerised clinical decision support for suspected PE.

    PubMed

    Jiménez, David; Resano, Santiago; Otero, Remedios; Jurkojc, Carolina; Portillo, Ana Karina; Ruiz-Artacho, Pedro; Corres, Jesús; Vicente, Agustina; den Exter, Paul L; Huisman, Menno V; Moores, Lisa; Yusen, Roger D

    2015-09-01

    This study aimed to determine the effect of an evidence-based clinical decision support (CDS) algorithm on the use and yield of CT pulmonary angiography (CTPA) and on outcomes of patients evaluated in the emergency department (ED) for suspected PE. The study included 1363 consecutive patients evaluated for suspected PE in an ED during 12 months before and 12 months after initiation of CDS use. Introduction of CDS was associated with decreased CTPA use (55% vs 49%; absolute difference (AD), 6.3%; 95% CI 1.0% to 11.6%; p=0.02). The use of CDS was associated with fewer symptomatic venous thromboembolic events during follow-up in patients with an initial negative diagnostic evaluation for PE (0.7% vs 3.2%; AD 2.5%; 95% CI 0.9% to 4.6%; p<0.01).

  14. Decision Support Systems: The Need, The Challenge.

    ERIC Educational Resources Information Center

    Roberts, Michael M.

    1982-01-01

    The evolution of decision support systems (DSS) has enabled computer and information technology to assist the management process of decision making. Decision support systems are designed to look forward in time, to forecast outcomes of uncertain events. A 70-item bibliography is included. (MLW)

  15. Anatomy of a Decision Support System.

    ERIC Educational Resources Information Center

    Chachra, Vinod; Heterick, Robert C.

    1982-01-01

    The decision support system (DSS) environment, the functional requirements of a DSS, and the architectural requirements of the computer systems and communications network necessary to support a DSS are discussed. Changes in the computing environment that are necessary to implement decision support systems are suggested. (Author/MLW)

  16. Virtual medical record implementation for enhancing clinical decision support.

    PubMed

    Gomoi, Valentin-Sergiu; Dragu, Daniel; Stoicu-Tivadar, Vasile

    2012-01-01

    Development of clinical decision support systems (CDS) is a process which highly depends on the local databases, this resulting in low interoperability. To increase the interoperability of CDS a standard representation of clinical information is needed. The paper suggests a CDS architecture which integrates several HL7 standards and the new vMR (virtual Medical Record). The clinical information for the CDS systems (the vMR) is represented with Topic Maps technology. Beside the implementation of the vMR, the architecture integrates: a Data Manager, an interface, a decision making system (based on Egadss), a retrieving data module. Conclusions are issued.

  17. Using SNOMED CT Expression Constraints to Bridge the Gap Between Clinical Decision-Support Systems and Electronic Health Records.

    PubMed

    Martínez-Salvador, Begoña; Marcos, Mar; Mañas, Alejandro; Maldonado, José Alberto; Robles, Monserrat

    2016-01-01

    Clinical decision-support systems (CDSSs) should be able to interact with the electronic health record (EHR) to obtain the patient data they require. A recent solution for the interoperability of CDSSs and EHR systems consists in the use of a mediated schema which provides a unified view of their two schemas. The use of such a mediated schema requires the definition of a mapping between this schema and the EHR one. In this paper we investigate the use of the SNOMED CT Expression Constraint Language to characterize these mappings. PMID:27577434

  18. A Clinical Decision Support System for Integrating Tuberculosis and HIV Care in Kenya: A Human-Centered Design Approach

    PubMed Central

    Catalani, Caricia; Green, Eric; Owiti, Philip; Keny, Aggrey; Diero, Lameck; Yeung, Ada; Israelski, Dennis; Biondich, Paul

    2014-01-01

    With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1) understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2) develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3) implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context. PMID:25170939

  19. A clinical decision support system for integrating tuberculosis and HIV care in Kenya: a human-centered design approach.

    PubMed

    Catalani, Caricia; Green, Eric; Owiti, Philip; Keny, Aggrey; Diero, Lameck; Yeung, Ada; Israelski, Dennis; Biondich, Paul

    2014-01-01

    With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1) understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2) develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3) implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context.

  20. Construction of a Clinical Decision Support System for Undergoing Surgery Based on Domain Ontology and Rules Reasoning

    PubMed Central

    Bau, Cho-Tsan; Huang, Chung-Yi

    2014-01-01

    Abstract Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. Results: The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. Conclusions: The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia. PMID:24730353

  1. Decision Support Systems for Academic Administration.

    ERIC Educational Resources Information Center

    Moore, Laurence J.; Greenwood, Allen G.

    1984-01-01

    The history and features of Decision Support Systems (DSS) and use of the approach by academic administrators are discussed. The objective of DSS is to involve the manager/decision maker in the decision-analysis process while simultaneously relieving that person of the burden of developing and performing detailed analysis. DSS represents a…

  2. A Clinical Decision Support System for Femoral Peripheral Arterial Disease Treatment

    PubMed Central

    Yurtkuran, Alkın; Tok, Mustafa

    2013-01-01

    One of the major challenges of providing reliable healthcare services is to diagnose and treat diseases in an accurate and timely manner. Recently, many researchers have successfully used artificial neural networks as a diagnostic assessment tool. In this study, the validation of such an assessment tool has been developed for treatment of the femoral peripheral arterial disease using a radial basis function neural network (RBFNN). A data set for training the RBFNN has been prepared by analyzing records of patients who had been treated by the thoracic and cardiovascular surgery clinic of a university hospital. The data set includes 186 patient records having 16 characteristic features associated with a binary treatment decision, namely, being a medical or a surgical one. K-means clustering algorithm has been used to determine the parameters of radial basis functions and the number of hidden nodes of the RBFNN is determined experimentally. For performance evaluation, the proposed RBFNN was compared to three different multilayer perceptron models having Pareto optimal hidden layer combinations using various performance indicators. Results of comparison indicate that the RBFNN can be used as an effective assessment tool for femoral peripheral arterial disease treatment. PMID:24382983

  3. What can Natural Language Processing do for Clinical Decision Support?

    PubMed Central

    Demner-Fushman, Dina; Chapman, Wendy W.; McDonald, Clement J.

    2009-01-01

    Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural Language Processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed. PMID:19683066

  4. A multiresolution clinical decision support system based on fractal model design for classification of histological brain tumours.

    PubMed

    Al-Kadi, Omar S

    2015-04-01

    Tissue texture is known to exhibit a heterogeneous or non-stationary nature; therefore using a single resolution approach for optimum classification might not suffice. A clinical decision support system that exploits the subbands' textural fractal characteristics for best bases selection of meningioma brain histopathological image classification is proposed. Each subband is analysed using its fractal dimension instead of energy, which has the advantage of being less sensitive to image intensity and abrupt changes in tissue texture. The most significant subband that best identifies texture discontinuities will be chosen for further decomposition, and its fractal characteristics would represent the optimal feature vector for classification. The performance was tested using the support vector machine (SVM), Bayesian and k-nearest neighbour (kNN) classifiers and a leave-one-patient-out method was employed for validation. Our method outperformed the classical energy based selection approaches, achieving for SVM, Bayesian and kNN classifiers an overall classification accuracy of 94.12%, 92.50% and 79.70%, as compared to 86.31%, 83.19% and 51.63% for the co-occurrence matrix, and 76.01%, 73.50% and 50.69% for the energy texture signatures; respectively. These results indicate the potential usefulness as a decision support system that could complement radiologists' diagnostic capability to discriminate higher order statistical textural information; for which it would be otherwise difficult via ordinary human vision.

  5. Integration of heterogeneous clinical decision support systems and their knowledge sets: feasibility study with Drug-Drug Interaction alerts.

    PubMed

    Kam, Hye Jin; Kim, Jeong Ah; Cho, InSook; Kim, Yoon; Park, Rae Woong

    2011-01-01

    There exist limitations in both commercial and in-house clinical decision support systems (CDSSs) and issues related to the integration of different knowledge sources and CDSSs. We chose Standard-based Shareable Active Guideline Environment (SAGE) as a new architecture with knowledge integration and a centralized knowledge base which includes authoring/management functions and independent CDSS, and applied it to Drug-Drug Interaction (DDI) CDSS. The aim of this study was to evaluate the feasibility of the newly integrated DDI alerting CDSS into a real world hospital information system involving construction of an integrated CDSS derived from two heterogeneous systems and their knowledge sets. The proposed CDSS was successfully implemented and compensated for the weaknesses of the old CDSS from knowledge integration and management, and its applicability in actual situations was verified. Although the DDI CDSS was constructed as an example case, the new CDS architecture might prove applicable to areas of CDSSs.

  6. DocBot: a novel clinical decision support algorithm.

    PubMed

    Ninh, Andrew Q

    2014-01-01

    DocBot is a web-based clinical decision support system (CDSS) that uses patient interaction and electronic health record analytics to assist medical practitioners with decision making. It consists of two distinct HTML interfaces: a preclinical form wherein a patient inputs symptomatic and demographic information, and an interface wherein a medical practitioner views patient information and analysis. DocBot comprises an improved software architecture that uses patient information, electronic health records, and etiologically relevant binary decision questions (stored in a knowledgebase) to provide medical practitioners with information including, but not limited to medical assessments, treatment plans, and specialist referrals.

  7. A Hyperknowledge Framework of Decision Support Systems.

    ERIC Educational Resources Information Center

    Chang, Ai-Mei; And Others

    1994-01-01

    Presents a hyperknowledge framework of decision support systems (DSS). This framework formalizes specifics about system functionality, representation of knowledge, navigation of the knowledge system, and user-interface traits as elements of a DSS environment that conforms closely to human cognitive processes in decision making. (Contains 52…

  8. A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study

    PubMed Central

    Lyons, Jason J; Greene, Tracy L; Haley, James M

    2015-01-01

    Objective To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. Design Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients’ designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. Setting Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. Participants Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. Main outcome measure ‘Suspected infection’ was the established gold standard to assess clinical decision support clinimetric performance. Results A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying ‘suspected infection’ as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. Conclusion A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis. PMID:26688744

  9. An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems.

    PubMed

    Sáez, Carlos; Bresó, Adrián; Vicente, Javier; Robles, Montserrat; García-Gómez, Juan Miguel

    2013-03-01

    The success of Clinical Decision Support Systems (CDSS) greatly depends on its capability of being integrated in Health Information Systems (HIS). Several proposals have been published up to date to permit CDSS gathering patient data from HIS. Some base the CDSS data input on the HL7 reference model, however, they are tailored to specific CDSS or clinical guidelines technologies, or do not focus on standardizing the CDSS resultant knowledge. We propose a solution for facilitating semantic interoperability to rule-based CDSS focusing on standardized input and output documents conforming an HL7-CDA wrapper. We define the HL7-CDA restrictions in a HL7-CDA implementation guide. Patient data and rule inference results are mapped respectively to and from the CDSS by means of a binding method based on an XML binding file. As an independent clinical document, the results of a CDSS can present clinical and legal validity. The proposed solution is being applied in a CDSS for providing patient-specific recommendations for the care management of outpatients with diabetes mellitus. PMID:23199936

  10. Using Visualization in Cockpit Decision Support Systems

    SciTech Connect

    Aragon, Cecilia R.

    2005-07-01

    In order to safely operate their aircraft, pilots must makerapid decisions based on integrating and processing large amounts ofheterogeneous information. Visual displays are often the most efficientmethod of presenting safety-critical data to pilots in real time.However, care must be taken to ensure the pilot is provided with theappropriate amount of information to make effective decisions and notbecome cognitively overloaded. The results of two usability studies of aprototype airflow hazard visualization cockpit decision support systemare summarized. The studies demonstrate that such a system significantlyimproves the performance of helicopter pilots landing under turbulentconditions. Based on these results, design principles and implicationsfor cockpit decision support systems using visualization arepresented.

  11. Attitude of Iranian physicians and nurses toward a clinical decision support system for pulmonary embolism and deep vein thrombosis.

    PubMed

    Agharezaei, Zhila; Bahaadinbeigy, Kambiz; Tofighi, Shahram; Agharezaei, Laleh; Nemati, Ali

    2014-07-01

    This research project sought to design and implement a computerized clinical decision support system (CDSS) that was able to identify patients who were at risk of pulmonary embolism (PE) and deep vein thrombosis (DVT), as well as produce reminders for prophylactic action for these diseases. The main purpose of the CDSS was to attempt to reduce the morbidity and mortality caused by embolism and thrombosis in patients admitted to hospitals. After implementation of this system in one of the large educational hospitals of Iran, a standard questionnaire was used, and interviews were conducted with physicians and nurses to evaluate the performance of the designed system for reducing the incidence of pulmonary embolism and thrombosis. From physicians and nurses' point of view, a system which assists the medical staff in making better decisions regarding patient care, and also reminds pulmonary embolism and thrombosis preventive procedures with timely warnings, can influence patient care quality improvement and lead to the improved performance of the medical staff in preventing the incidence of pulmonary embolism and thrombosis.

  12. A Novel Clinical Decision Support System Using Improved Adaptive Genetic Algorithm for the Assessment of Fetal Well-Being

    PubMed Central

    Jambek, Asral Bahari; Neoh, Siew-Chin

    2015-01-01

    A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG) dataset through an Improved Adaptive Genetic Algorithm (IAGA) and Extreme Learning Machine (ELM). IAGA employs a new scaling technique (called sigma scaling) to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity. Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function) to assess its performance. The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA. Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum. Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm. PMID:25793009

  13. Temporal pattern mining for multivariate clinical decision support.

    PubMed

    Saini, Sheetal; Dua, Sumeet

    2013-01-01

    Multivariate temporal data are collections of contiguous data values that reflect complex temporal changes over a given duration. Technological advances have resulted in significant amounts of such data in high-throughput disciplines, including EEG and iEEG data for effective and efficient healthcare informatics, and decision support. Most data analytics and data-mining algorithms are effective in capturing global trends, but fail to capture localized behavioral changes in large temporal data sets. We present a two-step algorithmic methodology to uncover temporal patterns and exploiting them for an efficient and accurate decision support system. This methodology aids the discovery of previously unknown, nontrivial, and potentially useful temporal patterns for enhanced patient-specific clinical decision support with high degrees of sensitivity and specificity. Classification results on multivariate time series iEEG data for epileptic seizure detection also demonstrate the efficacy and accuracy of the technique to uncover interesting and effective domain class-specific temporal patterns.

  14. Clinical Decision Support and Closed-Loop Control for Cardiopulmonary Management and Intensive Care Unit Sedation Using Expert Systems.

    PubMed

    Gholami, Behnood; Bailey, James M; Haddad, Wassim M; Tannenbaum, Allen R

    2012-03-01

    Patients in the intensive care unit (ICU) who require mechanical ventilation due to acute respiratory failure also frequently require the administration of sedative agents. The need for sedation arises both from patient anxiety due to the loss of personal control and the unfamiliar and intrusive environment of the ICU, and also due to pain or other variants of noxious stimuli. While physicians select the agent(s) used for sedation and cardiovascular function, the actual administration of these agents is the responsibility of the nursing staff. If clinical decision support systems and closed-loop control systems could be developed for critical care monitoring and lifesaving interventions as well as the administration of sedation and cardiopulmonary management, the ICU nurse could be released from the intense monitoring of sedation, allowing her/him to focus on other critical tasks. One particularly attractive strategy is to utilize the knowledge and experience of skilled clinicians, capturing explicitly the rules expert clinicians use to decide on how to titrate drug doses depending on the level of sedation. In this paper, we extend the deterministic rule-based expert system for cardiopulmonary management and ICU sedation framework presented in [1] to a stochastic setting by using probability theory to quantify uncertainty and hence deal with more realistic clinical situations.

  15. Decision Support and Knowledge-Based Systems.

    ERIC Educational Resources Information Center

    Konsynski, Benn R.; And Others

    1988-01-01

    A series of articles addresses issues concerning decision support and knowledge based systems. Topics covered include knowledge-based systems for information centers; object oriented systems; strategic information systems case studies; user perception; manipulation of certainty factors by individuals and expert systems; spreadsheet program use;…

  16. Evaluating a Web-Based Clinical Decision Support System for Language Disorders Screening in a Nursery School

    PubMed Central

    Valero Duboy, Miguel Ángel; Torcal Loriente, Carmen; Pau de la Cruz, Iván

    2014-01-01

    Background Early and effective identification of developmental disorders during childhood remains a critical task for the international community. The second highest prevalence of common developmental disorders in children are language delays, which are frequently the first symptoms of a possible disorder. Objective This paper evaluates a Web-based Clinical Decision Support System (CDSS) whose aim is to enhance the screening of language disorders at a nursery school. The common lack of early diagnosis of language disorders led us to deploy an easy-to-use CDSS in order to evaluate its accuracy in early detection of language pathologies. This CDSS can be used by pediatricians to support the screening of language disorders in primary care. Methods This paper details the evaluation results of the “Gades” CDSS at a nursery school with 146 children, 12 educators, and 1 language therapist. The methodology embraces two consecutive phases. The first stage involves the observation of each child’s language abilities, carried out by the educators, to facilitate the evaluation of language acquisition level performed by a language therapist. Next, the same language therapist evaluates the reliability of the observed results. Results The Gades CDSS was integrated to provide the language therapist with the required clinical information. The validation process showed a global 83.6% (122/146) success rate in language evaluation and a 7% (7/94) rate of non-accepted system decisions within the range of children from 0 to 3 years old. The system helped language therapists to identify new children with potential disorders who required further evaluation. This process will revalidate the CDSS output and allow the enhancement of early detection of language disorders in children. The system does need minor refinement, since the therapists disagreed with some questions from the CDSS knowledge base (KB) and suggested adding a few questions about speech production and pragmatic

  17. Knowledge-analytics synergy in Clinical Decision Support.

    PubMed

    Slonim, Noam; Carmeli, Boaz; Goldsteen, Abigail; Keller, Oliver; Kent, Carmel; Rinott, Ruty

    2012-01-01

    Clinical Decision Support (CDS) systems hold tremendous potential for improving patient care. Most existing systems are knowledge-based tools that rely on relatively simple rules. More recent approaches rely on analytics techniques to automatically mine EHR data to reveal meaningful insights. Here, we propose the Knowledge-Analytics Synergy paradigm for CDS, in which we synergistically combine existing relevant knowledge with analytics applied to EHR data. We propose a framework for implementing such a paradigm and demonstrate its principles over real-world clinical and genomic data of hypertensive patients.

  18. Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review

    PubMed Central

    Arguello Casteleiro, Mercedes; Ainsworth, John; Buchan, Iain

    2015-01-01

    Background Patients with multiple conditions have complex needs and are increasing in number as populations age. This multimorbidity is one of the greatest challenges facing health care. Having more than 1 condition generates (1) interactions between pathologies, (2) duplication of tests, (3) difficulties in adhering to often conflicting clinical practice guidelines, (4) obstacles in the continuity of care, (5) confusing self-management information, and (6) medication errors. In this context, clinical decision support (CDS) systems need to be able to handle realistic complexity and minimize iatrogenic risks. Objective The aim of this review was to identify to what extent CDS is adopted in multimorbidity. Methods This review followed PRISMA guidance and adopted a multidisciplinary approach. Scopus and PubMed searches were performed by combining terms from 3 different thesauri containing synonyms for (1) multimorbidity and comorbidity, (2) polypharmacy, and (3) CDS. The relevant articles were identified by examining the titles and abstracts. The full text of selected/relevant articles was analyzed in-depth. For articles appropriate for this review, data were collected on clinical tasks, diseases, decision maker, methods, data input context, user interface considerations, and evaluation of effectiveness. Results A total of 50 articles were selected for the full in-depth analysis and 20 studies were included in the final review. Medication (n=10) and clinical guidance (n=8) were the predominant clinical tasks. Four studies focused on merging concurrent clinical practice guidelines. A total of 17 articles reported their CDS systems were knowledge-based. Most articles reviewed considered patients’ clinical records (n=19), clinical practice guidelines (n=12), and clinicians’ knowledge (n=10) as contextual input data. The most frequent diseases mentioned were cardiovascular (n=9) and diabetes mellitus (n=5). In all, 12 articles mentioned generalist doctor(s) as the

  19. Formal Logic and Flowchart for Diagnosis Validity Verification and Inclusion in Clinical Decision Support Systems

    NASA Astrophysics Data System (ADS)

    Sosa, M.; Grundel, L.; Simini, F.

    2016-04-01

    Logical reasoning is part of medical practice since its origins. Modern Medicine has included information-intensive tools to refine diagnostics and treatment protocols. We are introducing formal logic teaching in Medical School prior to Clinical Internship, to foster medical practice. Two simple examples (Acute Myocardial Infarction and Diabetes Mellitus) are given in terms of formal logic expression and truth tables. Flowcharts of both diagnostic processes help understand the procedures and to validate them logically. The particularity of medical information is that it is often accompanied by “missing data” which suggests to adapt formal logic to a “three state” logic in the future. Medical Education must include formal logic to understand complex protocols and best practices, prone to mutual interactions.

  20. Decision support systems for robotic surgery and acute care

    NASA Astrophysics Data System (ADS)

    Kazanzides, Peter

    2012-06-01

    Doctors must frequently make decisions during medical treatment, whether in an acute care facility, such as an Intensive Care Unit (ICU), or in an operating room. These decisions rely on a various information sources, such as the patient's medical history, preoperative images, and general medical knowledge. Decision support systems can assist by facilitating access to this information when and where it is needed. This paper presents some research eorts that address the integration of information with clinical practice. The example systems include a clinical decision support system (CDSS) for pediatric traumatic brain injury, an augmented reality head- mounted display for neurosurgery, and an augmented reality telerobotic system for minimally-invasive surgery. While these are dierent systems and applications, they share the common theme of providing information to support clinical decisions and actions, whether the actions are performed with the surgeon's own hands or with robotic assistance.

  1. A highly scalable, interoperable clinical decision support service

    PubMed Central

    Goldberg, Howard S; Paterno, Marilyn D; Rocha, Beatriz H; Schaeffer, Molly; Wright, Adam; Erickson, Jessica L; Middleton, Blackford

    2014-01-01

    Objective To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions. Materials and methods The enterprise clinical rules service (ECRS) realizes nine design principles through a series of enterprise java beans and leverages off-the-shelf rules management systems in order to provide consistent, maintainable, and scalable decision support in a variety of settings. Results The ECRS is deployed at Partners HealthCare System (PHS) and is in use for a series of trials by members of the CDS consortium, including internally developed systems at PHS, the Regenstrief Institute, and vendor-based systems deployed at locations in Oregon and New Jersey. Performance measures indicate that the ECRS provides sub-second response time when measured apart from services required to retrieve data and assemble the continuity of care document used as input. Discussion We consider related work, design decisions, comparisons with emerging national standards, and discuss uses and limitations of the ECRS. Conclusions ECRS design, implementation, and use in CDS consortium trials indicate that it provides the flexibility and modularity needed for broad use and performs adequately. Future work will investigate additional CDS patterns, alternative methods of data passing, and further optimizations in ECRS performance. PMID:23828174

  2. Qualitative analysis of vendor discussions on the procurement of Computerised Physician Order Entry and Clinical Decision Support systems in hospitals

    PubMed Central

    Cresswell, Kathrin M; Lee, Lisa; Slee, Ann; Coleman, Jamie; Bates, David W; Sheikh, Aziz

    2015-01-01

    Objectives We studied vendor perspectives about potentially transferable lessons for implementing organisations and national strategies surrounding the procurement of Computerised Physician Order Entry (CPOE)/Clinical Decision Support (CDS) systems in English hospitals. Setting Data were collected from digitally audio-recorded discussions from a series of CPOE/CDS vendor round-table discussions held in September 2014 in the UK. Participants Nine participants, representing 6 key vendors operating in the UK, attended. The discussions were transcribed verbatim and thematically analysed. Results Vendors reported a range of challenges surrounding the procurement and contracting processes of CPOE/CDS systems, including hospitals’ inability to adequately assess their own needs and then select a suitable product, rushed procurement and implementation processes that resulted in difficulties in meaningfully engaging with vendors, as well as challenges relating to contracting leading to ambiguities in implementation roles. Consequently, relationships between system vendors and hospitals were often strained, the vendors attributing this to a lack of hospital management's appreciation of the complexities associated with implementation efforts. Future anticipated challenges included issues surrounding the standardisation of data to enable their aggregation across systems for effective secondary uses, and implementation of data exchange with providers outside the hospital. Conclusions Our results indicate that there are significant issues surrounding capacity to procure and optimise CPOE/CDS systems among UK hospitals. There is an urgent need to encourage more synergistic and collaborative working between providers and vendors and for a more centralised support for National Health Service hospitals, which draws on a wider body of experience, including a formalised procurement framework with value-based product specifications. PMID:26503385

  3. Using Visualization in Cockpit Decision Support Systems

    NASA Technical Reports Server (NTRS)

    Aragon, Cecilia R.

    2005-01-01

    In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.

  4. Decision support system for nursing management control

    SciTech Connect

    Ernst, C.J.

    1983-01-01

    A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.

  5. Reducing Diagnostic Error with Computer-Based Clinical Decision Support

    ERIC Educational Resources Information Center

    Greenes, Robert A.

    2009-01-01

    Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision…

  6. Developing Clinical Decision Support within a Commercial Electronic Health Record System to Improve Antimicrobial Prescribing in the Neonatal ICU

    PubMed Central

    Cato, K.; Sheehan, B.; Patel, S.; Duchon, J.; DeLaMora, P.; Ferng, Y.H.; Graham, P.; Vawdrey, D.K.; Perlman, J.; Larson, E.; Saiman, L.

    2014-01-01

    Summary Objective To develop and implement a clinical decision support (CDS) tool to improve antibiotic prescribing in neonatal intensive care units (NICUs) and to evaluate user acceptance of the CDS tool. Methods Following sociotechnical analysis of NICU prescribing processes, a CDS tool for empiric and targeted antimicrobial therapy for healthcare-associated infections (HAIs) was developed and incorporated into a commercial electronic health record (EHR) in two NICUs. User logs were reviewed and NICU prescribers were surveyed for their perceptions of the CDS tool. Results The CDS tool aggregated selected laboratory results, including culture results, to make treatment recommendations for common clinical scenarios. From July 2010 to May 2012, 1,303 CDS activations for 452 patients occurred representing 22% of patients prescribed antibiotics during this period. While NICU clinicians viewed two culture results per tool activation, prescribing recommendations were viewed during only 15% of activations. Most (63%) survey respondents were aware of the CDS tool, but fewer (37%) used it during their most recent NICU rotation. Respondents considered the most useful features to be summarized culture results (43%) and antibiotic recommendations (48%). Discussion During the study period, the CDS tool functionality was hindered by EHR upgrades, implementation of a new laboratory information system, and changes to antimicrobial testing methodologies. Loss of functionality may have reduced viewing antibiotic recommendations. In contrast, viewing culture results was frequently performed, likely because this feature was perceived as useful and functionality was preserved. Conclusion To improve CDS tool visibility and usefulness, we recommend early user and information technology team involvement which would facilitate use and mitigate implementation challenges. PMID:25024755

  7. Decision Support Systems in Academic Administration.

    ERIC Educational Resources Information Center

    Turban, Efraim; And Others

    1988-01-01

    Presents an overview of a computerized Decision Support System (DSS) for academic administrators. Following a discussion of its capabilities, the various components of a DSS are examined as well as the development tools needed. Examples follow of DSS in two universities, and various development and implementation issues are considered. (TE)

  8. Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

    PubMed

    Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

    2009-04-01

    Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

  9. SMARTHealth India: Development and Field Evaluation of a Mobile Clinical Decision Support System for Cardiovascular Diseases in Rural India

    PubMed Central

    Patel, Anushka; Raghu, Arvind; Clifford, Gari D; Maulik, Pallab K; Mohammad Abdul, Ameer; Mogulluru, Kishor; Tarassenko, Lionel; MacMahon, Stephen; Peiris, David

    2014-01-01

    Background Cardiovascular disease (CVD) is the major cause of premature death and disability in India and yet few people at risk of CVD are able to access best practice health care. Mobile health (mHealth) is a promising solution, but very few mHealth interventions have been subjected to robust evaluation in India. Objective The objectives were to develop a multifaceted, mobile clinical decision support system (CDSS) for CVD management and evaluate it for use by public nonphysician health care workers (NPHWs) and physicians in a rural Indian setting. Methods Plain language clinical rules were developed based on standard guidelines and programmed into a computer tablet app. The algorithm was validated and field-tested in 11 villages in Andhra Pradesh, involving 11 NPHWs and 3 primary health center (PHC) physicians. A mixed method evaluation was conducted comprising clinical and survey data and in-depth patient and staff interviews to understand barriers and enablers to the use of the system. Then this was thematically analyzed using NVivo 10. Results During validation of the algorithm, there was an initial agreement for 70% of the 42 calculated variables between the CDSS and SPSS software outputs. Discrepancies were identified and amendments were made until perfect agreement was achieved. During field testing, NPHWs and PHC physicians used the CDSS to screen 227 and 65 adults, respectively. The NPHWs identified 39% (88/227) of patients for referral with 78% (69/88) of these having a definite indication for blood pressure (BP)-lowering medication. However, only 35% (24/69) attended a clinic within 1 month of referral, with 42% (10/24) of these reporting continuing medications at 3-month follow-up. Physicians identified and recommended 17% (11/65) of patients for BP-lowering medications. Qualitative interviews identified 3 interrelated interview themes: (1) the CDSS had potential to change prevailing health care models, (2) task-shifting to NPHWs was the central

  10. Clinical Decision Support Knowledge Management: Strategies for Success.

    PubMed

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.

  11. Clinical Decision Support Knowledge Management: Strategies for Success.

    PubMed

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital. PMID:26152955

  12. Geospatial decision support systems for societal decision making

    USGS Publications Warehouse

    Bernknopf, R.L.

    2005-01-01

    While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the

  13. Computerized clinical decision support systems for primary preventive care: A decision-maker-researcher partnership systematic review of effects on process of care and patient outcomes

    PubMed Central

    2011-01-01

    Background Computerized clinical decision support systems (CCDSSs) are claimed to improve processes and outcomes of primary preventive care (PPC), but their effects, safety, and acceptance must be confirmed. We updated our previous systematic reviews of CCDSSs and integrated a knowledge translation approach in the process. The objective was to review randomized controlled trials (RCTs) assessing the effects of CCDSSs for PPC on process of care, patient outcomes, harms, and costs. Methods We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews Database, Inspec, and other databases, as well as reference lists through January 2010. We contacted authors to confirm data or provide additional information. We included RCTs that assessed the effect of a CCDSS for PPC on process of care and patient outcomes compared to care provided without a CCDSS. A study was considered to have a positive effect (i.e., CCDSS showed improvement) if at least 50% of the relevant study outcomes were statistically significantly positive. Results We added 17 new RCTs to our 2005 review for a total of 41 studies. RCT quality improved over time. CCDSSs improved process of care in 25 of 40 (63%) RCTs. Cumulative scientifically strong evidence supports the effectiveness of CCDSSs for screening and management of dyslipidaemia in primary care. There is mixed evidence for effectiveness in screening for cancer and mental health conditions, multiple preventive care activities, vaccination, and other preventive care interventions. Fourteen (34%) trials assessed patient outcomes, and four (29%) reported improvements with the CCDSS. Most trials were not powered to evaluate patient-important outcomes. CCDSS costs and adverse events were reported in only six (15%) and two (5%) trials, respectively. Information on study duration was often missing, limiting our ability to assess sustainability of CCDSS effects. Conclusions Evidence supports the

  14. Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation

    PubMed Central

    Linan, Margaret K.; Sottara, Davide; Freimuth, Robert R.

    2015-01-01

    Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines. PMID:26958298

  15. A Decision Support System for Supervised Assignment in Banking Decisions

    NASA Astrophysics Data System (ADS)

    Rigopoulos, George; Psarras, John; Askounis, Dimitrios Th.

    This study presents a Decision Support System (DSS) which supports assignment of actions (e.g., numbers, projects, people etc.) into predefined categories according to their score on evaluation criteria. It implements a novel classification algorithm based on multicriteria analysis and fuzzy preference relations. More detailed, assignment to classes is based on the concept of category threshold, which defines at what degree an alternative can be included in a specific category. For each category a threshold is defined by the corresponding decision maker, which indicates its lower limit with respect to the evaluation criteria. Actions are then evaluated according to the criteria and fuzzy inclusion degrees are calculated for each category. Finally, an action is assigned to the category for which the inclusion degree is the maximum. The DSS implements the above classification algorithm, providing a user-friendly interface, which supports decision makers to formulate and solve similar problems. In addition to the DSS, we present a real world application at a classification problem within the environment of a Greek bank. Results derived from evaluation experiments in the business environment provide evidence that the proposed methodology and the DSS can effectively support decision makers in classification decisions. The methodology as well as the proposed DSS can be used to classification problems not only in financial domain but to a variety of domains such as production, environmental, or human resources.

  16. Development of a real-time clinical decision support system upon the web mvc-based architecture for prostate cancer treatment

    PubMed Central

    2011-01-01

    Background A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily

  17. Expert System Shells for Rapid Clinical Decision Support Module Development: An ESTA Demonstration of a Simple Rule-Based System for the Diagnosis of Vaginal Discharge

    PubMed Central

    2012-01-01

    Objectives This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. Methods A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. Results The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. Conclusions An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community. PMID:23346475

  18. Clinical Decision Support for Colon and Rectal Surgery: An Overview

    PubMed Central

    McCoy, Allison B.; Melton, Genevieve B.; Wright, Adam; Sittig, Dean F.

    2013-01-01

    Clinical decision support (CDS) has been shown to improve clinical processes, promote patient safety, and reduce costs in healthcare settings, and it is now a requirement for clinicians as part of the Meaningful Use Regulation. However, most evidence for CDS has been evaluated primarily in internal medicine care settings, and colon and rectal surgery (CRS) has unique needs with CDS that are not frequently described in the literature. The authors reviewed published literature in informatics and medical journals, combined with expert opinion to define CDS, describe the evidence for CDS, outline the implementation process for CDS, and present applications of CDS in CRS.CDS functionalities such as order sets, documentation templates, and order facilitation aids are most often described in the literature and most likely to be beneficial in CRS. Further research is necessary to identify and better evaluate additional CDS systems in the setting of CRS. PMID:24436644

  19. Clinical Decision Support for Early Recognition of Sepsis.

    PubMed

    Amland, Robert C; Hahn-Cover, Kristin E

    2016-01-01

    Sepsis is an inflammatory response triggered by infection, with a high in-hospital mortality rate. Early recognition and treatment can reverse the inflammatory response, with evidence of improved patient outcomes. One challenge clinicians face is identifying the inflammatory syndrome against the background of the patient's infectious illness and comorbidities. An approach to this problem is implementation of computerized early warning tools for sepsis. This multicenter retrospective study sought to determine clinimetric performance of a cloud-based computerized sepsis clinical decision support system (CDS), understand the epidemiology of sepsis, and identify opportunities for quality improvement. Data encompassed 6200 adult hospitalizations from 2012 through 2013. Of 13% patients screened-in, 51% were already suspected to have an infection when the system activated. This study focused on a patient cohort screened-in before infection was suspected; median time from arrival to CDS activation was 3.5 hours, and system activation to diagnostic collect was another 8.6 hours. PMID:25385815

  20. Decision support system for drinking water management

    NASA Astrophysics Data System (ADS)

    Janža, M.

    2012-04-01

    The problems in drinking water management are complex and often solutions must be reached under strict time constrains. This is especially distinct in case of environmental accidents in the catchment areas of the wells that are used for drinking water supply. The beneficial tools that can help decision makers and make program of activities more efficient are decision support systems (DSS). In general they are defined as computer-based support systems that help decision makers utilize data and models to solve unstructured problems. The presented DSS was developed in the frame of INCOME project which is focused on the long-term stable and safe drinking water supply in Ljubljana. The two main water resources Ljubljana polje and Barje alluvial aquifers are characterized by a strong interconnection of surface and groundwater, high vulnerability, high velocities of groundwater flow and pollutant transport. In case of sudden pollution, reactions should be very fast to avoid serious impact to the water supply. In the area high pressures arising from urbanization, industry, traffic, agriculture and old environmental burdens. The aim of the developed DSS is to optimize the activities in cases of emergency water management and to optimize the administrative work regarding the activities that can improve groundwater quality status. The DSS is an interactive computer system that utilizes data base, hydrological modelling, and experts' and stakeholders' knowledge. It consists of three components, tackling the different abovementioned issues in water management. The first one utilizes the work on identification, cleaning up and restoration of illegal dumpsites that are a serious threat to the qualitative status of groundwater. The other two components utilize the predictive capability of the hydrological model and scenario analysis. The user interacts with the system by a graphical interface that guides the user step-by-step to the recommended remedial measures. Consequently, the

  1. IPDS: Integrated Planning Decision Support System

    SciTech Connect

    Mejia-Navarro, M.; Garcia, L.A.

    1995-12-31

    The Integrated Planning Decision Support System (IPDS) is designed as a decision support system (DSS) to assist governments and communities in evaluation of geological hazards, vulnerability, and risk. The IPDS system incorporates the Geographic Information Systems (GIS) Geographic Resource Analysis Support System (GRASS) and engineering numerical models within a Graphic User Interface (GUI), to provide the user with comprehensive modelling capabilities for geological hazards, vulnerability, and risk assessment. The methodology that IPDS follows for the evaluation of hazards takes into account the weight of each influencing factor within hazardous geologic processes. IPDS interactive algorithms compute the following parameters for each cell (based on the maximum resolution of the data): the related hazard, the vulnerability to geological hazards, and the risk. IPDS is designed to assess any generic hazard, such as debris flows, subsidence, and floods, with probable maximum precipitation and seismicity as triggering factors for susceptibility scenarios. The regular items considered in vulnerability analysis are (1) ecosystem sensitivity, (2) economic vulnerability, and (3) social infrastructure vulnerability. The risk is assessed as a function of hazard and vulnerability.

  2. 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

  3. Web Support System for Group Collaborative Decisions

    NASA Astrophysics Data System (ADS)

    Rigopoulos, George; Psarras, John; Askounis, Dimitrios Th.

    In this research, we present a Group Decision Support System (GDSS) based on web technology, which can be used in asynchronous mode from group members. It supports small collaborative groups in classification decisions, implementing a supervised multicriteria methodology. A facilitator, who defines necessary parameters and initiates the procedure, coordinates the entire operation. Next, members evaluate the proposed parameter set and express their preferences in numeric format. Aggregation of individuals` preferences is executed at the parameter level by utilization of OWA operator and a group parameter set is produced which is used as input for the classification algorithm. A multicriteria classification algorithm is used for the classification of actions (people, projects etc.). Finally, group members evaluate results and consensus as well as satisfaction indexes are calculated. In case of low acceptance level, parameters are redefined and aggregation phase is repeated. The system has been utilized effectively to solve group classification problems in business environment. The overall architecture as well the methodology is presented, along with a sample application. Empirical findings from GDSS application and the methodology provide evidence that it is a valid approach for similar decision problems in numerous business environments, including production, human resources and operations.

  4. IBM’s Health Analytics and Clinical Decision Support

    PubMed Central

    Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

    2014-01-01

    Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

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

    PubMed Central

    2011-01-01

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

  6. Examining the Relationship between Clinical Decision Support and Performance Measurement

    PubMed Central

    Haggstrom, David A.; Saleem, Jason J.; Militello, Laura G.; Arbuckle, Nicole; Flanagan, Mindy; Doebbeling, Bradley N.

    2009-01-01

    In concept and practice, clinical decision support (CDS) and performance measurement represent distinct approaches to organizational change, yet these two organizational processes are interrelated. We set out to better understand how the relationship between the two is perceived, as well as how they jointly influence clinical practice. To understand the use of CDS at benchmark institutions, we conducted semistructured interviews with key managers, information technology personnel, and clinical leaders during a qualitative field study. Improved performance was frequently cited as a rationale for the use of clinical reminders. Pay-for-performance efforts also appeared to provide motivation for the use of clinical reminders. Shared performance measures were associated with shared clinical reminders. The close link between clinical reminders and performance measurement causes these tools to have many of the same implementation challenges. PMID:20351854

  7. Clinical Decision Support for Immunizations (CDSi): A Comprehensive, Collaborative Strategy

    PubMed Central

    Arzt, Noam H.

    2016-01-01

    This article focuses on the requirements and current developments in clinical decision support technologies for immunizations (CDSi) in both the public health and clinical communities, with an emphasis on shareable solutions. The requirements of the Electronic Health Record Incentive Programs have raised some unique challenges for the clinical community, including vocabulary mapping, update of changing guidelines, single immunization schedule, and scalability. This article discusses new, collaborative approaches whose long-term goal is to make CDSi more sustainable for both the public and private sectors. PMID:27789956

  8. Semantic technologies in a decision support system

    NASA Astrophysics Data System (ADS)

    Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

    2015-10-01

    The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

  9. Artificial neural networks for decision support in clinical medicine.

    PubMed

    Forsström, J J; Dalton, K J

    1995-10-01

    Connectionist models such as neural networks are alternatives to linear, parametric statistical methods. Neural networks are computer-based pattern recognition methods with loose similarities with the nervous system. Individual variables of the network, usually called 'neurones', can receive inhibitory and excitatory inputs from other neurones. The networks can define relationships among input data that are not apparent when using other approaches, and they can use these relationships to improve accuracy. Thus, neural nets have substantial power to recognize patterns even in complex datasets. Neural network methodology has outperformed classical statistical methods in cases where the input variables are interrelated. Because clinical measurements usually derive from multiple interrelated systems it is evident that neural networks might be more accurate than classical methods in multivariate analysis of clinical data. This paper reviews the use of neural networks in medical decision support. A short introduction to the basics of neural networks is given, and some practical issues in applying the networks are highlighted. The current use of neural networks in image analysis, signal processing and laboratory medicine is reviewed. It is concluded that neural networks have an important role in image analysis and in signal processing. However, further studies are needed to determine the value of neural networks in the analysis of laboratory data.

  10. SANDS: A Service-Oriented Architecture for Clinical Decision Support in a National Health Information Network

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. PMID:18434256

  11. Ontology-based modeling of clinical practice guidelines: a clinical decision support system for breast cancer follow-up interventions at primary care settings.

    PubMed

    Abidi, Samina R; Abidi, Syed S R; Hussain, Sajjad; Shepherd, Mike

    2007-01-01

    Breast cancer follow-up care can be provided by family physicians after specialists complete the primary treatment. Cancer Care Nova Scotia has developed a breast cancer follow-up Clinical Practice Guideline (CPG) targeting family physicians. In this paper we present a project to computerize and deploy the said CPG in a Breast Cancer Follow-up Decision Support System (BCF-DSS) for use by family physicians in a primary care setting. We present a semantic web approach to model the CPG knowledge and employ a logic-based proof engine to execute the CPG in order to infer patient-specific recommendations. We present the three stages of the development of BCF-DSS--i.e., (a) Computerization of the paper-based CPG for Breast Cancer follow-up; (b) Development of three ontologies--i.e., the Breast Cancer Ontology, the CPG ontology based on the Guideline Element Model (GEM) and a Patient Ontology; and (c) Execution of the Breast Cancer follow-up CPG through a logic-based CPG execution engine.

  12. A multimedia electronic patient record (ePR) system to improve decision support in pre- and rehabilitation through clinical and movement analysis

    NASA Astrophysics Data System (ADS)

    Liu, Brent; Documet, Jorge; McNitt-Gray, Sarah; Requejo, Phil; McNitt-Gray, Jill

    2011-03-01

    Clinical decisions for improving motor function in patients both with disability as well as improving an athlete's performance are made through clinical and movement analysis. Currently, this analysis facilitates identifying abnormalities in a patient's motor function for a large amount of neuro-musculoskeletal pathologies. However definitively identifying the underlying cause or long-term consequences of a specific abnormality in the patient's movement pattern is difficult since this requires information from multiple sources and formats across different times and currently relies on the experience and intuition of the expert clinician. In addition, this data must be persistent for longitudinal outcomes studies. Therefore a multimedia ePR system integrating imaging informatics data could have a significant impact on decision support within this clinical workflow. We present the design and architecture of such an ePR system as well as the data types that need integration in order to develop relevant decision support tools. Specifically, we will present two data model examples: 1) A performance improvement project involving volleyball athletes and 2) Wheelchair propulsion evaluation of patients with disabilities. The end result is a new frontier area of imaging informatics research within rehabilitation engineering and biomechanics.

  13. Barriers to implementation of a computerized decision support system for depression: an observational report on lessons learned in "real world" clinical settings

    PubMed Central

    2009-01-01

    Background Despite wide promotion, clinical practice guidelines have had limited effect in changing physician behavior. Effective implementation strategies to date have included: multifaceted interventions involving audit and feedback, local consensus processes, marketing; reminder systems, either manual or computerized; and interactive educational meetings. In addition, there is now growing evidence that contextual factors affecting implementation must be addressed such as organizational support (leadership procedures and resources) for the change and strategies to implement and maintain new systems. Methods To examine the feasibility and effectiveness of implementation of a computerized decision support system for depression (CDSS-D) in routine public mental health care in Texas, fifteen study clinicians (thirteen physicians and two advanced nurse practitioners) participated across five sites, accruing over 300 outpatient visits on 168 patients. Results Issues regarding computer literacy and hardware/software requirements were identified as initial barriers. Clinicians also reported concerns about negative impact on workflow and the potential need for duplication during the transition from paper to electronic systems of medical record keeping. Conclusion The following narrative report based on observations obtained during the initial testing and use of a CDSS-D in clinical settings further emphasizes the importance of taking into account organizational factors when planning implementation of evidence-based guidelines or decision support within a system. PMID:19159458

  14. Computerized decision support system for kidney paired donation program.

    PubMed

    Chen, Yanhua; Song, Peter X-K

    2011-01-01

    In order to assist physicians and other health professionals for health care improvement, clinical decision support systems, through interactive computerized software, become very popular in clinical practice. The crisis associated with kidney organ shortage has triggered an innovative strategy, termed as Kidney Paired Donation (KPD) program, to address a rapidly expanding demand for donor kidneys. KPD program involves how to making optimal decision for allowing patients with incompatible living donors to receive compatible organs by best matching donors. Although some computerized optimization tools are being used in the current KPD program, there still lacks a general decision support system which enables us to evaluate and compare different kidney allocation strategies and effects of policy. In this paper, we discuss a general computer-based KPD decision model that appropriately reflects the real world clinical application. Also, the whole decision process is to be visualized by our Graphical User Interface (GUI) software, which offers a user friendly platform not only to provide a convenient interface for clinicians but also to assess different kidney exchange strategies of clinical importance. PMID:22255013

  15. Reducing diagnostic error with computer-based clinical decision support.

    PubMed

    Greenes, Robert A

    2009-09-01

    Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision making (Schiff). In addition, several other considerations relating to this topic are interesting to ponder. We are moving toward increased understanding of gene regulation and gene expression, identification of biomarkers, and the ability to predict patient response to disease and to tailor treatments to these individual variations-referred to as "personalized" or, more recently, "predictive" medicine. Consequently, diagnostic decision making is more and more linked to management decision making, and generic diagnostic labels like "diabetes" or "colon cancer" will no longer be sufficient, because they don't tell us what to do. Ultimately, if we have more complete data including more structured capture of phenomic data as well as the characterization of the patient's genome, direct prediction from responses of highly refined subsets of similar patients in a database can be used to select appropriate management, the effectiveness of which was demonstrated in projects in selected limited domains as early as the 1970s. In general, there are six classes of methodologies, including the above, which can be applied to delivering CDS. In addition, patients are becoming more knowledgeable and should be regarded as active participants, not only in helping to obtain data but also in their own status assessment and as recipients of decision support. With the above advances, this is a very promising time to be engaged in pursuit of methods of CDS. PMID:19669915

  16. Evaluation of medium-term consequences of implementing commercial computerized physician order entry and clinical decision support prescribing systems in two ‘early adopter’ hospitals

    PubMed Central

    Cresswell, Kathrin M; Bates, David W; Williams, Robin; Morrison, Zoe; Slee, Ann; Coleman, Jamie; Robertson, Ann; Sheikh, Aziz

    2014-01-01

    Objective To understand the medium-term consequences of implementing commercially procured computerized physician order entry (CPOE) and clinical decision support (CDS) systems in ‘early adopter’ hospitals. Materials and methods In-depth, qualitative case study in two hospitals using a CPOE or a CDS system for at least 2 years. Both hospitals had implemented commercially available systems. Hospital A had implemented a CPOE system (with basic decision support), whereas hospital B invested additional resources in a CDS system that facilitated order entry but which was integrated with electronic health records and offered more advanced CDS. We used a combination of documentary analysis of the implementation plans, audiorecorded semistructured interviews with system users, and observations of strategic meetings and systems usage. Results We collected 11 documents, conducted 43 interviews, and conducted a total of 21.5 h of observations. We identified three major themes: (1) impacts on individual users, including greater legibility of prescriptions, but also some accounts of increased workloads; (2) the introduction of perceived new safety risks related to accessibility and usability of hardware and software, with users expressing concerns that some problems such as duplicate prescribing were more likely to occur; and (3) realizing organizational benefits through secondary uses of data. Conclusions We identified little difference in the medium-term consequences of a CPOE and a CDS system. It is important that future studies investigate the medium- and longer-term consequences of CPOE and CDS systems in a wider range of hospitals. PMID:24431334

  17. Evaluation of RxNorm for Medication Clinical Decision Support

    PubMed Central

    Freimuth, Robert R.; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G.

    2014-01-01

    We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS. PMID:25954360

  18. Database and knowledge base integration in decision support systems.

    PubMed Central

    Johansson, B.; Shahsavar, N.; Ahlfeldt, H.; Wigertz, O.

    1996-01-01

    Since decision support systems (DSS) in medicine often are linked to clinical databases it is important to find methods that facilitate the work for DSS developers to implement database queries in the knowledge base (KB). This paper presents a method for linking clinical databases to a KB with Arden Syntax modules. The method is based on a query meta database including templates for SQL queries. During knowledge module authoring the medical expert only refers to a code in the query meta database. Our method uses standard tools so it can be implemented on different platforms and linked to different clinical databases. PMID:8947666

  19. Development of a clinical decision support system using genetic algorithms and Bayesian classification for improving the personalised management of women attending a colposcopy room.

    PubMed

    Bountris, Panagiotis; Topaka, Elena; Pouliakis, Abraham; Haritou, Maria; Karakitsos, Petros; Koutsouris, Dimitrios

    2016-06-01

    Cervical cancer (CxCa) is often the result of underestimated abnormalities in the test Papanicolaou (Pap test). The recent advances in the study of the human papillomavirus (HPV) infection (the necessary cause for CxCa development) have guided clinical practice to add HPV related tests alongside the Pap test. In this way, today, HPV DNA testing is well accepted as an ancillary test and it is used for the triage of women with abnormal findings in cytology. However, these tests are either highly sensitive or highly specific, and therefore none of them provides an optimal solution. In this Letter, a clinical decision support system based on a hybrid genetic algorithm - Bayesian classification framework is presented, which combines the results of the Pap test with those of the HPV DNA test in order to exploit the benefits of each method and produce more accurate outcomes. Compared with the medical tests and their combinations (co-testing), the proposed system produced the best receiver operating characteristic curve and the most balanced combination among sensitivity and specificity in detecting high-grade cervical intraepithelial neoplasia and CxCa (CIN2+). This system may support decision-making for the improved management of women who attend a colposcopy room following a positive test result. PMID:27382484

  20. Using Machine Learning and Natural Language Processing Algorithms to Automate the Evaluation of Clinical Decision Support in Electronic Medical Record Systems

    PubMed Central

    Szlosek, Donald A; Ferrett, Jonathan

    2016-01-01

    Introduction: As the number of clinical decision support systems (CDSSs) incorporated into electronic medical records (EMRs) increases, so does the need to evaluate their effectiveness. The use of medical record review and similar manual methods for evaluating decision rules is laborious and inefficient. The authors use machine learning and Natural Language Processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an EMR system, and they compare it against manual evaluation. Methods: Modeled after the EMR system EPIC at Maine Medical Center, we developed a dummy data set containing physician notes in free text for 3,621 artificial patients records undergoing a head computed tomography (CT) scan for mild traumatic brain injury after the incorporation of an electronic best practice approach. We validated the accuracy of the Best Practice Advisories (BPA) using three machine learning algorithms—C-Support Vector Classification (SVC), Decision Tree Classifier (DecisionTreeClassifier), k-nearest neighbors classifier (KNeighborsClassifier)—by comparing their accuracy for adjudicating the occurrence of a mild traumatic brain injury against manual review. We then used the best of the three algorithms to evaluate the effectiveness of the BPA, and we compared the algorithm’s evaluation of the BPA to that of manual review. Results: The electronic best practice approach was found to have a sensitivity of 98.8 percent (96.83–100.0), specificity of 10.3 percent, PPV = 7.3 percent, and NPV = 99.2 percent when reviewed manually by abstractors. Though all the machine learning algorithms were observed to have a high level of prediction, the SVC displayed the highest with a sensitivity 93.33 percent (92.49–98.84), specificity of 97.62 percent (96.53–98.38), PPV = 50.00, NPV = 99.83. The SVC algorithm was observed to have a sensitivity of 97.9 percent (94.7–99.86), specificity 10.30 percent, PPV 7.25 percent, and NPV 99.2 percent for

  1. Using Machine Learning and Natural Language Processing Algorithms to Automate the Evaluation of Clinical Decision Support in Electronic Medical Record Systems

    PubMed Central

    Szlosek, Donald A; Ferrett, Jonathan

    2016-01-01

    Introduction: As the number of clinical decision support systems (CDSSs) incorporated into electronic medical records (EMRs) increases, so does the need to evaluate their effectiveness. The use of medical record review and similar manual methods for evaluating decision rules is laborious and inefficient. The authors use machine learning and Natural Language Processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an EMR system, and they compare it against manual evaluation. Methods: Modeled after the EMR system EPIC at Maine Medical Center, we developed a dummy data set containing physician notes in free text for 3,621 artificial patients records undergoing a head computed tomography (CT) scan for mild traumatic brain injury after the incorporation of an electronic best practice approach. We validated the accuracy of the Best Practice Advisories (BPA) using three machine learning algorithms—C-Support Vector Classification (SVC), Decision Tree Classifier (DecisionTreeClassifier), k-nearest neighbors classifier (KNeighborsClassifier)—by comparing their accuracy for adjudicating the occurrence of a mild traumatic brain injury against manual review. We then used the best of the three algorithms to evaluate the effectiveness of the BPA, and we compared the algorithm’s evaluation of the BPA to that of manual review. Results: The electronic best practice approach was found to have a sensitivity of 98.8 percent (96.83–100.0), specificity of 10.3 percent, PPV = 7.3 percent, and NPV = 99.2 percent when reviewed manually by abstractors. Though all the machine learning algorithms were observed to have a high level of prediction, the SVC displayed the highest with a sensitivity 93.33 percent (92.49–98.84), specificity of 97.62 percent (96.53–98.38), PPV = 50.00, NPV = 99.83. The SVC algorithm was observed to have a sensitivity of 97.9 percent (94.7–99.86), specificity 10.30 percent, PPV 7.25 percent, and NPV 99.2 percent for

  2. [A decision-support system for hematology].

    PubMed

    Straka, L; Stránský, P; Kmonícek, M

    1998-01-01

    Thrombocytopenia and following bleeding at the treatment of hematological malignancies is a dangerous complication. The indication of thrombocyte transfusion is the key point for the therapy and proylaxy of bleeding. The all problem is divided into two parts. Evaluation of the risk of bleeding (80% of decision), estimation of the risk of aloimunization and risk of connected with the transfusion (20% decision). For now we are concentrated to the evaluation of the risk of bleeding. In the first stage we are concentrated to statistical evaluation of values to define factors possibly highering the risk of bleeding. Factors were determined with help of two test, GUHA method and using literature. For recognized factors were trained 3 layer neuron nets with a non-linear method pack propagation. After that an application was developed to determine the risk of bleeding for a routine use in clinical practice.

  3. Decision support system based semantic web for personalized patient care.

    PubMed

    Douali, Nassim; De Roo, Jos; Jaulent, Marie-Christine

    2012-01-01

    Personalized medicine may be considered an extension of traditional approaches to understanding and treating diseases, but with greater precision. A profile of a patient's genetic variation can guide the selection of drugs or treatment protocols that minimize harmful side effects or ensure a more successful outcome. In this paper we describe a decision support system designed to assist physicians for personalized care, and methodology for integration in the clinical workflow. A reasoning method for interacting heterogeneous knowledge and data is a necessity in the context of personalized medicine. Development of clinical decision support based semantic web for personalized patient care is to achieve its potential and improve the quality, safety and efficiency of healthcare.

  4. Case-based reasoning in Intelligent Health Decision Support Systems.

    PubMed

    González, Carolina; López, Diego M; Blobel, Bernd

    2013-01-01

    Decision-making is a crucial task for decision makers in healthcare, especially because decisions have to be made quickly, accurately and under uncertainty. Taking into account the importance of providing quality decisions, offering assistance in this complex process has been one of the main challenges of Artificial Intelligence throughout history. Decision Support Systems (DSS) have gained popularity in the medical field for their efficacy to assist decision-making. In this sense, many DSS have been developed, but only few of them consider processing and analysis of information contained in electronic health records, in order to identify individual or population health risk factors. This paper deals with Intelligent Decision Support Systems that are integrated into Electronic Health Records Systems (EHRS) or Public Health Information Systems (PHIS). It provides comprehensive support for a wide range of decisions with the purpose of improving quality of care delivered to patients or public health planning, respectively.

  5. Computer Decision Support to Improve Autism Screening and Care in Community Pediatric Clinics

    ERIC Educational Resources Information Center

    Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.

    2013-01-01

    An autism module was added to an existing computer decision support system (CDSS) to facilitate adherence to recommended guidelines for screening for autism spectrum disorders in primary care pediatric clinics. User satisfaction was assessed by survey and informal feedback at monthly meetings between clinical staff and the software team. To assess…

  6. An Organizational Informatics Analysis of Colorectal, Breast, and Cervical Cancer Screening Clinical Decision Support and Information Systems within Community Health Centers

    ERIC Educational Resources Information Center

    Carney, Timothy Jay

    2012-01-01

    A study design has been developed that employs a dual modeling approach to identify factors associated with facility-level cancer screening improvement and how this is mediated by the use of clinical decision support. This dual modeling approach combines principles of (1) Health Informatics, (2) Cancer Prevention and Control, (3) Health Services…

  7. Employing clinical decision support to attain our strategic goal: the safe care of the surgical patient.

    PubMed

    Magid, Steven K; Pancoast, Paul E; Fields, Theodore; Bradley, Diane G; Williams, Robert B

    2007-01-01

    Clinical decision support can be employed to increase patient safety and improve workflow efficiencies for physicians and other healthcare providers. Physician input into the design and deployment of clinical decision support systems can increase the utility of the alerts and reduce the likelihood of "alert fatigue." The Hospital for Special Surgery is a 146-bed orthopedic facility that performs approximately 18,000 surgeries a year Efficient work processes are a necessity. The facility began implementing a new electronic health record system in June 2005 and plan to go live in summer 2007. This article reports on some of the clinical decision support rules and alerts being incorporated into the facility's system in the following categories--high-risk, high-frequency scenarios, rules that provide efficiencies and value from the presciber perspective, and rules that relate to patient safety. PMID:17583164

  8. Automation and Accountability in Decision Support System Interface Design

    ERIC Educational Resources Information Center

    Cummings, Mary L.

    2006-01-01

    When the human element is introduced into decision support system design, entirely new layers of social and ethical issues emerge but are not always recognized as such. This paper discusses those ethical and social impact issues specific to decision support systems and highlights areas that interface designers should consider during design with an…

  9. Decision Support Systems in Elementary and Secondary Educational Administration.

    ERIC Educational Resources Information Center

    Fisher, Janet Cameron; And Others

    1990-01-01

    A decision support system (DSS) is an interactive computerized system capable of providing direct, personal support for complex managerial decisions. This paper reviews DDSs and their general capabilities, describes potential benefits to school administrators, presents DDS applications in several school districts, and discusses implementation…

  10. Improving Emergency Department Triage Classification with Computerized Clinical Decision Support at a Pediatric Hospital

    ERIC Educational Resources Information Center

    Kunisch, Joseph Martin

    2012-01-01

    Background: The Emergency Severity Index (ESI) is an emergency department (ED) triage classification system based on estimated patient-specific resource utilization. Rules for a computerized clinical decision support (CDS) system based on a patient's chief complaint were developed and tested using a stochastic model for predicting ESI scores.…

  11. Decision support system for theater missile defense

    NASA Astrophysics Data System (ADS)

    Gonsalves, Paul; Burge, Janet; Popp, Ben

    2003-08-01

    Military services require C4I systems that support a full spectrum of operations. This is specifically relevant to the theatre missile defense (TMD) mission planning and analysis community where there have been several recent concept changes; advancements in information technology, sensors, and weapons; and expansion in the diversity and capabilities of potential adversaries. To fully support campaign development and analysis in this new environment, there is a need for systems and tools that enhance understanding of adversarial behavior, assess potential threat capabilities and vulnerabilities, perform C4I system trades, and provide methods to identify macro-level novel or emergent combat tactics and behavior derived from simpler micro-level rules. Such systems must also be interactive, collaborative, and semi-autonomous, providing the INTEL analyst with the means for exploration and potential exploitation of novel enemy behavior patterns. To address these issues we have developed an Intelligent Threat Assessment Processor (ITAP) to provide prediction and interpretation of enemy courses of actions (eCOAs) for the TMD domain. This system uses a combination of genetic algorithm-based optimization in tandem with the spatial analysis and visualization capabilities of a commercial-off-the-shelf (COTS) geographic information system to generate and evaluate potential eCOAs.

  12. Personalization and Patient Involvement in Decision Support Systems: Current Trends

    PubMed Central

    Sacchi, L.; Lanzola, G.; Viani, N.

    2015-01-01

    Summary Objectives This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. Methods We considered papers published on scientific journals, by querying PubMed and Web of Science™. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. Results We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. Conclusions Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large. PMID:26293857

  13. The Future of Decision Support Systems in Institutional Research.

    ERIC Educational Resources Information Center

    Rohrbaugh, John

    1986-01-01

    In the context of decision support systems (DSS) use, four perspectives on evaluating decisions (consensual, political, empirical, and rational) and four models of organizational effectiveness (human relations, open system, internal process, and rational goal) are examined for their implications for DSS implementation and evaluation. (MSE)

  14. Decision Support Systems: An Introduction for Program Evaluators.

    ERIC Educational Resources Information Center

    O'Sullivan, Elizabethann

    1985-01-01

    Decision Support Systems (DSS) are automated information systems designed to aid administrative decision making. A literature review on the design, implementation, and evaluation of DSS, suggests that evaluators act as liasons between designers and managers, identify and collect data for DSS, and evaluate DSS. (Author/EGS)

  15. Decision support system for predicting color change after tooth whitening.

    PubMed

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

    Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ΔE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value=0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values. PMID:26657921

  16. Decision support system for predicting color change after tooth whitening.

    PubMed

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

    Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ΔE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value=0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values.

  17. Developing a New Computer-Aided Clinical Decision Support System for Prediction of Successful Postcardioversion Patients with Persistent Atrial Fibrillation

    PubMed Central

    Sterling, Mark; Huang, David T.; Ghoraani, Behnaz

    2015-01-01

    We propose a new algorithm to predict the outcome of direct-current electric (DCE) cardioversion for atrial fibrillation (AF) patients. AF is the most common cardiac arrhythmia and DCE cardioversion is a noninvasive treatment to end AF and return the patient to sinus rhythm (SR). Unfortunately, there is a high risk of AF recurrence in persistent AF patients; hence clinically it is important to predict the DCE outcome in order to avoid the procedure's side effects. This study develops a feature extraction and classification framework to predict AF recurrence patients from the underlying structure of atrial activity (AA). A multiresolution signal decomposition technique, based on matching pursuit (MP), was used to project the AA over a dictionary of wavelets. Seven novel features were derived from the decompositions and were employed in a quadratic discrimination analysis classification to predict the success of post-DCE cardioversion in 40 patients with persistent AF. The proposed algorithm achieved 100% sensitivity and 95% specificity, indicating that the proposed computational approach captures detailed structural information about the underlying AA and could provide reliable information for effective management of AF. PMID:26120354

  18. Introducing pharmacogenetic testing with clinical decision support into primary care: a feasibility study

    PubMed Central

    Dawes, Martin; Aloise, Martin N.; Ang, J. Sidney; Cullis, Pieter; Dawes, Diana; Fraser, Robert; Liknaitzky, Gideon; Paterson, Andrea; Stanley, Paul; Suarez-Gonzalez, Adriana; Katzov-Eckert, Hagit

    2016-01-01

    Background: Inappropriate prescribing increases patient illness and death owing to adverse drug events. The inclusion of genetic information into primary care medication practices is one solution. Our aim was to assess the ability to obtain and genotype saliva samples and to determine the levels of use of a decision support tool that creates medication options adjusted for patient characteristics, drug-drug interactions and pharmacogenetics. Methods: We conducted a cohort study in 6 primary care settings (5 family practices and 1 pharmacy), enrolling 191 adults with at least 1 of 10 common diseases. Saliva samples were obtained in the physician's office or pharmacy and sent to our laboratory, where DNA was extracted and genotyped and reports were generated. The reports were sent directly to the family physician/pharmacist and linked to an evidence-based prescribing decision support system. The primary outcome was ability to obtain and genotype samples. The secondary outcomes were yield and purity of DNA samples, ability to link results to decision support software and use of the decision support software. Results: Genotyping resulted in linking of 189 patients (99%) with pharmacogenetic reports to the decision support program. A total of 96.8% of samples had at least 1 actionable genotype for medications included in the decision support system. The medication support system was used by the physicians and pharmacists 236 times over 3 months. Interpretation: Physicians and pharmacists can collect saliva samples of sufficient quantity and quality for DNA extraction, purification and genotyping. A clinical decision support system with integrated data from pharmacogenetic tests may enable personalized prescribing within primary care. Trial registration: ClinicalTrials.gov, NCT02383290. PMID:27730116

  19. Examining perceptions of the usefulness and usability of a mobile-based system for pharmacogenomics clinical decision support: a mixed methods study

    PubMed Central

    Blagec, Kathrin; Romagnoli, Katrina M.; Boyce, Richard D.

    2016-01-01

    Background. Pharmacogenomic testing has the potential to improve the safety and efficacy of pharmacotherapy, but clinical application of pharmacogenetic knowledge has remained uncommon. Clinical Decision Support (CDS) systems could help overcome some of the barriers to clinical implementation. The aim of this study was to evaluate the perception and usability of a web- and mobile-enabled CDS system for pharmacogenetics-guided drug therapy–the Medication Safety Code (MSC) system–among potential users (i.e., physicians and pharmacists). Furthermore, this study sought to collect data on the practicability and comprehensibility of potential layouts of a proposed personalized pocket card that is intended to not only contain the machine-readable data for use with the MSC system but also human-readable data on the patient’s pharmacogenomic profile. Methods. We deployed an emergent mixed methods design encompassing (1) qualitative interviews with pharmacists and pharmacy students, (2) a survey among pharmacogenomics experts that included both qualitative and quantitative elements and (3) a quantitative survey among physicians and pharmacists. The interviews followed a semi-structured guide including a hypothetical patient scenario that had to be solved by using the MSC system. The survey among pharmacogenomics experts focused on what information should be printed on the card and how this information should be arranged. Furthermore, the MSC system was evaluated based on two hypothetical patient scenarios and four follow-up questions on the perceived usability. The second survey assessed physicians’ and pharmacists’ attitude towards the MSC system. Results. In total, 101 physicians, pharmacists and PGx experts coming from various relevant fields evaluated the MSC system. Overall, the reaction to the MSC system was positive across all investigated parameters and among all user groups. The majority of participants were able to solve the patient scenarios based on the

  20. The Clinical Support Systems Program: supporting system-wide improvement.

    PubMed

    Leigh, Jenni A; Long, Paul W; Barraclough, Bruce H

    2004-05-17

    The Clinical Support Systems Program (CSSP) provided a mechanism for change from the existing entrenched structure and culture of patient care to one based on patient-centred, evidence-based care. The spectrum of change and improvement achieved by the CSSP was extensive, with support from government and active and enthusiastic involvement of clinical champions, practising clinicians, consumers and managers. The CSSP experience confirmed that responsibility for quality clinical care cannot be borne solely by clinicians, and highlighted key areas where improvement in the support clinicians receive is needed. Many barriers to improvement in our complex healthcare system can be removed by recognising the need for accurate data recording and data systems, teamwork, and high-level organisational buy-in, with collaboration between teams and organisations trying to improve the quality of patient care. System-wide improvement has been stimulated and facilitated by the CSSP experience, with mutual flow-on benefits for the activities of the Australian Council for Safety and Quality in Health Care and the National Institute of Clinical Studies. PMID:15139847

  1. Intention to adopt clinical decision support systems in a developing country: effect of Physician’s perceived professional autonomy, involvement and belief: a cross-sectional study

    PubMed Central

    2012-01-01

    Background Computer-based clinical decision support systems (CDSS) are regarded as a key element to enhance decision-making in a healthcare environment to improve the quality of medical care delivery. The concern of having new CDSS unused is still one of the biggest issues in developing countries for the developers and implementers of clinical IT systems. The main objectives of this study are to determine whether (1) the physician’s perceived professional autonomy, (2) involvement in the decision to implement CDSS and (3) the belief that CDSS will improve job performance increase the intention to adopt CDSS. Four hypotheses were formulated and tested. Methods A questionnaire-based survey conducted between July 2010 and December 2010. The study was conducted in seven public and five private hospitals in Kuala Lumpur, Malaysia. Before contacting the hospitals, necessary permission was obtained from the Ministry of Health, Malaysia and the questionnaire was vetted by the ethics committee of the ministry. Physicians working in 12 hospitals from 10 different specialties participated in the study. The sampling method used was stratified random sampling and the physicians were stratified based on the specialty. A total of 450 physicians were selected using a random number generator. Each of these physicians was given a questionnaire and out of 450 questionnaires, 335 (response rate – 74%) were returned and 309 (69%) were deemed usable. Results The hypotheses were tested using Structural Equation Modeling (SEM). Salient results are: (1) Physicians’ perceived threat to professional autonomy lowers the intention to use CDSS (p < 0.01); (2) Physicians involvement in the planning, design and implementation increases their intention to use CDSS (p < 0.01); (3) Physicians belief that the new CDSS will improve his/her job performance increases their intention to use CDSS (p < 0.01). Conclusion The proposed model with the three main constructs (physician’s professional

  2. New approaches for real time decision support systems

    NASA Technical Reports Server (NTRS)

    Hair, D. Charles; Pickslay, Kent

    1994-01-01

    NCCOSC RDT&E Division (NRaD) is conducting research into ways of improving decision support systems (DSS) that are used in tactical Navy decision making situations. The research has focused on the incorporation of findings about naturalistic decision-making processes into the design of the DSS. As part of that research, two computer tools were developed that model the two primary naturalistic decision-making strategies used by Navy experts in tactical settings. Current work is exploring how best to incorporate the information produced by those tools into an existing simulation of current Navy decision support systems. This work has implications for any applications involving the need to make decisions under time constraints, based on incomplete or ambiguous data.

  3. Group decision support system for customer-driven product design

    NASA Astrophysics Data System (ADS)

    Lin, Zhihang; Chen, Hang; Chen, Kuen; Che, Ada

    2000-10-01

    This paper describes the work on the development of a group decision support system for customer driven product design. The customer driven is to develop products, which meet all customer requirements in whole life cycle of products. A process model of decision during product primary design is proposed to formulate the structured, semi-structured and unstructured decision problems. The framework for the decision support system is presented that integrated both advances in the group decision making and distributed artificial intelligent. The system consists of the product primary design tool kit and the collaborative platform with multi-agent structure. The collaborative platform of the system and the product primary design tool kit, including the VOC (Voice of Customer) tool, QFD (Quality Function Deployment) tool, the Conceptual design tool, Reliability analysis tool and the cost and profit forecasting tool, are indicated.

  4. Clinical Decision Support for Whole Genome Sequence Information Leveraging a Service-Oriented Architecture: a Prototype

    PubMed Central

    Welch, Brandon M.; Rodriguez-Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku

    2014-01-01

    Whole genome sequence (WGS) information could soon be routinely available to clinicians to support the personalized care of their patients. At such time, clinical decision support (CDS) integrated into the clinical workflow will likely be necessary to support genome-guided clinical care. Nevertheless, developing CDS capabilities for WGS information presents many unique challenges that need to be overcome for such approaches to be effective. In this manuscript, we describe the development of a prototype CDS system that is capable of providing genome-guided CDS at the point of care and within the clinical workflow. To demonstrate the functionality of this prototype, we implemented a clinical scenario of a hypothetical patient at high risk for Lynch Syndrome based on his genomic information. We demonstrate that this system can effectively use service-oriented architecture principles and standards-based components to deliver point of care CDS for WGS information in real-time. PMID:25954430

  5. Periodicals collection management using a decision support system

    SciTech Connect

    Compton, M.L.; Moser, E.C.

    1993-12-31

    Sandia National Laboratories is a multiprogram national laboratory established in 1949. The Library currently uses DOBIS for its automated system, including the Periodicals Control function for periodical check-in. DOBIS performs processing and control functions adequately, but could not meet our reporting needs. Therefore the Library`s Periodicals Decision Team decided that they needed another ``system`` for collection management. A Periodicals Decision Support System was created using information downloaded from DOBIS and uploaded into dBASE IV. The Periodical Decision Support System functions as an information-processing system that has aided us in making collection management decisions for periodicals. It certainly allows us to do interactive ad-hoc analysis; although there are no modeling tools currently incorporated in the system. We hope that these modeling tools will come later. We have been gathering information and developing needed reports to achieve this goal.

  6. Decision Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability Perspective

    ERIC Educational Resources Information Center

    Erskine, Michael A.

    2013-01-01

    As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…

  7. Effects of a computerized provider order entry and a clinical decision support system to improve cefazolin use in surgical prophylaxis: a cost saving analysis

    PubMed Central

    Veroneze, Izelandia; Burgardt, Celia I.; Fragoso, Marta F.

    2016-01-01

    Background: Computerized Provider Order Entry (CPOE) and Clinical Decision Support System (CDSS) help practitioners to choose evidence-based decisions, regarding patients’ needs. Despite its use in developed countries, in Brazil, the impact of a CPOE/CDSS to improve cefazolin use in surgical prophylaxis was not assessed yet. Objective: We aimed to evaluate the impact of a CDSS to improve the use of prophylactic cefazolin and to assess the cost savings associated to inappropriate prescribing. Methods: This is a cross-sectional study that compared two different scenarios: one prior CPOE/CDSS versus after software implementation. We conducted twelve years of data analysis (3 years prior and 9 years after CDSS implementation), where main outcomes from this study included: cefazolin Defined Daily Doses/100 bed-days (DDD), crude costs and product of costs-DDD (cost-DDD/100 bed-days). We applied a Spearman rho non-parametric test to assess the reduction of cefazolin consumption through the years. Results: In twelve years, 84,383 vials of cefazolin were dispensed and represented 38.89 DDD/100 bed-days or USD 44,722.99. Surgical wards were the largest drug prescribers and comprised >95% of our studied sample. While in 2002, there were 6.31 DDD/100 bed-days, 9 years later there was a reduction to 2.15 (p<0.05). In a scenario without CDSS, the hospital would have consumed 75.72 DDD/100 bed-days, which is equivalent to USD 116 998.07. It is estimated that CDSS provided USD 50,433.39 of cost savings. Conclusion: The implementation of a CPOE/CDSS helped to improve prophylactic cefazolin use by reducing its consumption and estimated direct costs. PMID:27785159

  8. Consensus Recommendations for Systematic Evaluation of Drug-Drug Interaction Evidence for Clinical Decision Support

    PubMed Central

    Scheife, Richard T.; Hines, Lisa E.; Boyce, Richard D.; Chung, Sophie P.; Momper, Jeremiah; Sommer, Christine D.; Abernethy, Darrell R.; Horn, John; Sklar, Stephen J.; Wong, Samantha K.; Jones, Gretchen; Brown, Mary; Grizzle, Amy J.; Comes, Susan; Wilkins, Tricia Lee; Borst, Clarissa; Wittie, Michael A.; Rich, Alissa; Malone, Daniel C.

    2015-01-01

    Background Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. Objective To provide recommendations for systematic evaluation of evidence from the scientific literature, drug product labeling, and regulatory documents with respect to DDIs for clinical decision support. Methods A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 15 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. Results We developed expert-consensus answers to three key questions: 1) What is the best approach to evaluate DDI evidence?; 2) What evidence is required for a DDI to be applicable to an entire class of drugs?; and 3) How should a structured evaluation process be vetted and validated? Conclusion Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug information systems that implement these recommendations should be able to provide higher quality information about DDIs in drug compendia and clinical decision support tools. PMID:25556085

  9. Neighborhood graph and learning discriminative distance functions for clinical decision support.

    PubMed

    Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

    2009-01-01

    There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification. PMID:19964399

  10. Using Visualization in Cockpit Decision Support Systems

    SciTech Connect

    Aragon, Cecilia R.

    2005-07-01

    Beamline 7.2 of the Advanced Light Source (ALS) at the Lawrence Berkeley National Laboratory (LBNL) is a beam diagnostics system that uses the synchrotron radiation emitted by a dipole magnet. It consists of two branches; in the first one the x-ray portion of the radiation is used in a pinhole camera system for measuring the transverse profile of the beam. The second branch is equipped with an x-ray beam position monitor (BPM) and with a multipurpose port where the visible and the far-infrared part of the radiation can be used for various applications such as bunch length measurements and IR coherent synchrotron radiation experiments. The pinhole system has been operating successfully since the end of 2003. The installation of the second branch has been completed recently and the results of its commissioning are presented in this paper together with examples of beam measurements performed at BL 7.2.

  11. Perceived barriers of heart failure nurses and cardiologists in using clinical decision support systems in the treatment of heart failure patients

    PubMed Central

    2013-01-01

    Background Clinical Decision Support Systems (CDSSs) can support guideline adherence in heart failure (HF) patients. However, the use of CDSSs is limited and barriers in working with CDSSs have been described as a major obstacle. It is unknown if barriers to CDSSs are present and differ between HF nurses and cardiologists. Therefore the aims of this study are; 1. Explore the type and number of perceived barriers of HF nurses and cardiologists to use a CDSS in the treatment of HF patients. 2. Explore possible differences in perceived barriers between two groups. 3. Assess the relevance and influence of knowledge management (KM) on Responsibility/Trust (R&T) and Barriers/Threats (B&T). Methods A questionnaire was developed including; B&T, R&T, and KM. For analyses, descriptive techniques, 2-tailed Pearson correlation tests, and multiple regression analyses were performed. Results The response- rate of 220 questionnaires was 74%. Barriers were found for cardiologists and HF nurses in all the constructs. Sixty-five percent did not want to be dependent on a CDSS. Nevertheless thirty-six percent of HF nurses and 50% of cardiologists stated that a CDSS can optimize HF medication. No relationship between constructs and age; gender; years of work experience; general computer experience and email/internet were observed. In the group of HF nurses a positive correlation (r .33, P<.01) between years of using the internet and R&T was found. In both groups KM was associated with the constructs B&T (B=.55, P=<.01) and R&T (B=.50, P=<.01). Conclusions Both cardiologists and HF-nurses perceived barriers in working with a CDSS in all of the examined constructs. KM has a strong positive correlation with perceived barriers, indicating that increasing knowledge about CDSSs can decrease their barriers. PMID:23622342

  12. Developing a Decision Support System: The Software and Hardware Tools.

    ERIC Educational Resources Information Center

    Clark, Phillip M.

    1989-01-01

    Describes some of the available software and hardware tools that can be used to develop a decision support system implemented on microcomputers. Activities that should be supported by software are discussed, including data entry, data coding, finding and combining data, and data compatibility. Hardware considerations include speed, storage…

  13. Costs Associated with Implementation of Computer-Assisted Clinical Decision Support System for Antenatal and Delivery Care: Case Study of Kassena-Nankana District of Northern Ghana

    PubMed Central

    Dalaba, Maxwell Ayindenaba; Akweongo, Patricia; Williams, John; Saronga, Happiness Pius; Tonchev, Pencho; Sauerborn, Rainer; Mensah, Nathan; Blank, Antje; Kaltschmidt, Jens; Loukanova, Svetla

    2014-01-01

    Objective This study analyzed cost of implementing computer-assisted Clinical Decision Support System (CDSS) in selected health care centres in Ghana. Methods A descriptive cross sectional study was conducted in the Kassena-Nankana district (KND). CDSS was deployed in selected health centres in KND as an intervention to manage patients attending antenatal clinics and the labour ward. The CDSS users were mainly nurses who were trained. Activities and associated costs involved in the implementation of CDSS (pre-intervention and intervention) were collected for the period between 2009–2013 from the provider perspective. The ingredients approach was used for the cost analysis. Costs were grouped into personnel, trainings, overheads (recurrent costs) and equipment costs (capital cost). We calculated cost without annualizing capital cost to represent financial cost and cost with annualizing capital costs to represent economic cost. Results Twenty-two trained CDSS users (at least 2 users per health centre) participated in the study. Between April 2012 and March 2013, users managed 5,595 antenatal clients and 872 labour clients using the CDSS. We observed a decrease in the proportion of complications during delivery (pre-intervention 10.74% versus post-intervention 9.64%) and a reduction in the number of maternal deaths (pre-intervention 4 deaths versus post-intervention 1 death). The overall financial cost of CDSS implementation was US$23,316, approximately US$1,060 per CDSS user trained. Of the total cost of implementation, 48% (US$11,272) was pre-intervention cost and intervention cost was 52% (US$12,044). Equipment costs accounted for the largest proportion of financial cost: 34% (US$7,917). When economic cost was considered, total cost of implementation was US$17,128–lower than the financial cost by 26.5%. Conclusions The study provides useful information in the implementation of CDSS at health facilities to enhance health workers' adherence to practice guidelines

  14. VisualDecisionLinc: a visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry.

    PubMed

    Mane, Ketan K; Bizon, Chris; Schmitt, Charles; Owen, Phillips; Burchett, Bruce; Pietrobon, Ricardo; Gersing, Kenneth

    2012-02-01

    Comparative Effectiveness Research (CER) is designed to provide research evidence on the effectiveness and risks of different therapeutic options on the basis of data compiled from subpopulations of patients with similar medical conditions. Electronic Health Record (EHR) system contain large volumes of patient data that could be used for CER, but the data contained in EHR system are typically accessible only in formats that are not conducive to rapid synthesis and interpretation of therapeutic outcomes. In the time-pressured clinical setting, clinicians faced with large amounts of patient data in formats that are not readily interpretable often feel 'information overload'. Decision support tools that enable rapid access at the point of care to aggregate data on the most effective therapeutic outcomes derived from CER would greatly aid the clinical decision-making process and individualize patient care. In this manuscript, we highlight the role that visual analytics can play in CER-based clinical decision support. We developed a 'VisualDecisionLinc' (VDL) tool prototype that uses visual analytics to provide summarized CER-derived data views to facilitate rapid interpretation of large amounts of data. We highlight the flexibility that visual analytics offers to gain an overview of therapeutic options and outcomes and if needed, to instantly customize the evidence to the needs of the patient or clinician. The VDL tool uses visual analytics to help the clinician evaluate and understand the effectiveness and risk of different therapeutic options for different subpopulations of patients.

  15. The Contribution of a Decision Support System to Educational Decision-Making Processes

    ERIC Educational Resources Information Center

    Klein, Joseph; Ronen, Herman

    2003-01-01

    In the light of reports of bias, the present study investigated the hypothesis that administrative educational decisions assisted by Decision Support Systems (DSS) are characterized by different pedagogical and organizational orientation than decisions made without computer assistance. One hundred and ten high school teachers were asked to suggest…

  16. Requiring Clinical Justification to Override Repeat Imaging Decision Support: Impact on CT Use

    PubMed Central

    O’Connor, Stacy D.; Sodickson, Aaron D.; Ip, Ivan K.; Raja, Ali S.; Healey, Michael J.; Schneider, Louise I.; Khorasani, Ramin

    2014-01-01

    OBJECTIVE The purpose of this study was to determine the impact of requiring clinical justification to override decision support alerts on repeat use of CT. SUBJECTS AND METHODS This before and after intervention study was conducted at a 793-bed tertiary hospital with computerized physician order entry and clinical decision support systems. When a CT order is placed, decision support alerts the orderer if the patient’s same body part has undergone CT within the past 90 days. The study cohort included all 28,420 CT orders triggering a repeat alert in 2010. The intervention required clinical justification, selected from a predetermined menu, to override repeat CT decision support alerts to place a CT order; otherwise the order could not be placed and was dropped. The primary outcome, dropped repeat CT orders, was analyzed using three methods: chi-square tests to compare proportions dropped before and after intervention; multiple logistic regression tests to control for orderer, care setting, and patient factors; and statistical process control for temporal trends. RESULTS The repeat CT order drop rate had an absolute increase of 1.4%; 6.1% (682/11,230) before to 7.5% (1290/17,190) after intervention, which was a 23% relative change (7.5 – 6.1) / 6.1 × 100 = 23%; p < 0.0001). Orders were dropped more often after intervention (odds ratio, 1.3; 95% CI, 1.1–1.4; p < 0.0001). Statistical control analysis supported the association between the increase in the drop rate with intervention rather than underlying trends. CONCLUSION Adding a requirement for clinical justification to override alerts modestly but significantly improves the impact of repeat CT decision support (23% relative change), with the overall effect of preventing one in 13 repeat CT orders. PMID:25341162

  17. Application of GIS in foreign direct investment decision support system

    NASA Astrophysics Data System (ADS)

    Zhou, Jianlan; Sun, Koumei

    2007-06-01

    It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.

  18. On the heuristic nature of medical decision-support systems.

    PubMed

    Aliferis, C F; Miller, R A

    1995-03-01

    In the realm of medical decision-support systems, the term "heuristic systems" is often considered to be synonymous with "medical artificial intelligence systems" or with "systems employing informal model(s) of problem solving". Such a view may be inaccurate and possibly impede the conceptual development of future systems. This article examines the nature of heuristics and the levels at which heuristic solutions are introduced during system design and implementation. The authors discuss why heuristics are ubiquitous in all medical decision-support systems operating at non-trivial domains, and propose a unifying definition of heuristics that encompasses formal and ad hoc systems. System developers should be aware of the heuristic nature of all problem solving done in complex real world domains, and characterize their own use of heuristics in describing system development and implementation. PMID:9082138

  19. Recent developments associated with decision support systems in water resources

    NASA Astrophysics Data System (ADS)

    Watkins, David W.; McKinney, Daene C.

    1995-07-01

    In order to limit the scope of this review, a working definition of a decision support system is needed. L. Adelman has defined decision support systems (DSSs) as "interactive computer programs that utilize analytical methods, such as decision analysis, optimization algorithms, program scheduling routines, and so on, for developing models to help decision makers formulate alternatives, analyze their impacts, and interpret and select appropriate options for implementation" (Adelman [1992], p. 2). Another definition has been offered by S. J. Andriole, who defined decision support as consisting of "any and all data, information, expertise or activities that contribute to option selection" (Andriole [1989], p. 3). A common idea explicit in each of these definitions is that DSSs integrate various technologies and aid in option selection. Implicit in each definition is that these are options for solving relatively large, unstructured problems. Thus, the following working definition of a DSS will be used in this review: A DSS is an integrated, interactive computer system, consisting of analytical tools and information management capabilities, designed to aid decision makers in solving relatively large, unstructured problems.

  20. Automation, decision support, and expert systems in nephrology.

    PubMed

    Soman, Sandeep; Zasuwa, Gerard; Yee, Jerry

    2008-01-01

    Increasing data suggest that errors in medicine occur frequently and result in substantial harm to the patient. The Institute of Medicine report described the magnitude of the problem, and public interest in this issue, which was already large, has grown. The traditional approach in medicine has been to identify the persons making the errors and recommend corrective strategies. However, it has become increasingly clear that it is more productive to focus on the systems and processes through which care is provided. If these systems are set up in ways that would both make errors less likely and identify those that do occur and, at the same time, improve efficiency, then safety and productivity would be substantially improved. Clinical decision support systems (CDSSs) are active knowledge systems that use 2 or more items of patient data to generate case specific recommendations. CDSSs are typically designed to integrate a medical knowledge base, patient data, and an inference engine to generate case specific advice. This article describes how automation, templating, and CDSS improve efficiency, patient care, and safety by reducing the frequency and consequences of medical errors in nephrology. We discuss practical applications of these in 3 settings: a computerized anemia-management program (CAMP, Henry Ford Health System, Detroit, MI), vascular access surveillance systems, and monthly capitation notes in the hemodialysis unit.

  1. Decision Support Systems and the Conflict Model of Decision Making: A Stimulus for New Computer-Assisted Careers Guidance Systems.

    ERIC Educational Resources Information Center

    Ballantine, R. Malcolm

    Decision Support Systems (DSSs) are computer-based decision aids to use when making decisions which are partially amenable to rational decision-making procedures but contain elements where intuitive judgment is an essential component. In such situations, DSSs are used to improve the quality of decision-making. The DSS approach is based on Simon's…

  2. Group Decision Support Systems and Group Communication: A Comparison of Decision Making in Computer-Supported and Nonsupported Groups.

    ERIC Educational Resources Information Center

    Poole, Marshall Scott; And Others

    1993-01-01

    Explores the effects of Group Decision Support Systems (GDSS) on small group communication and decision-making processes. Finds that comparing GDSS, manual, and baseline conditions enables separation of effects resulting from procedural structures from those resulting from computerization. Results support some aspects of the research model and…

  3. Computerized decision support systems: improving patient safety in nephrology

    PubMed Central

    Chang, Jamison; Ronco, Claudio; Rosner, Mitchell H.

    2016-01-01

    Incorrect prescription and administration of medications account for a substantial proportion of medical errors in the USA, causing adverse drug events (ADEs) that result in considerable patient morbidity and enormous costs to the health-care system. Patients with chronic kidney disease or acute kidney injury often have impaired drug clearance as well as polypharmacy, and are therefore at increased risk of experiencing ADEs. Studies have demonstrated that recognition of these conditions is not uniform among treating physicians, and prescribed drug doses are often incorrect. Early interventions that ensure appropriate drug dosing in this group of patients have shown encouraging results. Both computerized physician order entry and clinical decision support systems have been shown to reduce the rate of ADEs. Nevertheless, these systems have been implemented at surprisingly few institutions. Economic stimulus and health-care reform legislation present a rare opportunity to refine these systems and understand how they could be implemented more widely. Failure to explore this technology could mean that the opportunity to reduce the morbidity associated with ADEs is missed. PMID:21502973

  4. A Decision Support System for Solving Multiple Criteria Optimization Problems

    ERIC Educational Resources Information Center

    Filatovas, Ernestas; Kurasova, Olga

    2011-01-01

    In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria…

  5. A decision support system for AIDS intervention and prevention.

    PubMed

    Xu, L D

    1994-08-01

    In recent years, the importance of information systems has been identified as a vital issue to continuing success in AIDS intervention and prevention (AIP). The advances in information technology have resulted in integrative information systems including decision support systems (DSS). The concept of DSS for AIP was created at the intersection of two trends. The first trend was a growing belief that AIP information systems are successful in automating operations in AIP programs. The second was a continuing improvement in modeling and software development in the AIP area. This paper presents an integrated DSS for AIP. The system is integrated with a database and achieves its efficiency by incorporating various algorithms and models to support AIP decision processes. The application examples include screening AIDS-risky behaviors, evaluating educational interventions, and scheduling AIP sessions. The implementation results present evidence of the usefulness of the system in AIP.

  6. Advances In Infection Surveillance and Clinical Decision Support With Fuzzy Sets and Fuzzy Logic.

    PubMed

    Koller, Walter; de Bruin, Jeroen S; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

    2015-01-01

    By the use of extended intelligent information technology tools for fully automated healthcare-associated infection (HAI) surveillance, clinicians can be informed and alerted about the emergence of infection-related conditions in their patients. Moni--a system for monitoring nosocomial infections in intensive care units for adult and neonatal patients--employs knowledge bases that were written with extensive use of fuzzy sets and fuzzy logic, allowing the inherent un-sharpness of clinical terms and the inherent uncertainty of clinical conclusions to be a part of Moni's output. Thus, linguistic as well as propositional uncertainty became a part of Moni, which can now report retrospectively on HAIs according to traditional crisp HAI surveillance definitions, as well as support clinical bedside work by more complex crisp and fuzzy alerts and reminders. This improved approach can bridge the gap between classical retrospective surveillance of HAIs and ongoing prospective clinical-decision-oriented HAI support.

  7. Decision Support Systems and Line Performance: Case of Gold Coast University Hospital.

    PubMed

    Connor, Martin; Ghapanchi, Amir Hossein; Blumenstein, Michael; Amrollahi, Alireza; Najaftorkaman, Mohammadreza

    2015-01-01

    Computer-based decision support information systems have been promoted for their potential to improve physician performance and patient outcomes and support clinical decision making. The current case study reported design and implementation of a high-level decision support system (DSS) which facilitated the flow of data from operational level to top managers and leadership level of hospitals. The results shows that development of a DSS improve data connectivity, timing, and responsiveness issues via centralised sourcing and storing of principal health-related information in the hospital. The implementation of the system has resulted in significant enhancements in outpatient waiting times management.

  8. Behavior-aware decision support systems : LDRD final report.

    SciTech Connect

    Hirsch, Gary B.; Homer, Jack; Chenoweth, Brooke N.; Backus, George A.; Strip, David R.

    2007-11-01

    As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.

  9. Improving the Slum Planning Through Geospatial Decision Support System

    NASA Astrophysics Data System (ADS)

    Shekhar, S.

    2014-11-01

    In India, a number of schemes and programmes have been launched from time to time in order to promote integrated city development and to enable the slum dwellers to gain access to the basic services. Despite the use of geospatial technologies in planning, the local, state and central governments have only been partially successful in dealing with these problems. The study on existing policies and programmes also proved that when the government is the sole provider or mediator, GIS can become a tool of coercion rather than participatory decision-making. It has also been observed that local level administrators who have adopted Geospatial technology for local planning continue to base decision-making on existing political processes. In this juncture, geospatial decision support system (GSDSS) can provide a framework for integrating database management systems with analytical models, graphical display, tabular reporting capabilities and the expert knowledge of decision makers. This assists decision-makers to generate and evaluate alternative solutions to spatial problems. During this process, decision-makers undertake a process of decision research - producing a large number of possible decision alternatives and provide opportunities to involve the community in decision making. The objective is to help decision makers and planners to find solutions through a quantitative spatial evaluation and verification process. The study investigates the options for slum development in a formal framework of RAY (Rajiv Awas Yojana), an ambitious program of Indian Government for slum development. The software modules for realizing the GSDSS were developed using the ArcGIS and Community -VIZ software for Gulbarga city.

  10. Discriminative distance functions and the patient neighborhood graph for clinical decision support.

    PubMed

    Tsymbal, Alexey; Huber, Martin; Zhou, Shaohua Kevin

    2010-01-01

    There are two essential reasons for the slow progress in the acceptance of clinical similarity search-based decision support systems (DSSs); the especial complexity of biomedical data making it difficult to define a meaningful and effective distance function and the lack of transparency and explanation ability in many existing DSSs. In this chapter, we address these two problems by introducing a novel technique for visualizing patient similarity with neighborhood graphs and by considering two techniques for learning discriminative distance functions. We present an experimental study and discuss our implementation of similarity visualization within a clinical DSS. PMID:20865536

  11. A programmable rules engine to provide clinical decision support using HTML forms.

    PubMed

    Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

    1999-01-01

    The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

  12. Advancing clinical decision support using lessons from outside of healthcare: an interdisciplinary systematic review

    PubMed Central

    2012-01-01

    Background Greater use of computerized decision support (DS) systems could address continuing safety and quality problems in healthcare, but the healthcare field has struggled to implement DS technology. This study surveys DS experience across multiple non-healthcare disciplines for new insights that are generalizable to healthcare provider decisions. In particular, it sought design principles and lessons learned from the other disciplines that could inform efforts to accelerate the adoption of clinical decision support (CDS). Methods Our systematic review drew broadly from non-healthcare databases in the basic sciences, social sciences, humanities, engineering, business, and defense: PsychINFO, BusinessSource Premier, Social Sciences Abstracts, Web of Science, and Defense Technical Information Center. Because our interest was in DS that could apply to clinical decisions, we selected articles that (1) provided a review, overview, discussion of lessons learned, or an evaluation of design or implementation aspects of DS within a non-healthcare discipline and (2) involved an element of human judgment at the individual level, as opposed to decisions that can be fully automated or that are made at the organizational level. Results Clinical decisions share some similarities with decisions made by military commanders, business managers, and other leaders: they involve assessing new situations and choosing courses of action with major consequences, under time pressure, and with incomplete information. We identified seven high-level DS system design features from the non-healthcare literature that could be applied to CDS: providing broad, system-level perspectives; customizing interfaces to specific users and roles; making the DS reasoning transparent; presenting data effectively; generating multiple scenarios covering disparate outcomes (e.g., effective; effective with side effects; ineffective); allowing for contingent adaptations; and facilitating collaboration. The

  13. A Decision Support System for Optimum Use of Fertilizers

    SciTech Connect

    R. L. Hoskinson; J. R. Hess; R. K. Fink

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

  14. Needs assessment for diagnostic decision support systems (DDSS).

    PubMed Central

    Berner, E. S.; Shugerman, A. A.

    1991-01-01

    Diagnostic decision support systems are often developed without a clear idea of how well the system will meet the needs of its users. The present study was designed to assess the information needs of clinicians. A set of questions submitted to an information service by family physicians was used to determine how much need there was for diagnostic decision support, the types of support needed, and the general content areas of their questions. Results showed that less than half of the questions were related to diagnosis and that most of those were requests for general information about a given condition. In addition, the fewest diagnosis questions were for conditions that were seen frequently in ambulatory care in a survey of family practitioners. PMID:1807674

  15. Quantitative ultrasound texture analysis for clinical decision making support

    NASA Astrophysics Data System (ADS)

    Wu, Jie Ying; Beland, Michael; Konrad, Joseph; Tuomi, Adam; Glidden, David; Grand, David; Merck, Derek

    2015-03-01

    We propose a general ultrasound (US) texture-analysis and machine-learning framework for detecting the presence of disease that is suitable for clinical application across clinicians, disease types, devices, and operators. Its stages are image selection, image filtering, ROI selection, feature parameterization, and classification. Each stage is modular and can be replaced with alternate methods. Thus, this framework is adaptable to a wide range of tasks. Our two preliminary clinical targets are hepatic steatosis and adenomyosis diagnosis. For steatosis, we collected US images from 288 patients and their pathology-determined values of steatosis (%) from biopsies. Two radiologists independently reviewed all images and identified the region of interest (ROI) most representative of the hepatic echotexture for each patient. To parameterize the images into comparable quantities, we filter the US images at multiple scales for various texture responses. For each response, we collect a histogram of pixel features within the ROI, and parameterize it as a Gaussian function using its mean, standard deviation, kurtosis, and skew to create a 36-feature vector. Our algorithm uses a support vector machine (SVM) for classification. Using a threshold of 10%, we achieved 72.81% overall accuracy, 76.18% sensitivity, and 65.96% specificity in identifying steatosis with leave-ten-out cross-validation (p<0.0001). Extending this framework to adenomyosis, we identified 38 patients with MR-confirmed findings of adenomyosis and previous US studies and 50 controls. A single rater picked the best US-image and ROI for each case. Using the same processing pipeline, we obtained 76.14% accuracy, 86.00% sensitivity, and 63.16% specificity with leave-one-out cross-validation (p<0.0001).

  16. A Decision Support System for Concrete Bridge Maintenance

    NASA Astrophysics Data System (ADS)

    Rashidi, Maria; Lemass, Brett; Gibson, Peter

    2010-05-01

    The maintenance of bridges as a key element in transportation infrastructure has become a major concern for asset managers and society due to increasing traffic volumes, deterioration of existing bridges and well-publicised bridge failures. A pivotal responsibility for asset managers in charge of bridge remediation is to identify the risks and assess the consequences of remediation programs to ensure that the decisions are transparent and lead to the lowest predicted losses in recognized constraint areas. The ranking of bridge remediation treatments can be quantitatively assessed using a weighted constraint approach to structure the otherwise ill-structured phases of problem definition, conceptualization and embodiment [1]. This Decision Support System helps asset managers in making the best decision with regards to financial limitations and other dominant constraints imposed upon the problem at hand. The risk management framework in this paper deals with the development of a quantitative intelligent decision support system for bridge maintenance which has the ability to provide a source for consistent decisions through selecting appropriate remediation treatments based upon cost, service life, product durability/sustainability, client preferences, legal and environmental constraints. Model verification and validation through industry case studies is ongoing.

  17. Enabling health care decisionmaking through clinical decision support and knowledge management.

    PubMed Central

    Lobach, David; Sanders, Gillian D; Bright, Tiffani J; Wong, Anthony; Dhurjati, Ravi; Bristow, Erin; Bastian, Lori; Coeytaux, Remy; Samsa, Gregory; Hasselblad, Vic; Williams, John W; Wing, Liz; Musty, Michael; Kendrick, Amy S

    2012-01-01

    OBJECTIVES To catalogue study designs used to assess the clinical effectiveness of CDSSs and KMSs, to identify features that impact the success of CDSSs/KMSs, to document the impact of CDSSs/KMSs on outcomes, and to identify knowledge types that can be integrated into CDSSs/KMSs. DATA SOURCES MEDLINE(®), CINAHL(®), PsycINFO(®), and Web of Science(®). REVIEW METHODS We included studies published in English from January 1976 through December 2010. After screening titles and abstracts, full-text versions of articles were reviewed by two independent reviewers. Included articles were abstracted to evidence tables by two reviewers. Meta-analyses were performed for seven domains in which sufficient studies with common outcomes were included. RESULTS We identified 15,176 articles, from which 323 articles describing 311 unique studies including 160 reports on 148 randomized control trials (RCTs) were selected for inclusion. RCTs comprised 47.5 percent of the comparative studies on CDSSs/KMSs. Both commercially and locally developed CDSSs effectively improved health care process measures related to performing preventive services (n = 25; OR 1.42, 95% confidence interval [CI] 1.27 to 1.58), ordering clinical studies (n = 20; OR 1.72, 95% CI 1.47 to 2.00), and prescribing therapies (n = 46; OR 1.57, 95% CI 1.35 to 1.82). Fourteen CDSS/KMS features were assessed for correlation with success of CDSSs/KMSs across all endpoints. Meta-analyses identified six new success features: Integration with charting or order entry system. Promotion of action rather than inaction. No need for additional clinician data entry. Justification of decision support via research evidence. Local user involvement. Provision of decision support results to patients as well as providers. Three previously identified success features were confirmed: Automatic provision of decision support as part of clinician workflow. Provision of decision support at time and location of decisionmaking. Provision of a

  18. From clinical requirement to personalized wellness decision support: a data-driven framework for computer-supported guideline refinement.

    PubMed

    Hsueh, Pei-Yun; Lan, Ci-Wei; Deng, Vincent; Zhu, Xinxin

    2012-01-01

    Personalized wellness decision support has gained significant attention, owing to the shift to a patient-centric paradigm in healthcare domains, and the consequent availability of a wealth of patient-related data. Despite the success of data-driven analytics in improving practice outcome, there is a gap towards their deployment in guideline-based practice. In this paper we report on findings related to computer-supported guideline refinement, which maps a patient's guideline requirements to personalized recommendations that suit the patient's current context. In particular, we present a novel data-driven personalization framework, casting the mapping task as a statistical decision problem in search of a solution to maximize expected utility. The proposed framework is well suited to produce personalized recommendations based on not only clinical factors but contextual factors that reflect individual differences in non-clinical settings. We then describe its implementation within the guideline-based clinical decision support system and discuss opportunities and challenges looking forward. PMID:22874232

  19. From clinical requirement to personalized wellness decision support: a data-driven framework for computer-supported guideline refinement.

    PubMed

    Hsueh, Pei-Yun; Lan, Ci-Wei; Deng, Vincent; Zhu, Xinxin

    2012-01-01

    Personalized wellness decision support has gained significant attention, owing to the shift to a patient-centric paradigm in healthcare domains, and the consequent availability of a wealth of patient-related data. Despite the success of data-driven analytics in improving practice outcome, there is a gap towards their deployment in guideline-based practice. In this paper we report on findings related to computer-supported guideline refinement, which maps a patient's guideline requirements to personalized recommendations that suit the patient's current context. In particular, we present a novel data-driven personalization framework, casting the mapping task as a statistical decision problem in search of a solution to maximize expected utility. The proposed framework is well suited to produce personalized recommendations based on not only clinical factors but contextual factors that reflect individual differences in non-clinical settings. We then describe its implementation within the guideline-based clinical decision support system and discuss opportunities and challenges looking forward.

  20. A Decision Support System for Optimum Use of Fertilizers

    SciTech Connect

    Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

  1. Middle Mississippi River decision support system: user's manual

    USGS Publications Warehouse

    Rohweder, Jason J.; Zigler, Steven J.; Fox, Timothy J.; Hulse, Steven N.

    2005-01-01

    This user's manual describes the Middle Mississippi River Decision Support System (MMRDSS) and gives detailed examples on its use. The MMRDSS provides a framework to assist decision makers regarding natural resource issues in the Middle Mississippi River floodplain. The MMRDSS is designed to provide users with a spatially explicit tool for tasks, such as inventorying existing knowledge, developing models to investigate the potential effects of management decisions, generating hypotheses to advance scientific understanding, and developing scientifically defensible studies and monitoring. The MMRDSS also includes advanced tools to assist users in evaluating differences in complexity, connectivity, and structure of aquatic habitats among river reaches. The Environmental Systems Research Institute ArcView 3.x platform was used to create and package the data and tools of the MMRDSS.

  2. Decision Support Systems for Research and Management in Advanced Life Support

    NASA Technical Reports Server (NTRS)

    Rodriquez, Luis F.

    2004-01-01

    Decision support systems have been implemented in many applications including strategic planning for battlefield scenarios, corporate decision making for business planning, production planning and control systems, and recommendation generators like those on Amazon.com(Registered TradeMark). Such tools are reviewed for developing a similar tool for NASA's ALS Program. DSS are considered concurrently with the development of the OPIS system, a database designed for chronicling of research and development in ALS. By utilizing the OPIS database, it is anticipated that decision support can be provided to increase the quality of decisions by ALS managers and researchers.

  3. A Proposed Clinical Decision Support Architecture Capable of Supporting Whole Genome Sequence Information

    PubMed Central

    Welch, Brandon M.; Rodriguez Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku

    2014-01-01

    Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine. PMID:25411644

  4. Use of Simulation to Study Nurses' Acceptance and Nonacceptance of Clinical Decision Support Suggestions.

    PubMed

    Sousa, Vanessa E C; Lopez, Karen Dunn; Febretti, Alessandro; Stifter, Janet; Yao, Yingwei; Johnson, Andrew; Wilkie, Diana J; Keenan, Gail M

    2015-10-01

    Our long-term goal was to ensure nurse clinical decision support works as intended before full deployment in clinical practice. As part of a broader effort, this pilot project explored factors influencing acceptance/nonacceptance of eight clinical decision support suggestions displayed in an electronic health record-based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high-fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the clinical decision support suggestions. Of 168 total suggestions displayed during the experiment (eight for each of the 21 nurses), 123 (73.2%) were accepted, and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was seven of eight, with only two of 21 nurses accepting all. The main reason for clinical decision support acceptance was the nurse's belief that the suggestions were good for the patient (100%), with other features providing secondary reinforcement. Reasons for nonacceptance were less clear, with fewer than half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high-quality simulation and targeted questionnaires about specific clinical decision support selections offer a cost-effective means for testing before full deployment in clinical practice. PMID:26361268

  5. Development of a Decision Support System to Predict Physicians' Rehabilitation Protocols for Patients with Knee Osteoarthritis

    ERIC Educational Resources Information Center

    Hawamdeh, Ziad M.; Alshraideh, Mohammad A.; Al-Ajlouni, Jihad M.; Salah, Imad K.; Holm, Margo B.; Otom, Ali H.

    2012-01-01

    To design a medical decision support system (MDSS) that would accurately predict the rehabilitation protocols prescribed by the physicians for patients with knee osteoarthritis (OA) using only their demographic and clinical characteristics. The demographic and clinical variables for 170 patients receiving one of three treatment protocols for knee…

  6. Integrating Clinical Decision Support into EMR and PHR: a Case Study Using Anticoagulation.

    PubMed

    Chackery, Dave-Gregory; Keshavjee, Karim; Mirza, Kashif; Ghany, Ahmad; Holbrook, Anne M

    2015-01-01

    Clinical decision support (CDS) for atrial fibrillation is expected to ease the implementation of often-complex guidelines for atrial fibrillation and anticoagulation. Most clinical decision support systems (CDSS) for anticoagulation are stand-alone systems that do not integrate with electronic medical records (EMR). We have developed an architecture that consists of a computerized CDS that can integrate with multiple EMRs and multiple patient health records (PHRs). The design process revealed some significant issues that were resolved through systematic business/clinical analysis and creative clinical design in the diagnostic and treatment domains. Key issues identified and resolved include: 1) how to correctly allocate existing patients into various CDSS states (e.g., MAINTENANCE, HOLD, DISCONTINUE, etc), 2) identify when a patient becomes eligible for CDSS guidance over time, 3) how the CDSS maintains information about the patient's anticoagulation state and 4) how to transform vague human-readable concepts to explicit computable concepts. The management of anticoagulation for atrial fibrillation is no easy task and we believe our architecture will improve patient care at all levels and ultimately better balance the reduction of stroke risk while minimizing harms from major bleeding. In addition, the architecture presented is scalable to other treatment guidelines and is scalable to multiple EMRs and PHRs, making it suitable for use in a platform approach. PMID:25676955

  7. Disaster Management with a Next Generation Disaster Decision Support System

    NASA Astrophysics Data System (ADS)

    Chen, Y.

    2015-12-01

    As populations become increasingly concentrated in large cities, the world is experiencing an inevitably growing trend towards the urbanisation of disasters. Scientists have contributed significant advances in understanding the geophysical causes of natural hazards and have developed sophisticated tools to predict their effects; while, much less attention has been devoted to tools that increase situational awareness, facilitate leadership, provide effective communication channels and data flow and enhance the cognitive abilities of decision makers and first responders. In this paper, we envisioned the capabilities of a next generation disaster decision support system and hence proposed a state-of-the-art system architecture design to facilitate the decision making process in natural catastrophes such as flood and bushfire by utilising a combination of technologies for multi-channel data aggregation, disaster modelling, visualisation and optimisation. Moreover, we put our thoughts into action by implementing an Intelligent Disaster Decision Support System (IDDSS). The developed system can easily plug in to external disaster models and aggregate large amount of heterogeneous data from government agencies, sensor networks, and crowd sourcing platforms in real-time to enhance the situational awareness of decision makers and offer them a comprehensive understanding of disaster impacts from diverse perspectives such as environment, infrastructure and economy, etc. Sponsored by the Australian Government and the Victorian Department of Justice (Australia), the system was built upon a series of open-source frameworks (see attached figure) with four key components: data management layer, model application layer, processing service layer and presentation layer. It has the potential to be adopted by a range of agencies across Australian jurisdictions to assist stakeholders in accessing, sharing and utilising available information in their management of disaster events.

  8. Healthcare Decision Support System for Administration of Chronic Diseases

    PubMed Central

    Woo, Ji-In; Yang, Jung-Gi; Lee, Young-Ho

    2014-01-01

    Objectives A healthcare decision-making support model and rule management system is proposed based on a personalized rule-based intelligent concept, to effectively manage chronic diseases. Methods A Web service was built using a standard message transfer protocol for interoperability of personal health records among healthcare institutions. An intelligent decision service is provided that analyzes data using a service-oriented healthcare rule inference function and machine-learning platform; the rules are extensively compiled by physicians through a developmental user interface that enables knowledge base construction, modification, and integration. Further, screening results are visualized for the self-intuitive understanding of personal health status by patients. Results A recommendation message is output through the Web service by receiving patient information from the hospital information recording system and object attribute values as input factors. The proposed system can verify patient behavior by acting as an intellectualized backbone of chronic diseases management; further, it supports self-management and scheduling of screening. Conclusions Chronic patients can continuously receive active recommendations related to their healthcare through the rule management system, and they can model the system by acting as decision makers in diseases management; secondary diseases can be prevented and health management can be performed by reference to patient-specific lifestyle guidelines. PMID:25152830

  9. Automatic system testing of a decision support system for insulin dosing using Google Android.

    PubMed

    Spat, Stephan; Höll, Bernhard; Petritsch, Georg; Schaupp, Lukas; Beck, Peter; Pieber, Thomas R

    2013-01-01

    Hyperglycaemia in hospitalized patients is a common and costly health care problem. The GlucoTab system is a mobile workflow and decision support system, aiming to facilitate efficient and safe glycemic control of non-critically ill patients. Being a medical device, the GlucoTab requires extensive and reproducible testing. A framework for high-volume, reproducible and automated system testing of the GlucoTab system was set up applying several Open Source tools for test automation and system time handling. The REACTION insulin titration protocol was investigated in a paper-based clinical trial (PBCT). In order to validate the GlucoTab system, data from this trial was used for simulation and system tests. In total, 1190 decision support action points were identified and simulated. Four data points (0.3%) resulted in a GlucoTab system error caused by a defective implementation. In 144 data points (12.1%), calculation errors of physicians and nurses in the PBCT were detected. The test framework was able to verify manual calculation of insulin doses and detect relatively many user errors and workflow anomalies in the PBCT data. This shows the high potential of the electronic decision support application to improve safety of implementation of an insulin titration protocol and workflow management system in clinical wards. PMID:23542995

  10. Use of decision support systems as a drought management tool

    USGS Publications Warehouse

    Frevert, D.; Lins, H.; ,

    2005-01-01

    Droughts present a unique challenge to water managers throughout the world and the current drought in the western United States is taxing facilities to the limit. Coping with this severe drought requires state of the art decision support systems including efficient and accurate hydrologic process models, detailed hydrologic data bases and effective river systems management modeling frameworks. This paper will outline a system of models developed by the Bureau of Reclamation, the US Geological Survey, the University of Colorado and a number of other governmental and university partners. The application of the technology to drought management in several key western river basins will be discussed.

  11. Visual Cluster Analysis in Support of Clinical Decision Intelligence

    PubMed Central

    Gotz, David; Sun, Jimeng; Cao, Nan; Ebadollahi, Shahram

    2011-01-01

    Electronic health records (EHRs) contain a wealth of information about patients. In addition to providing efficient and accurate records for individual patients, large databases of EHRs contain valuable information about overall patient populations. While statistical insights describing an overall population are beneficial, they are often not specific enough to use as the basis for individualized patient-centric decisions. To address this challenge, we describe an approach based on patient similarity which analyzes an EHR database to extract a cohort of patient records most similar to a specific target patient. Clusters of similar patients are then visualized to allow interactive visual refinement by human experts. Statistics are then extracted from the refined patient clusters and displayed to users. The statistical insights taken from these refined clusters provide personalized guidance for complex decisions. This paper focuses on the cluster refinement stage where an expert user must interactively (a) judge the quality and contents of automatically generated similar patient clusters, and (b) refine the clusters based on his/her expertise. We describe the DICON visualization tool which allows users to interactively view and refine multidimensional similar patient clusters. We also present results from a preliminary evaluation where two medical doctors provided feedback on our approach. PMID:22195102

  12. Laboratory Medicine in the Clinical Decision Support for Treatment of Hypercholesterolemia: Pharmacogenetics of Statins.

    PubMed

    Ruaño, Gualberto; Seip, Richard; Windemuth, Andreas; Wu, Alan H B; Thompson, Paul D

    2016-09-01

    Statin responsiveness is an area of great research interest given the success of the drug class in the treatment of hypercholesterolemia and in primary and secondary prevention of cardiovascular disease. Interrogation of the patient's genome for gene variants will eventually guide anti-hyperlipidemic intervention. In this review, we discuss methodological approaches to discover genetic markers predictive of class-wide and drug-specific statin efficacy and safety. Notable pharmacogenetic findings are summarized from hypothesis-free genome wide and hypothesis-led candidate gene association studies. Physiogenomic models and clinical decision support systems will be required for DNA-guided statin therapy to reach practical use in medicine. PMID:27514463

  13. Laboratory Medicine in the Clinical Decision Support for Treatment of Hypercholesterolemia: Pharmacogenetics of Statins.

    PubMed

    Ruaño, Gualberto; Seip, Richard; Windemuth, Andreas; Wu, Alan H B; Thompson, Paul D

    2016-09-01

    Statin responsiveness is an area of great research interest given the success of the drug class in the treatment of hypercholesterolemia and in primary and secondary prevention of cardiovascular disease. Interrogation of the patient's genome for gene variants will eventually guide anti-hyperlipidemic intervention. In this review, we discuss methodological approaches to discover genetic markers predictive of class-wide and drug-specific statin efficacy and safety. Notable pharmacogenetic findings are summarized from hypothesis-free genome wide and hypothesis-led candidate gene association studies. Physiogenomic models and clinical decision support systems will be required for DNA-guided statin therapy to reach practical use in medicine.

  14. Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

    PubMed

    Dolan, James G

    2010-01-01

    Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

  15. Human-Computer Interaction with Medical Decisions Support Systems

    NASA Technical Reports Server (NTRS)

    Adolf, Jurine A.; Holden, Kritina L.

    1994-01-01

    Decision Support Systems (DSSs) have been available to medical diagnosticians for some time, yet their acceptance and use have not increased with advances in technology and availability of DSS tools. Medical DSSs will be necessary on future long duration space missions, because access to medical resources and personnel will be limited. Human-Computer Interaction (HCI) experts at NASA's Human Factors and Ergonomics Laboratory (HFEL) have been working toward understanding how humans use DSSs, with the goal of being able to identify and solve the problems associated with these systems. Work to date consists of identification of HCI research areas, development of a decision making model, and completion of two experiments dealing with 'anchoring'. Anchoring is a phenomenon in which the decision maker latches on to a starting point and does not make sufficient adjustments when new data are presented. HFEL personnel have replicated a well-known anchoring experiment and have investigated the effects of user level of knowledge. Future work includes further experimentation on level of knowledge, confidence in the source of information and sequential decision making.

  16. A decision support system for assessing landfill performance.

    PubMed

    Celik, Başak; Girgin, Sertan; Yazici, Adnan; Unlü, Kahraman

    2010-01-01

    Designing environmentally sound landfills is a challenging engineering task due to complex interactions of numerous design variables; such as landfill size, waste characteristics, and site hydrogeology. Decision support systems (DSS) can be utilized to handle these complex interactions and to aid in a performance-based landfill design by coupling system simulation models (SSM). The aim of this paper is to present a decision support system developed for a performance-based landfill design. The developed DSS is called Landfill Design Decision Support System - LFDSS. A two-step DSS framework, composed of preliminary design and detailed design phases, is set to effectively couple and run the SSMs and calculation modules. In preliminary design phase, preliminary design alternatives are proposed using general site data. In detailed design phase, proposed design alternatives are further simulated under site-specific data using SSMs for performance evaluation. LFDSS calculates the required landfill volume, performs landfill base contour design, proposes preliminary design alternatives based on general site conditions, evaluates the performance of the proposed designs, calculates the factor of safety values for slope stability analyses, and performs major cost calculations. The DSS evaluates the results of all landfill design alternatives, and determines whether the design satisfies the predefined performance criteria. The DSS ultimately enables comparisons among different landfill designs based on their performances (i.e. leachate head stability, and groundwater contamination), constructional stability and costs. The developed DSS was applied to a real site, and the results demonstrated the strengths of the developed system on designing environmentally sound and feasible landfills.

  17. A decision support system for assessing landfill performance

    SciTech Connect

    Celik, Basak; Girgin, Sertan; Yazici, Adnan; Unlue, Kahraman

    2010-01-15

    Designing environmentally sound landfills is a challenging engineering task due to complex interactions of numerous design variables; such as landfill size, waste characteristics, and site hydrogeology. Decision support systems (DSS) can be utilized to handle these complex interactions and to aid in a performance-based landfill design by coupling system simulation models (SSM). The aim of this paper is to present a decision support system developed for a performance-based landfill design. The developed DSS is called Landfill Design Decision Support System - LFDSS. A two-step DSS framework, composed of preliminary design and detailed design phases, is set to effectively couple and run the SSMs and calculation modules. In preliminary design phase, preliminary design alternatives are proposed using general site data. In detailed design phase, proposed design alternatives are further simulated under site-specific data using SSMs for performance evaluation. LFDSS calculates the required landfill volume, performs landfill base contour design, proposes preliminary design alternatives based on general site conditions, evaluates the performance of the proposed designs, calculates the factor of safety values for slope stability analyses, and performs major cost calculations. The DSS evaluates the results of all landfill design alternatives, and determines whether the design satisfies the predefined performance criteria. The DSS ultimately enables comparisons among different landfill designs based on their performances (i.e. leachate head stability, and groundwater contamination), constructional stability and costs. The developed DSS was applied to a real site, and the results demonstrated the strengths of the developed system on designing environmentally sound and feasible landfills.

  18. Patient electronic health data-driven approach to clinical decision support.

    PubMed

    Mane, Ketan K; Bizon, Chris; Owen, Phillips; Gersing, Ken; Mostafa, Javed; Schmitt, Charles

    2011-10-01

    This article presents a novel visual analytics (VA)-based clinical decision support (CDS) tool prototype that was designed as a collaborative work between Renaissance Computing Institute and Duke University. Using Major Depressive Disorder data from MindLinc electronic health record system at Duke, the CDS tool shows an approach to leverage data from comparative population (patients with similar medical profile) to enhance a clinicians' decision making process at the point of care. The initial work is being extended in collaboration with the University of North Carolina CTSA to address the key challenges of CDS, as well as to show the use of VA to derive insight from large volumes of Electronic Health Record patient data.

  19. Decision support system for the operating room rescheduling problem.

    PubMed

    van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J

    2012-12-01

    Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

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

    PubMed

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

    2015-01-01

    Clinical Decision Support Systems (CDSS) help to improve health care and reduce costs. However, the lack of knowledge management and modelling hampers their maintenance and reuse. Current EHR standards and terminologies can allow the semantic representation of the data and knowledge of CDSS systems boosting their interoperability, reuse and maintenance. This paper presents the modelling process of respiratory conditions' symptoms and signs by a multidisciplinary team of clinicians and information architects with the help of openEHR, SNOMED and clinical information modelling tools for a CDSS. The information model of the CDSS was defined by means of an archetype and the knowledge model was implemented by means of an SNOMED-CT based ontology. PMID:25991115

  1. How Turing and Wolf influenced my Decision Support Systems.

    PubMed

    Richards, Bernard

    2013-01-01

    Decision Support Systems (DSS) have a vital role to play in today's scenario for Patient Care. They can embody a vast knowledge not normally found in one individual where diagnosis and treatment are involved. This paper highlights the training in minute details and precise mathematics needed in a successful DSS and indicates how such attention-to-detail was instilled into the writer as a result of working with Alan Turing and Emil Wolf who have both since achieved world-wide recognition in their own fields as a result of international publicity by the current writer. The article discusses four Decision Support Systems written by the present writer all of which have been shown to improve patient treatment and care, and which are of such complexity that, without their use, patient care would fall short of optimum. The Systems considered are those for Intensive Care Units, Cardiovascular Surgery, a Programmed Investigation Unit, and Diagnosis of Congenital Abnormalities. All these Systems have performed better than the human alternatives and have shown their value in the improvement of patient care.

  2. How Turing and Wolf influenced my Decision Support Systems.

    PubMed

    Richards, Bernard

    2013-01-01

    Decision Support Systems (DSS) have a vital role to play in today's scenario for Patient Care. They can embody a vast knowledge not normally found in one individual where diagnosis and treatment are involved. This paper highlights the training in minute details and precise mathematics needed in a successful DSS and indicates how such attention-to-detail was instilled into the writer as a result of working with Alan Turing and Emil Wolf who have both since achieved world-wide recognition in their own fields as a result of international publicity by the current writer. The article discusses four Decision Support Systems written by the present writer all of which have been shown to improve patient treatment and care, and which are of such complexity that, without their use, patient care would fall short of optimum. The Systems considered are those for Intensive Care Units, Cardiovascular Surgery, a Programmed Investigation Unit, and Diagnosis of Congenital Abnormalities. All these Systems have performed better than the human alternatives and have shown their value in the improvement of patient care. PMID:23542962

  3. A Framework for Decision Support Systems Based on Zachman Framework

    NASA Astrophysics Data System (ADS)

    Ostadzadeh, S. Shervin; Habibi, Jafar; Ostadzadeh, S. Arash

    Recent challenges have brought about an inevitable tendency for enterprises to lunge towards organizing their information activities in a comprehensive way. In this respect, Enterprise Architecture (EA) has proven to be the leading option for development and maintenance of information systems. EA clearly provides a thorough outline of the whole information system comprising an enterprise. To establish such an outline, a logical framework needs to be laid upon the entire information system. Zachman framework (ZF) has been widely accepted as a standard scheme for identifying and organizing descriptive representations that have critical roles in enterprise management and system development. In this paper, we propose a framework based on ZF for Decision Support Systems (DSS). Furthermore, a modeling approach based on Model-Driven Architecture (MDA) is utilized to obtain compatible models for all cells in the framework. The efficiency of the proposed framework is examined through a case study.

  4. Development and Validation of a Clinical and Computerised Decision Support System for Management of Hypertension (DSS-HTN) at a Primary Health Care (PHC) Setting

    PubMed Central

    Anchala, Raghupathy; Di Angelantonio, Emanuele; Prabhakaran, Dorairaj; Franco, Oscar H.

    2013-01-01

    Background Hypertension remains the top global cause of disease burden. Decision support systems (DSS) could provide an adequate and cost-effective means to improve the management of hypertension at a primary health care (PHC) level in a developing country, nevertheless evidence on this regard is rather limited. Methods Development of DSS software was based on an algorithmic approach for (a) evaluation of a hypertensive patient, (b) risk stratification (c) drug management and (d) lifestyle interventions, based on Indian guidelines for hypertension II (2007). The beta testing of DSS software involved a feedback from the end users of the system on the contents of the user interface. Software validation and piloting was done in field, wherein the virtual recommendations and advice given by the DSS were compared with two independent experts (government doctors from the non-participating PHC centers). Results The overall percent agreement between the DSS and independent experts among 60 hypertensives on drug management was 85% (95% CI: 83.61 - 85.25). The kappa statistic for overall agreement for drug management was 0.659 (95% CI: 0.457 - 0.862) indicating a substantial degree of agreement beyond chance at an alpha fixed at 0.05 with 80% power. Receiver operator curve (ROC) showed a good accuracy for the DSS, wherein, the area under curve (AUC) was 0.848 (95% CI: 0.741 - 0.948). Sensitivity and specificity of the DSS were 83.33 and 85.71% respectively when compared with independent experts. Conclusion A point of care, pilot tested and validated DSS for management of hypertension has been developed in a resource constrained low and middle income setting and could contribute to improved management of hypertension at a primary health care level. PMID:24223984

  5. The 2013 symposium on pathology data integration and clinical decision support and the current state of field

    PubMed Central

    Baron, Jason M.; Dighe, Anand S.; Arnaout, Ramy; Balis, Ulysses J.; Black-Schaffer, W. Stephen; Carter, Alexis B.; Henricks, Walter H.; Higgins, John M.; Jackson, Brian R.; Kim, JiYeon; Klepeis, Veronica E.; Le, Long P.; Louis, David N.; Mandelker, Diana; Mermel, Craig H.; Michaelson, James S.; Nagarajan, Rakesh; Platt, Mihae E.; Quinn, Andrew M.; Rao, Luigi; Shirts, Brian H.; Gilbertson, John R.

    2014-01-01

    Background: Pathologists and informaticians are becoming increasingly interested in electronic clinical decision support for pathology, laboratory medicine and clinical diagnosis. Improved decision support may optimize laboratory test selection, improve test result interpretation and permit the extraction of enhanced diagnostic information from existing laboratory data. Nonetheless, the field of pathology decision support is still developing. To facilitate the exchange of ideas and preliminary studies, we convened a symposium entitled: Pathology data integration and clinical decision support. Methods: The symposium was held at the Massachusetts General Hospital, on May 10, 2013. Participants were selected to represent diverse backgrounds and interests and were from nine different institutions in eight different states. Results: The day included 16 plenary talks and three panel discussions, together covering four broad areas. Summaries of each presentation are included in this manuscript. Conclusions: A number of recurrent themes emerged from the symposium. Among the most pervasive was the dichotomy between diagnostic data and diagnostic information, including the opportunities that laboratories may have to use electronic systems and algorithms to convert the data they generate into more useful information. Differences between human talents and computer abilities were described; well-designed symbioses between humans and computers may ultimately optimize diagnosis. Another key theme related to the unique needs and challenges in providing decision support for genomics and other emerging diagnostic modalities. Finally, many talks relayed how the barriers to bringing decision support toward reality are primarily personnel, political, infrastructural and administrative challenges rather than technological limitations. PMID:24672737

  6. A Framework for a Decision Support System in a Hierarchical Extended Enterprise Decision Context

    NASA Astrophysics Data System (ADS)

    Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul

    Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.

  7. Evaluation of a novel electronic genetic screening and clinical decision support tool in prenatal clinical settings.

    PubMed

    Edelman, Emily A; Lin, Bruce K; Doksum, Teresa; Drohan, Brian; Edelson, Vaughn; Dolan, Siobhan M; Hughes, Kevin; O'Leary, James; Vasquez, Lisa; Copeland, Sara; Galvin, Shelley L; DeGroat, Nicole; Pardanani, Setul; Gregory Feero, W; Adams, Claire; Jones, Renee; Scott, Joan

    2014-07-01

    "The Pregnancy and Health Profile" (PHP) is a free prenatal genetic screening and clinical decision support (CDS) software tool for prenatal providers. PHP collects family health history (FHH) during intake and provides point-of-care risk assessment for providers and education for patients. This pilot study evaluated patient and provider responses to PHP and effects of using PHP in practice. PHP was implemented in four clinics. Surveys assessed provider confidence and knowledge and patient and provider satisfaction with PHP. Data on the implementation process were obtained through semi-structured interviews with administrators. Quantitative survey data were analyzed using Chi square test, Fisher's exact test, paired t tests, and multivariate logistic regression. Open-ended survey questions and interviews were analyzed using qualitative thematic analysis. Of the 83% (513/618) of patients that provided feedback, 97% felt PHP was easy to use and 98% easy to understand. Thirty percent (21/71) of participating physicians completed both pre- and post-implementation feedback surveys [13 obstetricians (OBs) and 8 family medicine physicians (FPs)]. Confidence in managing genetic risks significantly improved for OBs on 2/6 measures (p values ≤0.001) but not for FPs. Physician knowledge did not significantly change. Providers reported value in added patient engagement and reported mixed feedback about the CDS report. We identified key steps, resources, and staff support required to implement PHP in a clinical setting. To our knowledge, this study is the first to report on the integration of patient-completed, electronically captured and CDS-enabled FHH software into primary prenatal practice. PHP is acceptable to patients and providers. Key to successful implementation in the future will be customization options and interoperability with electronic health records.

  8. Decision Support Systems for Launch and Range Operations Using Jess

    NASA Technical Reports Server (NTRS)

    Thirumalainambi, Rajkumar

    2007-01-01

    The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

  9. Systematic review of clinical decision support interventions with potential for inpatient cost reduction

    PubMed Central

    2013-01-01

    Background Healthcare costs are increasing rapidly and at an unsustainable rate in many countries, and inpatient hospitalizations are a significant driver of these costs. Clinical decision support (CDS) represents a promising approach to not only improve care but to reduce costs in the inpatient setting. The purpose of this study was to systematically review trials of CDS interventions with the potential to reduce inpatient costs, so as to identify promising interventions for more widespread implementation and to inform future research in this area. Methods To identify relevant studies, MEDLINE was searched up to July 2013. CDS intervention studies with the potential to reduce inpatient healthcare costs were identified through titles and abstracts, and full text articles were reviewed to make a final determination on inclusion. Relevant characteristics of the studies were extracted and summarized. Results Following a screening of 7,663 articles, 78 manuscripts were included. 78.2% of studies were controlled before-after studies, and 15.4% were randomized controlled trials. 53.8% of the studies were focused on pharmacotherapy. The majority of manuscripts were published during or after 2008. 70.5% of the studies resulted in statistically and clinically significant improvements in an explicit financial measure or a proxy financial measure. Only 12.8% of the studies directly measured the financial impact of an intervention, whereas the financial impact was inferred in the remainder of studies. Data on cost effectiveness was available for only one study. Conclusions Significantly more research is required on the impact of clinical decision support on inpatient costs. In particular, there is a remarkable gap in the availability of cost effectiveness studies required by policy makers and decision makers in healthcare systems. PMID:24344752

  10. Towards a decision support system for hand dermatology.

    PubMed

    Mazzola, Luca; Cavazzina, Alice; Pinciroli, Francesco; Bonacina, Stefano; Pigatto, Paolo; Ayala, Fabio; De Pità, Ornella; Marceglia, Sara

    2014-01-01

    The complexity of the medical diagnosis is faced by practitioners relying mainly on their experiences. This can be acquired during daily practices and on-the-job training. Given the complexity and extensiveness of the subject, supporting tools that include knowledge extracted by highly specialized practitioners can be valuable. In the present work, a Decision Support System (DSS) for hand dermatology was developed based on data coming from a Visit Report Form (VRF). Using a Bayesian approach and factors significance difference over the population average for the case, we demonstrated the potentiality of creating an enhanced VRF that include a diagnoses distribution probability based on the DSS rules applied for the specific patient situation. PMID:25160145

  11. Towards sustainable decision-support system facilitating EBM.

    PubMed

    Stolba, Nevena; Nguyen, Tho Manh; Tjoa, A Min

    2007-01-01

    Due to the immense volumes of medical data, the architecture of the future healthcare decision support systems focus more on interoperability than on integration. With the raising need for the creation of unified knowledge base, the federated approach to distributed data warehouses (DWH) is getting increasing attention. In this paper, we explore the idea of a federation technology and its uses within the domain of health, particularly in the conceptualization of DWH federation as a sustainable, appropriate and legitimate solution. Further, we present a federated DWH model which enables the interoperability between heterogeneous and distributed medical IS, which includes a sense and response mechanism and facilitates evidence-based medicine in order to primarily support the physicians at the point of care. A real-world scenario illustrates a possible application field in the area of emergency and intensive care.

  12. Recommended practices for computerized clinical decision support and knowledge management in community settings: a qualitative study

    PubMed Central

    2012-01-01

    Background The purpose of this study was to identify recommended practices for computerized clinical decision support (CDS) development and implementation and for knowledge management (KM) processes in ambulatory clinics and community hospitals using commercial or locally developed systems in the U.S. Methods Guided by the Multiple Perspectives Framework, the authors conducted ethnographic field studies at two community hospitals and five ambulatory clinic organizations across the U.S. Using a Rapid Assessment Process, a multidisciplinary research team: gathered preliminary assessment data; conducted on-site interviews, observations, and field surveys; analyzed data using both template and grounded methods; and developed universal themes. A panel of experts produced recommended practices. Results The team identified ten themes related to CDS and KM. These include: 1) workflow; 2) knowledge management; 3) data as a foundation for CDS; 4) user computer interaction; 5) measurement and metrics; 6) governance; 7) translation for collaboration; 8) the meaning of CDS; 9) roles of special, essential people; and 10) communication, training, and support. Experts developed recommendations about each theme. The original Multiple Perspectives framework was modified to make explicit a new theoretical construct, that of Translational Interaction. Conclusions These ten themes represent areas that need attention if a clinic or community hospital plans to implement and successfully utilize CDS. In addition, they have implications for workforce education, research, and national-level policy development. The Translational Interaction construct could guide future applied informatics research endeavors. PMID:22333210

  13. The Arden Syntax standard for clinical decision support: experiences and directions.

    PubMed

    Samwald, Matthias; Fehre, Karsten; de Bruin, Jeroen; Adlassnig, Klaus-Peter

    2012-08-01

    Arden Syntax is a widely recognized standard for representing clinical and scientific knowledge in an executable format. It has a history that reaches back until 1989 and is currently maintained by the Health Level 7 (HL7) organization. We created a production-ready development environment, compiler, rule engine and application server for Arden Syntax. Over the course of several years, we have applied this Arden - Syntax - based CDS system in a wide variety of clinical problem domains, such as hepatitis serology interpretation, monitoring of nosocomial infections or the prediction of metastatic events in melanoma patients. We found the Arden Syntax standard to be very suitable for the practical implementation of CDS systems. Among the advantages of Arden Syntax are its status as an actively developed HL7 standard, the readability of the syntax, and various syntactic features such as flexible list handling. A major challenge we encountered was the technical integration of our CDS systems in existing, heterogeneous health information systems. To address this issue, we are currently working on incorporating the HL7 standard GELLO, which provides a standardized interface and query language for accessing data in health information systems. We hope that these planned extensions of the Arden Syntax might eventually help in realizing the vision of a global, interoperable and shared library of clinical decision support knowledge.

  14. Clinical utility of an electronic poisons information and clinical decision support tool.

    PubMed

    Watts, Martin; Fountain, John; Reith, David M; Herbison, Peter

    2003-08-01

    The objective of the study was to assess the use of a computer toxicology database/clinical decision aid by clinical practitioners. The study investigated the sources that Emergency Department (ED) personnel use to obtain toxicology information and performed a quality audit of the current database. A questionnaire survey of ED staff was used in departments with access to the New Zealand Poisons Centre Substance Database (NZSD), a toxicology CD ROM computer database. Outcome measures were reported use of alternative data sources when managing clinical toxicology presentations and the qualities of the NZSD. Computer databases are commonly used for the management of clinical toxicology cases and the toxicology computer database/clinical decision aid studied is well accepted and used in Emergency Medicine practice. The users of the NZSD assessed the usability and quality of the information of the database. PMID:12909152

  15. Comparing decision-support systems in adopting sustainable intensification criteria

    PubMed Central

    Ahmadi, Bouda Vosough; Moran, Dominic; Barnes, Andrew P.; Baret, Philippe V.

    2015-01-01

    Sustainable intensification (SI) is a multifaceted concept incorporating the ambition to increase or maintain the current level of agricultural yields while reduce negative ecological and environmental impacts. Decision-support systems (DSS) that use integrated analytical methods are often used to support decision making processes in agriculture. However, DSS often consist of set of values, objectives, and assumptions that may be inconsistent or in conflict with merits and objectives of SI. These potential conflicts will have consequences for adoption and up-take of agricultural research, technologies and related policies and regulations such as genetic technology in pursuit of SI. This perspective paper aimed at comparing a number of frequently used socio-economic DSS with respect to their capacity in incorporating various dimensions of SI, and discussing their application to analyzing farm animal genetic resources (FAnGR) policies. The case of FAnGR policies was chosen because of its great potential in delivering merits of SI. It was concluded that flexible DSS, with great integration capacity with various natural and social sciences, are needed to provide guidance on feasibility, practicality, and policy implementation for SI. PMID:25717336

  16. Randomized pilot study and qualitative evaluation of a clinical decision support system for brain tumour diagnosis based on SV ¹H MRS: evaluation as an additional information procedure for novice radiologists.

    PubMed

    Sáez, Carlos; Martí-Bonmatí, Luis; Alberich-Bayarri, Angel; Robles, Montserrat; García-Gómez, Juan M

    2014-02-01

    The results of a randomized pilot study and qualitative evaluation of the clinical decision support system Curiam BT are reported. We evaluated the system's feasibility and potential value as a radiological information procedure complementary to magnetic resonance (MR) imaging to assist novice radiologists in diagnosing brain tumours using MR spectroscopy (1.5 and 3.0T). Fifty-five cases were analysed at three hospitals according to four non-exclusive diagnostic questions. Our results show that Curiam BT improved the diagnostic accuracy in all the four questions. Additionally, we discuss the findings of the users' feedback about the system, and the further work to optimize it for real environments and to conduct a large clinical trial. PMID:24480160

  17. Validation of a decision support system for improving irrigation system performance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To address water shortage and improve water delivery operations, decision support systems have been developed and utilized throughout the United States and the world. One critical aspect that is often neglected during the development and implementation of decision support systems is validation, whi...

  18. Evaluating the Effectiveness of Nurse-Focused Computerized Clinical Decision Support on Urinary Catheter Practice Guidelines

    ERIC Educational Resources Information Center

    Lang, Robin Lynn Neal

    2012-01-01

    A growing national emphasis has been placed on health information technology (HIT) with robust computerized clinical decision support (CCDS) integration into health care delivery. Catheter-associated urinary tract infection is the most frequent health care-associated infection in the United States and is associated with high cost, high volumes and…

  19. Decision support system for managing oil spill events.

    PubMed

    Keramitsoglou, Iphigenia; Cartalis, Constantinos; Kassomenos, Pavlos

    2003-08-01

    The Mediterranean environment is exposed to various hazards, including oil spills, forest fires, and floods, making the development of a decision support system (DSS) for emergency management an objective of utmost importance. The present work presents a complete DSS for managing marine pollution events caused by oil spills. The system provides all the necessary tools for early detection of oil-spills from satellite images, monitoring of their evolution, estimation of the accident consequences and provision of support to responsible Public Authorities during clean-up operations. The heart of the system is an image processing-geographic information system and other assistant individual software tools that perform oil spill evolution simulation and all other necessary numerical calculations as well as cartographic and reporting tasks related to a specific management of the oil spill event. The cartographic information is derived from the extant general maps representing detailed information concerning several regional environmental and land-cover characteristics as well as financial activities of the application area. Early notification of the authorities with up-to-date accurate information on the position and evolution of the oil spill, combined with the detailed coastal maps, is of paramount importance for emergency assessment and effective clean-up operations that would prevent environmental hazard. An application was developed for the Region of Crete, an area particularly vulnerable to oil spills due to its location, ecological characteristics, and local economic activities.

  20. Clinical-decision support based on medical literature: A complex network approach

    NASA Astrophysics Data System (ADS)

    Jiang, Jingchi; Zheng, Jichuan; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin

    2016-10-01

    In making clinical decisions, clinicians often review medical literature to ensure the reliability of diagnosis, test, and treatment because the medical literature can answer clinical questions and assist clinicians making clinical decisions. Therefore, finding the appropriate literature is a critical problem for clinical-decision support (CDS). First, the present study employs search engines to retrieve relevant literature about patient records. However, the result of the traditional method is usually unsatisfactory. To improve the relevance of the retrieval result, a medical literature network (MLN) based on these retrieved papers is constructed. Then, we show that this MLN has small-world and scale-free properties of a complex network. According to the structural characteristics of the MLN, we adopt two methods to further identify the potential relevant literature in addition to the retrieved literature. By integrating these potential papers into the MLN, a more comprehensive MLN is built to answer the question of actual patient records. Furthermore, we propose a re-ranking model to sort all papers by relevance. We experimentally find that the re-ranking model can improve the normalized discounted cumulative gain of the results. As participants of the Text Retrieval Conference 2015, our clinical-decision method based on the MLN also yields higher scores than the medians in most topics and achieves the best scores for topics: #11 and #12. These research results indicate that our study can be used to effectively assist clinicians in making clinical decisions, and the MLN can facilitate the investigation of CDS.

  1. A Legal Framework to Enable Sharing of Clinical Decision Support Knowledge and Services across Institutional Boundaries

    PubMed Central

    Hongsermeier, Tonya; Maviglia, Saverio; Tsurikova, Lana; Bogaty, Dan; Rocha, Roberto A.; Goldberg, Howard; Meltzer, Seth; Middleton, Blackford

    2011-01-01

    The goal of the CDS Consortium (CDSC) is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology at scale – across multiple ambulatory care settings and Electronic Health Record technology platforms. In the course of the CDSC research effort, it became evident that a sound legal foundation was required for knowledge sharing and clinical decision support services in order to address data sharing, intellectual property, accountability, and liability concerns. This paper outlines the framework utilized for developing agreements in support of sharing, accessing, and publishing content via the CDSC Knowledge Management Portal as well as an agreement in support of deployment and consumption of CDSC developed web services in the context of a research project under IRB oversight. PMID:22195151

  2. WEB-GIS Decision Support System for CO2 storage

    NASA Astrophysics Data System (ADS)

    Gaitanaru, Dragos; Leonard, Anghel; Radu Gogu, Constantin; Le Guen, Yvi; Scradeanu, Daniel; Pagnejer, Mihaela

    2013-04-01

    Environmental decision support systems (DSS) paradigm evolves and changes as more knowledge and technology become available to the environmental community. Geographic Information Systems (GIS) can be used to extract, assess and disseminate some types of information, which are otherwise difficult to access by traditional methods. In the same time, with the help of the Internet and accompanying tools, creating and publishing online interactive maps has become easier and rich with options. The Decision Support System (MDSS) developed for the MUSTANG (A MUltiple Space and Time scale Approach for the quaNtification of deep saline formations for CO2 storaGe) project is a user friendly web based application that uses the GIS capabilities. MDSS can be exploited by the experts for CO2 injection and storage in deep saline aquifers. The main objective of the MDSS is to help the experts to take decisions based large structured types of data and information. In order to achieve this objective the MDSS has a geospatial objected-orientated database structure for a wide variety of data and information. The entire application is based on several principles leading to a series of capabilities and specific characteristics: (i) Open-Source - the entire platform (MDSS) is based on open-source technologies - (1) database engine, (2) application server, (3) geospatial server, (4) user interfaces, (5) add-ons, etc. (ii) Multiple database connections - MDSS is capable to connect to different databases that are located on different server machines. (iii)Desktop user experience - MDSS architecture and design follows the structure of a desktop software. (iv)Communication - the server side and the desktop are bound together by series functions that allows the user to upload, use, modify and download data within the application. The architecture of the system involves one database and a modular application composed by: (1) a visualization module, (2) an analysis module, (3) a guidelines module

  3. Decision support systems and methods for complex networks

    DOEpatents

    Huang, Zhenyu; Wong, Pak Chung; Ma, Jian; Mackey, Patrick S; Chen, Yousu; Schneider, Kevin P

    2012-02-28

    Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

  4. Clinical Application of Bioartificial Liver Support Systems

    PubMed Central

    van de Kerkhove, Maarten Paul; Hoekstra, Ruurdtje; Chamuleau, Robert A. F. M.; van Gulik, Thomas M.

    2004-01-01

    Objective: To review the present status of bioartificial liver (BAL) devices and their obtained clinical results. Background: Acute liver failure (ALF) is a disease with a high mortality. Standard therapy at present is liver transplantation. Liver transplantation is hampered by the increasing shortage of organ donors, resulting in high incidence of patients with ALF dying on the transplantation waiting list. Among a variety of liver assist therapies, BAL therapy is marked as the most promising solution to bridge ALF patients to liver transplantation or to liver regeneration, because several BAL systems showed significant survival improvement in animal ALF studies. Until today, clinical application of 11 different BAL systems has been reported. Methods: A literature review was performed using MEDLINE and additional library searches. Only BAL systems that have been used in a clinical trial were included in this review. Results: Eleven BAL systems found clinical application. Three systems were studied in a controlled trial, showing no significant survival benefits, in part due to the insufficient number of patients included. The other systems were studied in a phase I trial or during treatment of a single patient and all showed to be safe. Most BAL therapies resulted in improvement of clinical and biochemical parameters. Conclusions: Bioartificial liver therapy for bridging patients with ALF to liver transplantation or liver regeneration is promising. Its clinical value awaits further improvement of BAL devices, replacement of hepatocytes of animal origin by human hepatocytes, and assessment in controlled clinical trials. PMID:15273544

  5. SERVIR: A Regional Monitoring and Decision Support System for Mesoamerica

    NASA Astrophysics Data System (ADS)

    Irwin, D.; Hardin, D. M.; Sever, T.; Graves, S.

    2008-05-01

    Mesoamerica is a prime example of a multi-national region with natural and human induced stresses that benefits from information provided by observation systems. The region is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability of its population to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, the University of Alabama in Huntsville and numerous SERVIR* partners are developing data products, knowledge extraction methods and decision support tools for environmental monitoring, disaster response and sustainable growth planning in Mesoamerica. The combination of space- based observations from NASA's Earth Observing Satellites with information management and knowledge extraction technologies has yielded a robust system for use by scientists, educators, environmental ministers and policy makers. These resources enhance the ability to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. Now in its fourth year SERVIR has become a partner in the International Space and Major Disasters Charter. In the past year the Charter provided commercial satellite imagery to aid in disaster response to Hurricanes Dean, Felix and Noel. Overcoming roadblocks to coordination and data sharing between countries, organizations and disciplines SERVIR is providing environmental monitoring and decision support products and applications that directly map to several Observation GEOSS societal benefit areas. This paper provides an overview of the ongoing accomplishments of the SERVIR project. *SERVIR is a Spanish verb meaning "to serve" or "be useful" is also an acronym for the Spanish name of the capability: Sistema Regional de Visualizacion y Monitero.

  6. Query-handling in MLM-based decision support systems.

    PubMed

    Arkad, K; Gao, X M; Ahlfeldt, H

    1995-01-01

    Arden Syntax for Medical Logic Modules is a standard specification for creation and sharing of knowledge bases. The standard specification focuses on knowledge that can be represented as a set of independent Medical Logic Modules (MLMs) such as rules, formulas and protocols. The basic functions of an MLM are to retrieve patient data, manipulate the data, come to some decision, and possibly perform an action. All connections to the world outside an MLM are collected in the data-slot of the MLM. The institution specific parts of these connections are inside the notation of curly brackets ([]) to facilitate sharing of MLM between institutions. This paper focuses on some of the problems that occur in relation to Arden Syntax and connections to a patient database such as database queries. Problems related to possibilities of moving one or several module(s) are also discussed, with emphasis on database connections. As an example, an MLM based Decision Support System (DSS) developed at Linköping University is described. PMID:8882561

  7. Towards a Decision Support System for Space Flight Operations

    NASA Technical Reports Server (NTRS)

    Meshkat, Leila; Hogle, Charles; Ruszkowski, James

    2013-01-01

    The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of

  8. Service oriented architecture for clinical decision support: a systematic review and future directions.

    PubMed

    Loya, Salvador Rodriguez; Kawamoto, Kensaku; Chatwin, Chris; Huser, Vojtech

    2014-12-01

    The use of a service-oriented architecture (SOA) has been identified as a promising approach for improving health care by facilitating reliable clinical decision support (CDS). A review of the literature through October 2013 identified 44 articles on this topic. The review suggests that SOA related technologies such as Business Process Model and Notation (BPMN) and Service Component Architecture (SCA) have not been generally adopted to impact health IT systems' performance for better care solutions. Additionally, technologies such as Enterprise Service Bus (ESB) and architectural approaches like Service Choreography have not been generally exploited among researchers and developers. Based on the experience of other industries and our observation of the evolution of SOA, we found that the greater use of these approaches have the potential to significantly impact SOA implementations for CDS.

  9. Research on web-based decision support system for sports competitions

    NASA Astrophysics Data System (ADS)

    Huo, Hanqiang

    2010-07-01

    This paper describes the system architecture and implementation technology of the decision support system for sports competitions, discusses the design of decision-making modules, management modules and security of the system, and proposes the development idea of building a web-based decision support system for sports competitions.

  10. Tablet-based patient monitoring and decision support systems in hospital care.

    PubMed

    Baig, Mirza Mansoor; GholamHosseini, Hamid; Linden, Maria

    2015-08-01

    Remote patient monitoring with evidence-based decision support is revolutionizing healthcare. This novel approach could enable both patients and healthcare providers to improve quality of care and reduce costs. Clinicians can also view patients' data within the hospital network on tablet computers as well as other ubiquitous devices. Today, a wide range of applications are available on tablet computers which are increasingly integrating into the healthcare mainstream as clinical decision support systems. Despite the benefits of tablet-based healthcare applications, there are concerns around the accuracy, security and stability of such applications. In this study, we developed five tablet-based application screens for remote patient monitoring at hospital care settings and identified related issues and challenges. The ultimate aim of this research is to integrate decision support algorithms into the monitoring system in order to improve inpatient care and the effectiveness of such applications. PMID:26736485

  11. Visualization Component of Vehicle Health Decision Support System

    NASA Technical Reports Server (NTRS)

    Jacob, Joseph; Turmon, Michael; Stough, Timothy; Siegel, Herbert; Walter, patrick; Kurt, Cindy

    2008-01-01

    The visualization front-end of a Decision Support System (DSS) also includes an analysis engine linked to vehicle telemetry, and a database of learned models for known behaviors. Because the display is graphical rather than text-based, the summarization it provides has a greater information density on one screen for evaluation by a flight controller.This tool provides a system-level visualization of the state of a vehicle, and drill-down capability for more details and interfaces to separate analysis algorithms and sensor data streams. The system-level view is a 3D rendering of the vehicle, with sensors represented as icons, tied to appropriate positions within the vehicle body and colored to indicate sensor state (e.g., normal, warning, anomalous state, etc.). The sensor data is received via an Information Sharing Protocol (ISP) client that connects to an external server for real-time telemetry. Users can interactively pan, zoom, and rotate this 3D view, as well as select sensors for a detail plot of the associated time series data. Subsets of the plotted data can be selected and sent to an external analysis engine to either search for a similar time series in an historical database, or to detect anomalous events. The system overview and plotting capabilities are completely general in that they can be applied to any vehicle instrumented with a collection of sensors. This visualization component can interface with the ISP for data streams used by NASA s Mission Control Center at Johnson Space Center. In addition, it can connect to, and display results from, separate analysis engine components that identify anomalies or that search for past instances of similar behavior. This software supports NASA's Software, Intelligent Systems, and Modeling element in the Exploration Systems Research and Technology Program by augmenting the capability of human flight controllers to make correct decisions, thus increasing safety and reliability. It was designed specifically as a

  12. Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications

    PubMed Central

    Berrouiguet, Sofian; Barrigón, Maria Luisa; Brandt, Sara A.; Ovejero-García, Santiago; Álvarez-García, Raquel; Carballo, Juan Jose; Lenca, Philippe; Courtet, Philippe; Baca-García, Enrique

    2016-01-01

    Purpose The emergence of electronic prescribing devices with clinical decision support systems (CDSS) is able to significantly improve management pharmacological treatments. We developed a web application available on smartphones in order to help clinicians monitor prescription and further propose CDSS. Method A web application (www.MEmind.net) was developed to assess patients and collect data regarding gender, age, diagnosis and treatment. We analyzed antipsychotic prescriptions in 4345 patients attended in five Psychiatric Community Mental Health Centers from June 2014 to October 2014. The web-application reported average daily dose prescribed for antipsychotics, prescribed daily dose (PDD), and the PDD to defined daily dose (DDD) ratio. Results The MEmind web-application reported that antipsychotics were used in 1116 patients out of the total sample, mostly in 486 (44%) patients with schizophrenia related disorders but also in other diagnoses. Second generation antipsychotics (quetiapine, aripiprazole and long-acting paliperidone) were preferably employed. Low doses were more frequently used than high doses. Long acting paliperidone and ziprasidone however, were the only two antipsychotics used at excessive dosing. Antipsychotic polypharmacy was used in 287 (26%) patients with classic depot drugs, clotiapine, amisulpride and clozapine. Conclusions In this study we describe the first step of the development of a web application that is able to make polypharmacy, high dose usage and off label usage of antipsychotics visible to clinicians. Current development of the MEmind web application may help to improve prescription security via momentary feedback of prescription and clinical decision support system. PMID:27764107

  13. Effectively marketing prepaid medical care with decision support systems.

    PubMed

    Forgionne, G A

    1991-01-01

    The paper reports a decision support system (DSS) that enables health plan administrators to quickly and easily: (1) manage relevant medical care market (consumer preference and competitors' program) information and (2) convert the information into appropriate medical care delivery and/or payment policies. As the paper demonstrates, the DSS enables providers to design cost efficient and market effective medical care programs. The DSS provides knowledge about subscriber preferences, customer desires, and the program offerings of the competition. It then helps administrators structure a medical care plan in a way that best meets consumer needs in view of the competition. This market effective plan has the potential to generate substantial amounts of additional revenue for the program. Since the system's data base consists mainly of the provider's records, routine transactions, and other readily available documents, the DSS can be implemented at a nominal incremental cost. The paper also evaluates the impact of the information system on the general financial performance of existing dental and mental health plans. In addition, the paper examines how the system can help contain the cost of providing medical care while providing better services to more potential beneficiaries than current approaches.

  14. SADA: Ecological Risk Based Decision Support System for Selective Remediation

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

  15. The Morningside Initiative: Collaborative Development of a Knowledge Repository to Accelerate Adoption of Clinical Decision Support

    PubMed Central

    Greenes, Robert; Bloomrosen, Meryl; Brown-Connolly, Nancy E.; Curtis, Clayton; Detmer, Don E; Enberg, Robert; Fridsma, Douglas; Fry, Emory; Goldstein, Mary K; Haug, Peter; Hulse, Nathan; Hongsermeier, Tonya; Maviglia, Saverio; Robbins, Craig W; Shah, Hemant

    2010-01-01

    The Morningside Initiative is a public-private activity that has evolved from an August, 2007, meeting at the Morningside Inn, in Frederick, MD, sponsored by the Telemedicine and Advanced Technology Research Center (TATRC) of the US Army Medical Research Materiel Command. Participants were subject matter experts in clinical decision support (CDS) and included representatives from the Department of Defense, Veterans Health Administration, Kaiser Permanente, Partners Healthcare System, Henry Ford Health System, Arizona State University, and the American Medical Informatics Association (AMIA). The Morningside Initiative was convened in response to the AMIA Roadmap for National Action on Clinical Decision Support and on the basis of other considerations and experiences of the participants. Its formation was the unanimous recommendation of participants at the 2007 meeting which called for creating a shared repository of executable knowledge for diverse health care organizations and practices, as well as health care system vendors. The rationale is based on the recognition that sharing of clinical knowledge needed for CDS across organizations is currently virtually non-existent, and that, given the considerable investment needed for creating, maintaining and updating authoritative knowledge, which only larger organizations have been able to undertake, this is an impediment to widespread adoption and use of CDS. The Morningside Initiative intends to develop and refine (1) an organizational framework, (2) a technical approach, and (3) CDS content acquisition and management processes for sharing CDS knowledge content, tools, and experience that will scale with growing numbers of participants and can be expanded in scope of content and capabilities. Intermountain Healthcare joined the initial set of participants shortly after its formation. The efforts of the Morningside Initiative are intended to serve as the basis for a series of next steps in a national agenda for CDS. It

  16. Creating a GIS-Based Decision-Support System

    NASA Technical Reports Server (NTRS)

    Alvarado, Lori; Gates, Ann Q.; Gray, Bob; Reyes, Raul

    1998-01-01

    Tilting the Balance: Climate Variability and Water Resource Management in the Southwest, a regional conference hosted by the Pan American Center for Environmental Studies, will be held at The University of Texas at El Paso on March 2-4, 1998. The conference is supported through the US Global Change Research Program (USGCRP) established by the President in 1989, and codified by Congress in the Global Change Research Act of 1990. The NASA Mission to Planet Earth program is one of the workshops sponsors. The purpose of the regional workshops is to improve understanding of the consequences of global change. This workshop will be focused on issues along the border and the Rio Grande River and thus will bring together stakeholders from Mexico, California, Texas, New Mexico, Arizona and Colorado representing federal, state, and local governments; universities and laboratories; industry, agricultural and natural resource managers; and non-governmental organizations. This paper discusses the efforts of the NASA PACES center create a GIS-based decision-support system that can be used to facilitate discussion of the complex issues of resource management within the targeted international region.

  17. A decision support system for managing forest fire casualties.

    PubMed

    Bonazountas, Marc; Kallidromitou, Despina; Kassomenos, Pavlos; Passas, Nikos

    2007-09-01

    Southern Europe is exposed to anthropogenic and natural forest fires. These result in loss of lives, goods and infrastructure, but also deteriorate the natural environment and degrade ecosystems. The early detection and combating of such catastrophes requires the use of a decision support system (DSS) for emergency management. The current literature reports on a series of efforts aimed to deliver DSSs for the management of the forest fires by utilising technologies like remote sensing and geographical information systems (GIS), yet no integrated system exists. This manuscript presents the results of scientific research aiming to the development of a DSS for managing forest fires. The system provides a series of software tools for the assessment of the propagation and combating of forest fires based on Arc/Info, ArcView, Arc Spatial Analyst, Arc Avenue, and Visual C++ technologies. The system integrates GIS technologies under the same data environment and utilises a common user interface to produce an integrated computer system based on semi-automatic satellite image processing (fuel maps), socio-economic risk modelling and probabilistic models that would serve as a useful tool for forest fire prevention, planning and management. Its performance has been demonstrated via real time up-to-date accurate information on the position and evolution of the fire. The system can assist emergency assessment, management and combating of the incident. A site demonstration and validation has been accomplished for the island of Evoia, Greece, an area particularly vulnerable to forest fires due to its ecological characteristics and prevailing wind patterns. PMID:16928418

  18. A decision support system for managing forest fire casualties.

    PubMed

    Bonazountas, Marc; Kallidromitou, Despina; Kassomenos, Pavlos; Passas, Nikos

    2007-09-01

    Southern Europe is exposed to anthropogenic and natural forest fires. These result in loss of lives, goods and infrastructure, but also deteriorate the natural environment and degrade ecosystems. The early detection and combating of such catastrophes requires the use of a decision support system (DSS) for emergency management. The current literature reports on a series of efforts aimed to deliver DSSs for the management of the forest fires by utilising technologies like remote sensing and geographical information systems (GIS), yet no integrated system exists. This manuscript presents the results of scientific research aiming to the development of a DSS for managing forest fires. The system provides a series of software tools for the assessment of the propagation and combating of forest fires based on Arc/Info, ArcView, Arc Spatial Analyst, Arc Avenue, and Visual C++ technologies. The system integrates GIS technologies under the same data environment and utilises a common user interface to produce an integrated computer system based on semi-automatic satellite image processing (fuel maps), socio-economic risk modelling and probabilistic models that would serve as a useful tool for forest fire prevention, planning and management. Its performance has been demonstrated via real time up-to-date accurate information on the position and evolution of the fire. The system can assist emergency assessment, management and combating of the incident. A site demonstration and validation has been accomplished for the island of Evoia, Greece, an area particularly vulnerable to forest fires due to its ecological characteristics and prevailing wind patterns.

  19. Team Machine: A Decision Support System for Team Formation

    ERIC Educational Resources Information Center

    Bergey, Paul; King, Mark

    2014-01-01

    This paper reports on the cross-disciplinary research that resulted in a decision-support tool, Team Machine (TM), which was designed to create maximally diverse student teams. TM was used at a large United States university between 2004 and 2012, and resulted in significant improvement in the performance of student teams, superior overall balance…

  20. A decision support system for rainfed agricultural areas of Mexico

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rural inhabitants of arid lands lack sufficient water to fulfill their agricultural and household needs. They do not have readily available technical information to support decisions regarding the course of action they should follow to handle the agro-climatic risk. In this paper, a computer model (...

  1. Fuzzy-Arden-Syntax-based, Vendor-agnostic, Scalable Clinical Decision Support and Monitoring Platform.

    PubMed

    Adlassnig, Klaus-Peter; Fehre, Karsten; Rappelsberger, Andrea

    2015-01-01

    This study's objective is to develop and use a scalable genuine technology platform for clinical decision support based on Arden Syntax, which was extended by fuzzy set theory and fuzzy logic. Arden Syntax is a widely recognized formal language for representing clinical and scientific knowledge in an executable format, and is maintained by Health Level Seven (HL7) International and approved by the American National Standards Institute (ANSI). Fuzzy set theory and logic permit the representation of knowledge and automated reasoning under linguistic and propositional uncertainty. These forms of uncertainty are a common feature of patients' medical data, the body of medical knowledge, and deductive clinical reasoning.

  2. Decision-Making Amplification under Uncertainty: An Exploratory Study of Behavioral Similarity and Intelligent Decision Support Systems

    ERIC Educational Resources Information Center

    Campbell, Merle Wayne

    2013-01-01

    Intelligent decision systems have the potential to support and greatly amplify human decision-making across a number of industries and domains. However, despite the rapid improvement in the underlying capabilities of these "intelligent" systems, increasing their acceptance as decision aids in industry has remained a formidable challenge.…

  3. A Pain Management Decision Support System for Nurses

    PubMed Central

    Heriot, Cathy; Graves, Judith; Bouhaddou, Omar; Armstrong, Margaret; Wigertz, Gudrun; Ben Said, Mohamed

    1988-01-01

    This paper describes the development and uses of the Nursing Pain Management Consultation System, a prototype demonstration project for Integrated Academic Information Management System (IAIMS) at the University of Utah. A knowledge base representing the best current thinking regarding management of acute pain secondary to total hip arthroplasty (THA) is the knowledge core of the expert system. The decisions modeled range from assessment of the severity of pain to decisions related to both pharmacologic and non-pharmacologic approaches to the alleviation of pain. The system also advises the nurses on measures to assess and prevent complications of the treatments.

  4. Clinical Decision Support for the Classification of Diabetic Retinopathy: A Comparison of Manual and Automated Results.

    PubMed

    Mitsch, Christoph; Fehre, Karsten; Prager, Sonja; Scholda, Christoph; Kriechbaum, Katharina; Wrba, Thomas; Schmidt-Erfurth, Ursula

    2016-01-01

    The management of diabetic retinopathy, a frequent ophthalmological manifestation of diabetes mellitus, consists of regular examinations and a standardized, manual classification of disease severity, which is used to recommend re-examination intervals. To evaluate the feasibility and safety of implementing automated, guideline-based diabetic retinopathy (DR) grading into clinical routine by applying established clinical decision support (CDS) technology. We compared manual with automated classification that was generated using medical documentation and an Arden server with a specific medical logic module. Of 7169 included eyes, 47% (n=3373) showed inter-method classification agreement, specifically 29.4% in mild DR, 38.3% in moderate DR, 27.6% in severe DR, and 65.7% in proliferative DR. We demonstrate that the implementation of a CDS system for automated disease severity classification in diabetic retinopathy is feasible but also that, due to the highly individual nature of medical documentation, certain important criteria for the used electronic health record system need to be met in order to achieve reliable results.

  5. Lung Cancer Assistant: a hybrid clinical decision support application for lung cancer care

    PubMed Central

    Sesen, M. Berkan; Peake, Michael D.; Banares-Alcantara, Rene; Tse, Donald; Kadir, Timor; Stanley, Roz; Gleeson, Fergus; Brady, Michael

    2014-01-01

    Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments. PMID:24990290

  6. A Wireless, Handheld Decision Support System To Promote Smoking Cessation in Primary Care

    PubMed Central

    Michel, George; Marcy, Theodore; Shiffman, Richard N.

    2005-01-01

    Tobacco use remains a relatively unaddressed cause of disease and death in the daily care of patients by physicians. To overcome the barriers that physicians face in addressing tobacco use and its treatment in the primary care setting, we have developed a clinical decision support system that is readily accessible through the use of familiar wireless handheld devices and supportive of treatment through the implementation of the Tobacco Use and Dependence Treatment Guideline recommendations. We adopted the Information Management Services model to ensure that the application would effectively implement the guideline. The techniques used here are readily adaptable to implementing a broad range of clinical guidelines. PMID:16779096

  7. Improving Information Products for System 2 Decision Support

    ERIC Educational Resources Information Center

    Gibson, Neal

    2010-01-01

    The creation, maintenance, and management of Information Product (IP) systems that are used by organizations for complex decisions represent a unique set of challenges. These challenges are compounded when the purpose of such a systems is also for knowledge creation and dissemination. Information quality research to date has focused mainly upon…

  8. Is there a need for hydrological modelling in decision support systems for nuclear emergencies.

    PubMed

    Raskob, W; Heling, R; Zheleznyak, M

    2004-01-01

    This paper discusses the role of hydrological modelling in decision support systems for nuclear emergencies. In particular, most recent developments such as, the radionuclide transport models integrated in to the decision support system RODOS will be explored. Recent progress in the implementation of physically-based distributed hydrological models for operational forecasting in national and supranational centres, may support a closer cooperation between national hydrological services and therefore, strengthen the use of hydrological and radiological models implemented in decision support systems.

  9. Developing a Software for Fuzzy Group Decision Support System: A Case Study

    ERIC Educational Resources Information Center

    Baba, A. Fevzi; Kuscu, Dincer; Han, Kerem

    2009-01-01

    The complex nature and uncertain information in social problems required the emergence of fuzzy decision support systems in social areas. In this paper, we developed user-friendly Fuzzy Group Decision Support Systems (FGDSS) software. The software can be used for multi-purpose decision making processes. It helps the users determine the main and…

  10. Why decision support systems are important for medical education.

    PubMed

    Konstantinidis, Stathis Th; Bamidis, Panagiotis D

    2016-03-01

    During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified.

  11. Why decision support systems are important for medical education.

    PubMed

    Konstantinidis, Stathis Th; Bamidis, Panagiotis D

    2016-03-01

    During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified. PMID:27222734

  12. Mountaineer`s gas facilities decision support system

    SciTech Connect

    1997-02-01

    Mountaineer Gas Co. of Charleston, W.Va., is justifiably proud of its capacity to combine electronic maps with a full database of information about its facilities and customers, and use that mix to make the decisions required in operating a gas company with better information and more quickly. Determining when a pipeline needs replacement or repair used to take several days at Mountaineer. With the new system in place, the decision can be made in a matter of minutes. The paper describes the system and its development, then discusses adding customer information as the next step.

  13. Critical infrastructure protection decision support system decision model : overview and quick-start user's guide.

    SciTech Connect

    Samsa, M.; Van Kuiken, J.; Jusko, M.; Decision and Information Sciences

    2008-12-01

    The Critical Infrastructure Protection Decision Support System Decision Model (CIPDSS-DM) is a useful tool for comparing the effectiveness of alternative risk-mitigation strategies on the basis of CIPDSS consequence scenarios. The model is designed to assist analysts and policy makers in evaluating and selecting the most effective risk-mitigation strategies, as affected by the importance assigned to various impact measures and the likelihood of an incident. A typical CIPDSS-DM decision map plots the relative preference of alternative risk-mitigation options versus the annual probability of an undesired incident occurring once during the protective life of the investment, assumed to be 20 years. The model also enables other types of comparisons, including a decision map that isolates a selected impact variable and displays the relative preference for the options of interest--parameterized on the basis of the contribution of the isolated variable to total impact, as well as the likelihood of the incident. Satisfaction/regret analysis further assists the analyst or policy maker in evaluating the confidence with which one option can be selected over another.

  14. MAROS: a decision support system for optimizing monitoring plans.

    PubMed

    Aziz, Julia J; Ling, Meng; Rifai, Hanadi S; Newell, Charles J; Gonzales, James R

    2003-01-01

    The Monitoring and Remediation Optimization System (MAROS), a decision-support software, was developed to assist in formulating cost-effective ground water long-term monitoring plans. MAROS optimizes an existing ground water monitoring program using both temporal and spatial data analyses to determine the general monitoring system category and the locations and frequency of sampling for future compliance monitoring at the site. The objective of the MAROS optimization is to minimize monitoring locations in the sampling network and reduce sampling frequency without significant loss of information, ensuring adequate future characterization of the contaminant plume. The interpretive trend analysis approach recommends the general monitoring system category for a site based on plume stability and site-specific hydrogeologic information. Plume stability is characterized using primary lines of evidence (i.e., Mann-Kendall analysis and linear regression analysis) based on concentration trends, and secondary lines of evidence based on modeling results and empirical data. The sampling optimization approach, consisting of a two-dimensional spatial sampling reduction method (Delaunay method) and a temporal sampling analysis method (Modified CES method), provides detailed sampling location and frequency results. The Delaunay method is designed to identify and eliminate redundant sampling locations without causing significant information loss in characterizing the plume. The Modified CES method determines the optimal sampling frequency for a sampling location based on the direction, magnitude, and uncertainty in its concentration trend. MAROS addresses a variety of ground water contaminants (fuels, solvents, and metals), allows import of various data formats, and is designed for continual modification of long-term monitoring plans as the plume or site conditions change over time.

  15. Computer aided decision support system for cervical cancer classification

    NASA Astrophysics Data System (ADS)

    Rahmadwati, Rahmadwati; Naghdy, Golshah; Ros, Montserrat; Todd, Catherine

    2012-10-01

    Conventional analysis of a cervical histology image, such a pap smear or a biopsy sample, is performed by an expert pathologist manually. This involves inspecting the sample for cellular level abnormalities and determining the spread of the abnormalities. Cancer is graded based on the spread of the abnormal cells. This is a tedious, subjective and time-consuming process with considerable variations in diagnosis between the experts. This paper presents a computer aided decision support system (CADSS) tool to help the pathologists in their examination of the cervical cancer biopsies. The main aim of the proposed CADSS system is to identify abnormalities and quantify cancer grading in a systematic and repeatable manner. The paper proposes three different methods which presents and compares the results using 475 images of cervical biopsies which include normal, three stages of pre cancer, and malignant cases. This paper will explore various components of an effective CADSS; image acquisition, pre-processing, segmentation, feature extraction, classification, grading and disease identification. Cervical histological images are captured using a digital microscope. The images are captured in sufficient resolution to retain enough information for effective classification. Histology images of cervical biopsies consist of three major sections; background, stroma and squamous epithelium. Most diagnostic information are contained within the epithelium region. This paper will present two levels of segmentations; global (macro) and local (micro). At the global level the squamous epithelium is separated from the background and stroma. At the local or cellular level, the nuclei and cytoplasm are segmented for further analysis. Image features that influence the pathologists' decision during the analysis and classification of a cervical biopsy are the nuclei's shape and spread; the ratio of the areas of nuclei and cytoplasm as well as the texture and spread of the abnormalities

  16. Clinical Decision Support Alert Appropriateness: A Review and Proposal for Improvement

    PubMed Central

    McCoy, Allison B.; Thomas, Eric J.; Krousel-Wood, Marie; Sittig, Dean F.

    2014-01-01

    Background Many healthcare providers are adopting clinical decision support (CDS) systems to improve patient safety and meet meaningful use requirements. Computerized alerts that prompt clinicians about drug-allergy, drug-drug, and drug-disease warnings or provide dosing guidance are most commonly implemented. Alert overrides, which occur when clinicians do not follow the guidance presented by the alert, can hinder improved patient outcomes. Methods We present a review of CDS alerts and describe a proposal to develop novel methods for evaluating and improving CDS alerts that builds upon traditional informatics approaches. Our proposal incorporates previously described models for predicting alert overrides that utilize retrospective chart review to determine which alerts are clinically relevant and which overrides are justifiable. Results Despite increasing implementations of CDS alerts, detailed evaluations rarely occur because of the extensive labor involved in manual chart reviews to determine alert and response appropriateness. Further, most studies have solely evaluated alert overrides that are appropriate or justifiable. Our proposal expands the use of web-based monitoring tools with an interactive dashboard for evaluating CDS alert and response appropriateness that incorporates the predictive models. The dashboard provides 2 views, an alert detail view and a patient detail view, to provide a full history of alerts and help put the patient's events in context. Conclusion The proposed research introduces several innovations to address the challenges and gaps in alert evaluations. This research can transform alert evaluation processes across healthcare settings, leading to improved CDS, reduced alert fatigue, and increased patient safety. PMID:24940129

  17. Development of a Decision Support System for Analysis and Solutions of Prolonged Standing in the Workplace

    PubMed Central

    Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

    2014-01-01

    Background Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. Methods The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Results Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. Conclusion The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially. PMID:25180141

  18. Interactive decision support system to predict print quality.

    PubMed

    Leman, Sugani; Lehto, Mark R

    2003-01-15

    Customers using printers occasionally experience problems such as fuzzy images, bands, or streaks. The customer may call or otherwise contact the manufacturer, who attempts to diagnose the problem based on the customer's description of the problem. This study evaluated Bayesian inference as a tool for identifying or diagnosing 16 different types of print defects from such descriptions. The Bayesian model was trained using 1701 narrative descriptions of print defects obtained from 60 subjects with varying technical backgrounds. The Bayesian model was then implemented as an interactive decision support system, which was used by eight 'agents' to diagnose print defects reported by 16 'customers' in a simulated call centre. The 'agents' and 'customers' in the simulated call centre were all students at Purdue University. Each customer made eight telephone calls, resulting in a total of 128 telephone calls in which the customer reported defects to the agents. The results showed that the Bayesian model closely fitted the data in the training set of narratives. Overall, the model correctly predicted the actual defect category with its top prediction 70% of the time. The actual defect was in the top five predictions 94% of the time. The model in the simulated call centre performed nearly as well for the test subjects. The top prediction was correct 50% of the time, and the defect was one of the top five predictions 80% of the time. Agent accuracy in diagnosing the problem improved when using the tool. These results demonstrated that the Bayesian system learned enough from the existing narratives to accurately classify print defect categories.

  19. Evaluation of Effectiveness and Cost‐Effectiveness of a Clinical Decision Support System in Managing Hypertension in Resource Constrained Primary Health Care Settings: Results From a Cluster Randomized Trial

    PubMed Central

    Anchala, Raghupathy; Kaptoge, Stephen; Pant, Hira; Di Angelantonio, Emanuele; Franco, Oscar H.; Prabhakaran, D.

    2015-01-01

    Background Randomized control trials from the developed world report that clinical decision support systems (DSS) could provide an effective means to improve the management of hypertension (HTN). However, evidence from developing countries in this regard is rather limited, and there is a need to assess the impact of a clinical DSS on managing HTN in primary health care center (PHC) settings. Methods and Results We performed a cluster randomized trial to test the effectiveness and cost‐effectiveness of a clinical DSS among Indian adult hypertensive patients (between 35 and 64 years of age), wherein 16 PHC clusters from a district of Telangana state, India, were randomized to receive either a DSS or a chart‐based support (CBS) system. Each intervention arm had 8 PHC clusters, with a mean of 102 hypertensive patients per cluster (n=845 in DSS and 783 in CBS groups). Mean change in systolic blood pressure (SBP) from baseline to 12 months was the primary endpoint. The mean difference in SBP change from baseline between the DSS and CBS at the 12th month of follow‐up, adjusted for age, sex, height, waist, body mass index, alcohol consumption, vegetable intake, pickle intake, and baseline differences in blood pressure, was −6.59 mm Hg (95% confidence interval: −12.18 to −1.42; P=0.021). The cost‐effective ratio for CBS and DSS groups was $96.01 and $36.57 per mm of SBP reduction, respectively. Conclusion Clinical DSS are effective and cost‐effective in the management of HTN in resource‐constrained PHC settings. Clinical Trial Registration URL: http://www.ctri.nic.in. Unique identifier: CTRI/2012/03/002476. PMID:25559011

  20. Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders: A Scoping Review.

    PubMed

    Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S; Williams-Whitt, Kelly; Shaw, Nicola T; Hartvigsen, Jan; Qin, Ziling; Ha, Christine; Woodhouse, Linda J; Steenstra, Ivan A

    2016-09-01

    Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.

  1. GEOGRAPHICAL INFORMATION SYSTEM, DECISION SUPPORT SYSTEMS, AND URBAN STORMWATER MANAGEMENT

    EPA Science Inventory

    The full report reviews the application of Geographic Inforamtion System (GIS) technology to the field of urban stormwater modeling. The GIS literature is reviewed in the context of its use as a spatial database for urban stormwater modeling, integration of GIS and hydroloic time...

  2. Is there a "magic" hemoglobin number? Clinical decision support promoting restrictive blood transfusion practices.

    PubMed

    Goodnough, Lawrence Tim; Shah, Neil

    2015-10-01

    Blood transfusion has been identified as one of the most frequently performed therapeutic procedures, with a significant percentage of transfusions identified to be inappropriate. Recent key clinical trials in adults have provided Level 1 evidence to support restrictive red blood cell (RBC) transfusion practices. However, some advocates have attempted to identify a "correct" Hb threshold for RBC transfusion; whereas others assert that management of anemia, including transfusion decisions, must take into account clinical patient variables, rather than simply one diagnostic laboratory test. The heterogeneity of guidelines for blood transfusion by a number of medical societies reflects this controversy. Clinical decision support (CDS) uses a Hb threshold number in a smart Best Practices Alert (BPA) upon physician order, to trigger a concurrent utilization self-review for whether blood transfusion therapy is appropriate. This review summarizes Level 1 evidence in seven key clinical trials in adults that support restrictive transfusion practices, along strategies made possible by CDS that have demonstrated value in improving blood utilization by promoting restrictive transfusion practices.

  3. Towards knowledge-based systems in clinical practice: development of an integrated clinical information and knowledge management support system.

    PubMed

    Kalogeropoulos, Dimitris A; Carson, Ewart R; Collinson, Paul O

    2003-09-01

    Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

  4. Diabetes Telehealth and Computerized Decision Support Systems: A Sound System with a Human Touch Is Needed

    PubMed Central

    Holmström, Inger

    2010-01-01

    Telehealth holds the promise of improved consistency and fast and equal access to care, and will have great impact on future care. To enhance its quality and safety, computerized decision support systems (CDSS) have been launched. This commentary focuses specifically on the impact of telehealth and CDSS on diabetes patient management. Ideally, clinical information should be linked to evidence based recommendations and guidelines in the CDSS to provide tailored recommendations at the moment of care. However, technical support such as CDSS is not enough. The human touch is essential. A named healthcare provider with access to telehealth and CDSS seems to promise a way of providing both patient-centered and evidence-based care. PMID:20663469

  5. Using systems thinking to support clinical system transformation.

    PubMed

    Best, Allan; Berland, Alex; Herbert, Carol; Bitz, Jennifer; van Dijk, Marlies W; Krause, Christina; Cochrane, Douglas; Noel, Kevin; Marsden, Julian; McKeown, Shari; Millar, John

    2016-05-16

    Purpose - The British Columbia Ministry of Health's Clinical Care Management initiative was used as a case study to better understand large-scale change (LSC) within BC's health system. Using a complex system framework, the purpose of this paper is to examine mechanisms that enable and constrain the implementation of clinical guidelines across various clinical settings. Design/methodology/approach - Researchers applied a general model of complex adaptive systems plus two specific conceptual frameworks (realist evaluation and system dynamics mapping) to define and study enablers and constraints. Focus group sessions and interviews with clinicians, executives, managers and board members were validated through an online survey. Findings - The functional themes for managing large-scale clinical change included: creating a context to prepare clinicians for health system transformation initiatives; promoting shared clinical leadership; strengthening knowledge management, strategic communications and opportunities for networking; and clearing pathways through the complexity of a multilevel, dynamic system. Research limitations/implications - The action research methodology was designed to guide continuing improvement of implementation. A sample of initiatives was selected; it was not intended to compare and contrast facilitators and barriers across all initiatives and regions. Similarly, evaluating the results or process of guideline implementation was outside the scope; the methods were designed to enable conversations at multiple levels - policy, management and practice - about how to improve implementation. The study is best seen as a case study of LSC, offering a possible model for replication by others and a tool to shape further dialogue. Practical implications - Recommended action-oriented strategies included engaging local champions; supporting local adaptation for implementation of clinical guidelines; strengthening local teams to guide implementation; reducing

  6. An Oceanographic Decision Support System for Scientific Field Experiments

    NASA Astrophysics Data System (ADS)

    Maughan, T.; Das, J.; McCann, M. P.; Rajan, K.

    2011-12-01

    Thom Maughan, Jnaneshwar Das, Mike McCann, Danelle Cline, Mike Godin, Fred Bahr, Kevin Gomes, Tom O'Reilly, Frederic Py, Monique Messie, John Ryan, Francisco Chavez, Jim Bellingham, Maria Fox, Kanna Rajan Monterey Bay Aquarium Research Institute Moss Lading, California, United States Many of the coastal ocean processes we wish to observe in order to characterize marine ecosystems have large spatial extant (tens of square km) and are dynamic moving kilometers in a day with biological processes spanning anywhere from minutes to days. Some like harmful algal blooms generate toxins which can significantly impact human health and coastal economies. In order to obtain a viable understanding of the biogeochemical processes which define their dynamics and ecology, it is necessary to persistently observe, track and sample within and near the dynamic fields using augmented methods of observation such as autonomous platforms like AUVs, gliders and surface craft. Field experiments to plan, execute and manage such multitude of assets are challenging. To alleviate this problem the autonomous systems group with its collaborators at MBARI and USC designed, built and fielded a prototype Oceanographic Decision Support System (ODSS) that provides situational awareness and a single portal to visualize and plan deployments for the large scale October 2010 CANON field program as well as a series of 2 week field programs in 2011. The field programs were conducted in Monterey Bay, a known 'red tide' incubator, and varied from as many as twenty autonomous platforms, four ships and 2 manned airplanes to coordinated AUV operations, drifters and a single ship. The ODSS web-based portal was used to assimilate information from a collection of sources at sea, including AUVs, moorings, radar data as well as remote sensing products generated by partner organizations to provide a synthesis of views useful to predict the movement of a chlorophyll patch in the confines of the northern Monterey Bay

  7. Interface design principles for usable decision support: a targeted review of best practices for clinical prescribing interventions.

    PubMed

    Horsky, Jan; Schiff, Gordon D; Johnston, Douglas; Mercincavage, Lauren; Bell, Douglas; Middleton, Blackford

    2012-12-01

    Developing effective clinical decision support (CDS) systems for the highly complex and dynamic domain of clinical medicine is a serious challenge for designers. Poor usability is one of the core barriers to adoption and a deterrent to its routine use. We reviewed reports describing system implementation efforts and collected best available design conventions, procedures, practices and lessons learned in order to provide developers a short compendium of design goals and recommended principles. This targeted review is focused on CDS related to medication prescribing. Published reports suggest that important principles include consistency of design concepts across networked systems, use of appropriate visual representation of clinical data, use of controlled terminology, presenting advice at the time and place of decision making and matching the most appropriate CDS interventions to clinical goals. Specificity and contextual relevance can be increased by periodic review of trigger rules, analysis of performance logs and maintenance of accurate allergy, problem and medication lists in health records in order to help avoid excessive alerting. Developers need to adopt design practices that include user-centered, iterative design and common standards based on human-computer interaction (HCI) research methods rooted in ethnography and cognitive science. Suggestions outlined in this report may help clarify the goals of optimal CDS design but larger national initiatives are needed for systematic application of human factors in health information technology (HIT) development. Appropriate design strategies are essential for developing meaningful decision support systems that meet the grand challenges of high-quality healthcare.

  8. Physician Attitudes toward Adopting Genome-Guided Prescribing through Clinical Decision Support.

    PubMed

    Overby, Casey Lynnette; Erwin, Angelika Ludtke; Abul-Husn, Noura S; Ellis, Stephen B; Scott, Stuart A; Obeng, Aniwaa Owusu; Kannry, Joseph L; Hripcsak, George; Bottinger, Erwin P; Gottesman, Omri

    2014-01-01

    This study assessed physician attitudes toward adopting genome-guided prescribing through clinical decision support (CDS), prior to enlisting in the Clinical Implementation of Personalized Medicine through Electronic Health Records and Genomics pilot pharmacogenomics project (CLIPMERGE PGx). We developed a survey instrument that includes the Evidence Based Practice Attitude Scale, adapted to measure attitudes toward adopting genome-informed interventions (EBPAS-GII). The survey also includes items to measure physicians' characteristics (awareness, experience, and perceived usefulness), attitudes about personal genome testing (PGT) services, and comfort using technology. We surveyed 101 General Internal Medicine physicians from the Icahn School of Medicine at Mount Sinai (ISMMS). The majority were residency program trainees (~88%). Prior to enlisting into CLIPMERGE PGx, most physicians were aware of and had used decision support aids. Few physicians, however, were aware of and had used genome-guided prescribing. The majority of physicians viewed decision support aids and genotype data as being useful for making prescribing decisions. Most physicians had not heard of, but were willing to use, PGT services and felt comfortable interpreting PGT results. Most physicians were comfortable with technology. Physicians who perceived genotype data to be useful in making prescribing decisions, had more positive attitudes toward adopting genome-guided prescribing through CDS. Our findings suggest that internal medicine physicians have a deficit in their familiarity and comfort interpreting and using genomic information. This has reinforced the importance of gathering feedback and guidance from our enrolled physicians when designing genome-guided CDS and the importance of prioritizing genomic medicine education at our institutions. PMID:25562141

  9. Decision System Integrating Preferences to Support Sleep Staging.

    PubMed

    Ugon, Adrien; Sedki, Karima; Kotti, Amina; Seroussi, Brigitte; Philippe, Carole; Ganascia, Jean-Gabriel; Garda, Patrick; Bouaud, Jacques; Pinna, Andrea

    2016-01-01

    Scoring sleep stages can be considered as a classification problem. Once the whole recording segmented into 30-seconds epochs, features, extracted from raw signals, are typically injected into machine learning algorithms in order to build a model able to assign a sleep stage, trying to mimic what experts have done on the training set. Such approaches ignore the advances in sleep medicine, in which guidelines have been published by the AASM, providing definitions and rules that should be followed to score sleep stages. In addition, these approaches are not able to solve conflict situations, in which criteria of different sleep stages are met. This work proposes a novel approach based on AASM guidelines. Rules are formalized integrating, for some of them, preferences allowing to support decision in conflict situations. Applied to a doubtful epoch, our approach has taken the appropriate decision. PMID:27577436

  10. Infrastructure support for Clinical Information Systems

    SciTech Connect

    McGovern, Greg, A.

    2007-06-15

    Executive Summary: For the past 5 years, Adventist Health has been implementing a clinical information system, titled Project IntelliCare, throughout its 19 hospitals. To successfully do this, a commitment was made to ensure continuous availability of vital patient health information to the local hospitals. This commitment required a centralized data center with sufficient capacity and a backup data center to be used in case of technical software or natural disaster where interruptions could occur. The DOE grant provided financial assistance to purchase equipment to increase the capacity of an existing data center, along with purchase of more sophisticated software for the data center thus providing a reduction in time that information is unavailable to the local hospitals when hardware or software problems occur. Relative to public good, this translates into increased safety and convenience for the patients we serve because their electronic medical records are current and available a higher percentage of the time.

  11. Using a service oriented architecture approach to clinical decision support: performance results from two CDS Consortium demonstrations.

    PubMed

    Paterno, Marilyn D; Goldberg, Howard S; Simonaitis, Linas; Dixon, Brian E; Wright, Adam; Rocha, Beatriz H; Ramelson, Harley Z; Middleton, Blackford

    2012-01-01

    The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial. Data were gathered during each 6 month period and analyzed to assess performance, reliability, and response time in the form of means and standard deviations for all technical components of the service, including assembling and preparation of input data. The mean service call time for each period was just over 2 seconds. In this paper we report on the findings and analysis to date while describing the areas for further analysis and optimization as we continue to expand our use of a Services Oriented Architecture approach for CDS across multiple institutions.

  12. Design of a decision support system for preventive maintenance planning in health structures.

    PubMed

    Miniati, Roberto; Dori, Fabrizio; Gentili, Guido Biffi

    2012-01-01

    The appropriate maintenance of medical devices, including performance inspections and preventive maintenance, is fundamental in mitigating clinical risk caused by adverse events in health care. Although several models for managing and planning preventive maintenance have been developed, the problem is lacking in standard methodology and still presents an open challenge for today's health experts. This paper aims to provide and develop methodology together with support systems able to assist decision makers in constructing preventive maintenance and performance inspection plans, taking into account both the technical and economic needs of hospital clinical engineering departments. Interventions by decision makers are of crucial importance within complex situations where large numbers, types of devices and different contractual situations are involved. SISMA system has achieved optimal results with minimum expense and maximum security for patients and technicians at the University Hospital of Florence where it has been applied in actual case studies. PMID:22735735

  13. An information retrieval service to support clinical decision-making at the point of care.

    PubMed Central

    Sullivan, F; Gardner, M; van Rijsbergen, K

    1999-01-01

    The information retrieval systems currently available in general practice, such as Medline, and web search engines are passive and relatively difficult to access during consultations. Emergent technologies, including the National Electronic Library for Health, offer opportunities for more active decision support. We examine the extent to which information retrieval could support primary care consultations by examining the impact of the new technology at different stages of the consultation. We advocate a system whereby professional organisations concerned with quality of care, such as the Royal College of General Practitioners, might contribute the the process. PMID:10824349

  14. Hydrologic Drought Decision Support System (HyDroDSS)

    USGS Publications Warehouse

    Granato, Gregory E.

    2014-01-01

    The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions

  15. Mining balance disorders' data for the development of diagnostic decision support systems.

    PubMed

    Exarchos, T P; Rigas, G; Bibas, A; Kikidis, D; Nikitas, C; Wuyts, F L; Ihtijarevic, B; Maes, L; Cenciarini, M; Maurer, C; Macdonald, N; Bamiou, D-E; Luxon, L; Prasinos, M; Spanoudakis, G; Koutsouris, D D; Fotiadis, D I

    2016-10-01

    In this work we present the methodology for the development of the EMBalance diagnostic Decision Support System (DSS) for balance disorders. Medical data from patients with balance disorders have been analysed using data mining techniques for the development of the diagnostic DSS. The proposed methodology uses various data, ranging from demographic characteristics to clinical examination, auditory and vestibular tests, in order to provide an accurate diagnosis. The system aims to provide decision support for general practitioners (GPs) and experts in the diagnosis of balance disorders as well as to provide recommendations for the appropriate information and data to be requested at each step of the diagnostic process. Detailed results are provided for the diagnosis of 12 balance disorders, both for GPs and experts. Overall, the reported accuracy ranges from 59.3 to 89.8% for GPs and from 74.3 to 92.1% for experts.

  16. Mining balance disorders' data for the development of diagnostic decision support systems.

    PubMed

    Exarchos, T P; Rigas, G; Bibas, A; Kikidis, D; Nikitas, C; Wuyts, F L; Ihtijarevic, B; Maes, L; Cenciarini, M; Maurer, C; Macdonald, N; Bamiou, D-E; Luxon, L; Prasinos, M; Spanoudakis, G; Koutsouris, D D; Fotiadis, D I

    2016-10-01

    In this work we present the methodology for the development of the EMBalance diagnostic Decision Support System (DSS) for balance disorders. Medical data from patients with balance disorders have been analysed using data mining techniques for the development of the diagnostic DSS. The proposed methodology uses various data, ranging from demographic characteristics to clinical examination, auditory and vestibular tests, in order to provide an accurate diagnosis. The system aims to provide decision support for general practitioners (GPs) and experts in the diagnosis of balance disorders as well as to provide recommendations for the appropriate information and data to be requested at each step of the diagnostic process. Detailed results are provided for the diagnosis of 12 balance disorders, both for GPs and experts. Overall, the reported accuracy ranges from 59.3 to 89.8% for GPs and from 74.3 to 92.1% for experts. PMID:27619194

  17. Adaptation of a Published Risk Model to Point-of-care Clinical Decision Support Tailored to Local Workflow.

    PubMed

    Sobel, Jeffrey L; Baker, Craig C; Levy, David; Cain, Carol H

    2015-01-01

    Electronic clinical decision support can bring newly published knowledge to the point of care. However, local organizational buy-in, support for team workflows, IT system ease of use and other sociotechnical factors are needed to promote adoption. We successfully implemented a multi-variate cardiac risk stratification model from another institution into ours. We recreated the model and integrated it into our workflow, accessing it from our EHR with patient-specific data and facilitating clinical documentation if the user accepts the model results. Our clinical leaders championed the change and led educational dissemination efforts. We describe the ad-hoc social and technical collaboration needed to build and deploy the tool. The tool complements a clinical initiative within a community of practice, and is correlated with appropriate use of nuclear imaging. PMID:26958255

  18. Information/Knowledge Acquisition Methods for Decision Support Systems and Expert Systems.

    ERIC Educational Resources Information Center

    Yang, Heng-Li

    1995-01-01

    Compares information requirement-elicitation (IRE) methods for decision support systems (DSS) with knowledge acquisition (KA) methods for expert systems (ES) development. The definition and architectures of ES and DSS are compared and the systems' development cycles and IRE/KA methods are discussed. Differences are noted between ES and DSS…

  19. Performance of online drug information databases as clinical decision support tools in infectious disease medication management.

    PubMed

    Polen, Hyla H; Zapantis, Antonia; Clauson, Kevin A; Clauson, Kevin Alan; Jebrock, Jennifer; Paris, Mark

    2008-01-01

    Infectious disease (ID) medication management is complex and clinical decision support tools (CDSTs) can provide valuable assistance. This study evaluated scope and completeness of ID drug information found in online databases by evaluating their ability to answer 147 question/answer pairs. Scope scores produced highest rankings (%) for: Micromedex (82.3), Lexi-Comp/American Hospital Formulary Service (81.0), and Medscape Drug Reference (81.0); lowest includes: Epocrates Online Premium (47.0), Johns Hopkins ABX Guide (45.6), and PEPID PDC (40.8). PMID:18999059

  20. Genetic stratification in myeloid diseases: from risk assessment to clinical decision support tool.

    PubMed

    Ofran, Yishai

    2014-10-01

    Genetic aberrations have become a dominant factor in the stratification of myeloid malignancies. Cytogenetic and a few mutation studies are the backbone of risk assessment models of myeloid malignancies which are a major consideration in clinical decisions, especially patient assignment for allogeneic stem cell transplantation. Progress in our understanding of the genetic basis of the pathogenesis of myeloid malignancies and the growing capabilities of mass sequencing may add new roles for the clinical usage of genetic data. A few recently identified mutations recognized to be associated with specific diseases or clinical scenarios may soon become part of the diagnostic criteria of such conditions. Mutational studies may also advance our capabilities for a more efficient patient selection process, assigning the most effective therapy at the best timing for each patient. The clinical utility of genetic data is anticipated to advance further with the adoption of deep sequencing and next-generation sequencing techniques. We herein suggest some future potential applications of sequential genetic data to identify pending deteriorations at time points which are the best for aggressive interventions such as allogeneic stem cell transplantation. Genetics is moving from being mostly a prognostic factor to becoming a multitasking decision support tool for hematologists. Physicians must pay attention to advances in molecular hematology as it will soon be accessible and influential for most of our patients.

  1. A framework for ecological decision support systems: Building the right systems and building the systems right

    USGS Publications Warehouse

    D'Erchia, Frank; Korschgen, Carl E.; Nyquist, M.; Root, Ralph; Sojda, Richard S.; Stine, Peter

    2001-01-01

    Workshops in the late 1990's launched the commitment of the U.S. Geological Survey's Biological Resources Division (BRD) to develop and implement decision support systems (DSS) applications. One of the primary goals of this framework document is to provide sufficient background and information for Department of the Interior (DOI) bureau stakeholders and other clients to determine the potential for DSS development. Such an understanding can assist them in carrying out effective land planning and management practices. This document provides a definition of DSS and its characteristics and capabilities. It proceeds to describe issues related to meeting resource managers needs, such as the needs for specific applications, customer requirements, information and technology transfer, user support, and institutionalization. Using the decision process as a means to guide DSS development and determine users needs is also discussed. We conclude with information on method to evaluate DSS development efforts and recommended procedures for verification and validation. 

  2. Introduction to Decision Support Systems for Risk Based Management of Contaminated Sites

    EPA Science Inventory

    A book on Decision Support Systems for Risk-based Management of contaminated sites is appealing for two reasons. First, it addresses the problem of contaminated sites, which has worldwide importance. Second, it presents Decision Support Systems (DSSs), which are powerful comput...

  3. Decision Support Systems Project. Design Review Conference, October 14-15, 1984. Summary Report of Findings.

    ERIC Educational Resources Information Center

    Tetlow, William L.

    Findings of a conference that reviewed and evaluated design decisions concerning the Decision Support System (DSS) Demonstrator are summarized. The DSS Demonstrator was designed by the National Center for Higher Education Management Systems as an example of the way in which microcomputer technology can support and make more effective planning and…

  4. Recommendations for Selecting Drug-Drug Interactions for Clinical Decision Support

    PubMed Central

    Tilson, Hugh; Hines, Lisa E.; McEvoy, Gerald; Weinstein, David M.; Hansten, Philip D.; Matuszewski, Karl; le Comte, Marianne; Higby-Baker, Stefanie; Hanlon, Joseph T.; Pezzullo, Lynn; Vieson, Kathleen; Helwig, Amy L.; Huang, Shiew-Mei; Perre, Anthony; Bates, David W.; Poikonen, John; Wittie, Michael A.; Grizzle, Amy J.; Brown, Mary; Malone, Daniel C.

    2016-01-01

    Purpose To recommend principles for including drug-drug interactions (DDIs) in clinical decision support. Methods A conference series was conducted to improve clinical decision support (CDS) for DDIs. The Content Workgroup met monthly by webinar from January 2013 to February 2014, with two in-person meetings to reach consensus. The workgroup consisted of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information (IT) vendors, and healthcare organizations. Workgroup members addressed four key questions: (1) What process should be used to develop and maintain a standard set of DDIs?; (2) What information should be included in a knowledgebase of standard DDIs?; (3) Can/should a list of contraindicated drug pairs be established?; and (4) How can DDI alerts be more intelligently filtered? Results To develop and maintain a standard set of DDIs for CDS in the United States, we recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated, as only a small set of drug combinations are truly contraindicated. Finally, we recommend more research to identify methods to safely reduce repetitive and less relevant alerts. Conclusion A systematic ongoing process is necessary to select DDIs for alerting clinicians. We anticipate that our recommendations can lead to consistent and clinically relevant content for interruptive DDIs, and thus reduce alert fatigue and improve patient safety. PMID:27045070

  5. A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine

    PubMed Central

    2009-01-01

    Background In recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs. Discussion Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the Roadmap for National Action on Clinical Decision Support commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government. Summary A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for

  6. Development of a decision support system to predict physicians' rehabilitation protocols for patients with knee osteoarthritis.

    PubMed

    Hawamdeh, Ziad M; Alshraideh, Mohammad A; Al-Ajlouni, Jihad M; Salah, Imad K; Holm, Margo B; Otom, Ali H

    2012-09-01

    To design a medical decision support system (MDSS) that would accurately predict the rehabilitation protocols prescribed by the physicians for patients with knee osteoarthritis (OA) using only their demographic and clinical characteristics. The demographic and clinical variables for 170 patients receiving one of three treatment protocols for knee OA were entered into the MDSS. Demographic variables in the model were age and sex. Clinical variables entered into the model were height, weight, BMI, affected side, severity of knee OA, and severity of pain. All patients in the study received one of three treatment protocols for patients with knee OA: (a) hot packs, followed by electrotherapy and exercise, (b) ice packs, followed by ultrasound and exercise and (c) exercise alone. The resilient back propagation artificial neural network algorithm was used, with a ten-fold cross-validation. It was estimated that the MDSS is able to accurately predict the treatment prescribed by the physician for 87% of the patients. We developed an artificial neural network-based decision support system that can viably aid physicians in determining which treatment protocol would best match the anthropometric and clinical characteristics of patients with knee OA. PMID:22508428

  7. Modeling the costs of clinical decision support for genomic precision medicine.

    PubMed

    Mathias, Patrick C; Tarczy-Hornoch, Peter; Shirts, Brian H

    2016-01-01

    Clinical decision support (CDS) within the electronic health record represents a promising mechanism to provide important genomic findings within clinical workflows. To better understand the current and possible future costs of genomic CDS, we leveraged our local CDS experience to assemble a simple model with inputs such as initial cost and numbers of patients, rules, and institutions. Our model assumed efficiencies of scale and allowed us to perform a one-way sensitivity analysis of the impact of each model input. The number of patients with genomic results per institution was the only single variable that could decrease the cost of CDS per useful alert below projected genomic sequencing costs. Because of the prohibitive upfront cost of sequencing large numbers of individuals, increasing the number of institutions using genomic CDS and improving the efficiency of sharing CDS infrastructure represent the most promising paths to making genomic CDS cost-effective. PMID:27570652

  8. Modeling the costs of clinical decision support for genomic precision medicine

    PubMed Central

    Mathias, Patrick C.; Tarczy-Hornoch, Peter; Shirts, Brian H.

    2016-01-01

    Clinical decision support (CDS) within the electronic health record represents a promising mechanism to provide important genomic findings within clinical workflows. To better understand the current and possible future costs of genomic CDS, we leveraged our local CDS experience to assemble a simple model with inputs such as initial cost and numbers of patients, rules, and institutions. Our model assumed efficiencies of scale and allowed us to perform a one-way sensitivity analysis of the impact of each model input. The number of patients with genomic results per institution was the only single variable that could decrease the cost of CDS per useful alert below projected genomic sequencing costs. Because of the prohibitive upfront cost of sequencing large numbers of individuals, increasing the number of institutions using genomic CDS and improving the efficiency of sharing CDS infrastructure represent the most promising paths to making genomic CDS cost-effective. PMID:27570652

  9. Decentralizing Data through Decision-Support Systems: The Impact of Increased Access to Data on Decision Making

    ERIC Educational Resources Information Center

    Petrides, Lisa A.; McClelland, Sara I.

    2007-01-01

    This study examines the impact of a new Decision-Support System (DSS) on decision making in a community college in California. It looks at how attitudes and behaviors about data and their use were impacted by the implementation of a new DSS. The study found that the decentralization of data, through the DSS, produced a shift in terms of an…

  10. Information Systems to Support a Decision Process at Stanford.

    ERIC Educational Resources Information Center

    Chaffee, Ellen Earle

    1982-01-01

    When a rational decision process is desired, information specialists can contribute information and also contribute to the process in which that information is used, thereby promoting rational decision-making. The contribution of Stanford's information specialists to rational decision-making is described. (MLW)

  11. Hydrologic Drought Decision Support System (HyDroDSS)

    USGS Publications Warehouse

    Granato, Gregory E.

    2014-01-01

    The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions

  12. The utility of an online diagnostic decision support system (Isabel) in general practice: a process evaluation

    PubMed Central

    Henderson, Emily J; Rubin, Greg P

    2013-01-01

    Objectives To evaluate the utility of Isabel, an online diagnostic decision support system developed by Isabel Healthcare primarily for secondary medical care, in the general practice setting. Design Focus groups were conducted with clinicians to understand why and how they used the system. A modified online post-use survey asked practitioners about its impact on their decision-making. Normalization process theory (NPT) was used as a theoretical framework to determine whether the system could be incorporated into routine clinical practice. Setting The system was introduced by NHS County Durham and Darlington in the UK in selected general practices as a three-month pilot. Participants General practitioners and nurse practitioners who had access to Isabel as part of the Primary Care Trust's pilot. Main outcome measures General practitioners’ views, experiences and usage of the system. Results Seven general practices agreed to pilot Isabel. Two practices did not subsequently use it. The remaining five practices conducted searches on 16 patients. Post-use surveys (n = 10) indicated that Isabel had little impact on diagnostic decision-making. Focus group participants stated that, although the diagnoses produced by Isabel in general did not have an impact on their decision-making, they would find the tool useful if it were better tailored to the primary care setting. Our analysis concluded that normalization was not likely to occur in its current form. Conclusions Isabel was of limited utility in this short pilot study and may need further modification for use in general practice. PMID:23772310

  13. A randomized trial of population-based clinical decision support to manage health and resource use for Medicaid beneficiaries.

    PubMed

    Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Silvey, Garry M; Willis, Janese M; Johnson, Fred S; Edwards, Rex; Simo, Jessica; Phillips, Pam; Crosslin, David R; Eisenstein, Eric L

    2013-02-01

    To determine whether a clinical decision support system can favorably impact the delivery of emergency department and hospital services. Randomized clinical trial of three clinical decision support delivery modalities: email messages to care managers (email), printed reports to clinic administrators (report) and letters to patients (letter) conducted among 20,180 Medicaid beneficiaries in Durham County, North Carolina with follow-up through 9 months. Patients in the email group had fewer low-severity emergency department encounters vs. controls (8.1 vs. 10.6/100 enrollees, p < 0.001) with no increase in outpatient encounters or medical costs. Patients in the letter group had more outpatient encounters and greater outpatient and total medical costs. There were no treatment-related differences for patients in the reports group. Among patients <18 years, those in the email group had fewer low severity (7.6 vs. 10.6/100 enrollees, p < 0.001) and total emergency department encounters (18.3 vs. 23.5/100 enrollees, p < 0.001), and lower emergency department ($63 vs. $89, p = 0.002) and total medical costs ($1,736 vs. $2,207, p = 0.009). Patients who were ≥18 years in the letter group had greater outpatient medical costs. There were no intervention-related differences in patient-reported assessments of quality of life and medical care received. The effectiveness of clinical decision support messaging depended upon the delivery modality and patient age. Health IT interventions must be carefully evaluated to ensure that the resultant outcomes are aligned with expectations as interventions can have differing effects on clinical and economic outcomes.

  14. A Clinical Support System Based on Quality of Life Estimation.

    PubMed

    Faria, Brígida Mónica; Gonçalves, Joaquim; Reis, Luis Paulo; Rocha, Álvaro

    2015-10-01

    Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

  15. A Clinical Support System Based on Quality of Life Estimation.

    PubMed

    Faria, Brígida Mónica; Gonçalves, Joaquim; Reis, Luis Paulo; Rocha, Álvaro

    2015-10-01

    Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision. PMID:26277614

  16. Agricultural Model for the Nile Basin Decision Support System

    NASA Astrophysics Data System (ADS)

    van der Bolt, Frank; Seid, Abdulkarim

    2014-05-01

    To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.

  17. Usability Testing and Adaptation of the Pediatric Cardiovascular Risk Reduction Clinical Decision Support Tool

    PubMed Central

    Furberg, Robert D; Bagwell, Jacqueline E; LaBresh, Kenneth A

    2016-01-01

    Background Cardiovascular disease (CVD) is 1 of the leading causes of death, years of life lost, and disability-adjusted years of life lost worldwide. CVD prevention for children and teens is needed, as CVD risk factors and behaviors beginning in youth contribute to CVD development. In 2012, the National Heart, Lung, and Blood Institute released their “Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents” for clinicians, describing CVD risk factors they should address with patients at primary care preventative visits. However, uptake of new guidelines is slow. Clinical decision support (CDS) tools can improve guideline uptake. In this paper, we describe our process of testing and adapting a CDS tool to help clinicians evaluate patient risk, recommend behaviors to prevent development of risk, and complete complex calculations to determine appropriate interventions as recommended by the guidelines, using a user-centered design approach. Objective The objective of the study was to assess the usability of a pediatric CVD risk factor tool by clinicians. Methods The tool was tested using one-on-one in-person testing and a “think aloud” approach with 5 clinicians and by using the tool in clinical practice along with formal usability metrics with 14 pediatricians. Thematic analysis of the data from the in-person testing and clinical practice testing identified suggestions for change in 3 major areas: user experience, content refinement, and technical deployment. Descriptive statistical techniques were employed to summarize users’ overall experience with the tool. Results Data from testers showed that general reactions toward the CDS tool were positive. Clinical practice testers suggested revisions to make the application more user-friendly, especially for clinicians using the application on the iPhone, and called for refining recommendations to be more succinct and better tailored to the patient. Tester feedback was

  18. A decision support system for pre-earthquake planning of lifeline networks

    SciTech Connect

    Liang, J.W.

    1996-12-01

    This paper describes the frame of a decision support system for pre-earthquake planning of gas and water networks. The system is mainly based on the earthquake experiences and lessons from the 1976 Tangshan earthquake. The objective of the system is to offer countermeasures and help make decisions for seismic strengthening, remaking, and upgrading of gas and water networks.

  19. Information System Engineering Supporting Observation, Orientation, Decision, and Compliant Action

    NASA Astrophysics Data System (ADS)

    Georgakopoulos, Dimitrios

    The majority of today's software systems and organizational/business structures have been built on the foundation of solving problems via long-term data collection, analysis, and solution design. This traditional approach of solving problems and building corresponding software systems and business processes, falls short in providing the necessary solutions needed to deal with many problems that require agility as the main ingredient of their solution. For example, such agility is needed in responding to an emergency, in military command control, physical security, price-based competition in business, investing in the stock market, video gaming, network monitoring and self-healing, diagnosis in emergency health care, and many other areas that are too numerous to list here. The concept of Observe, Orient, Decide, and Act (OODA) loops is a guiding principal that captures the fundamental issues and approach for engineering information systems that deal with many of these problem areas. However, there are currently few software systems that are capable of supporting OODA. In this talk, we provide a tour of the research issues and state of the art solutions for supporting OODA. In addition, we provide specific examples of OODA solutions we have developed for the video surveillance and emergency response domains.

  20. Systems Analysis and Design for Decision Support Systems on Economic Feasibility of Projects

    NASA Astrophysics Data System (ADS)

    Balaji, S. Arun

    2010-11-01

    This paper discuss about need for development of the Decision Support System (DSS) software for economic feasibility of projects in Rwanda, Africa. The various economic theories needed and the corresponding formulae to compute payback period, internal rate of return and benefit cost ratio of projects are clearly given in this paper. This paper is also deals with the systems flow chart to fabricate the system in any higher level computing language. The various input requirements from the projects and the output needed for the decision makers are also included in this paper. The data dictionary used for input and output data structure is also explained.

  1. Decision Support Systems: Applications in Statistics and Hypothesis Testing.

    ERIC Educational Resources Information Center

    Olsen, Christopher R.; Bozeman, William C.

    1988-01-01

    Discussion of the selection of appropriate statistical procedures by educators highlights a study conducted to investigate the effectiveness of decision aids in facilitating the use of appropriate statistics. Experimental groups and a control group using a printed flow chart, a computer-based decision aid, and a standard text are described. (11…

  2. Decision support system for monitoring environmental-human interactions.

    PubMed

    Delavari-Edalat, Farideh; Abdi, M Reza

    2009-06-01

    The specific aim of this study is to investigate popular attitudes toward trees. The paper is involved the understanding of biophilia tendencies with respect to people's views in an urban area. Biophilia is considered as the idea insisting on the dependency of human identity on his relationship with nature. The biophilia fundamental tendencies were explored to establish a biological framework for valuing and affiliating the natural world. Accordingly, the nine tendencies i.e. utilitarian, naturalistic, ecologistic-scientific, aesthetic, symbolic, humanistic, moralistic, dominionistic, and negativistic were investigate to find out how people relate to the nature especially trees. The investigation was based on a quantitative interview which was applied to the public population in the Liverpool urban parks. Data collected from the designed questionnaire was followed by analysis of the data to identify people's attitudes towards trees. The results indicated how important the physical appeal and beauty of trees was for the people and also showed the people's emotional attachments to trees. Furthermore, a decision support model was proposed to evaluate human instincts and preferences in relation to their surrounding areas using the Analytical Hierarchical Process (AHP). The proposed model composed the environmental factors and the biophilia tendencies as the criteria of evaluating environmental-human interactions. A case study was then conducted in Liverpool parks to examine theses interactions. The data gathered was used as the input to the AHP model for the attribute analysis. The AHP model would enable environment managers to compose the relevant information via a link between human feelings about urban trees, and environmental factors for monitoring purposes and performance analysis.

  3. Use of Simulation to Study Nurses Acceptance and Non-Acceptance of Clinical Decision Support Suggestions

    PubMed Central

    Sousa, Vanessa E. C.; Lopez, Karen Dunn; Febretti, Alessandro; Stifter, Janet; Yao, Yingwei; Johnson, Andrew; Wilkie, Diana J.; Keenan, Gail M.

    2015-01-01

    Our long term goal is to ensure nurse clinical decision support (CDS) works as intended before full deployment in clinical practice. As part of a broader effort, this pilot explores factors influencing acceptance/non-acceptance of 8 CDS suggestions displayed through selecting a blinking red button in an electronic health record (EHR) based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the CDS suggestions. Of 168 total suggestions displayed during the experiment (8 for each of the 21 nurses), 123 (73.2%) were accepted and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was 7 of 8 with only 2 of 21 nurses accepting all. The main reason for CDS acceptance was the nurse’s belief that the suggestions were good for the patient (n=100%) with other features being secondarily reinforcing. Reasons for non-acceptance were less clear, with under half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high quality simulation and targeted questionnaires about specific CDS selections offers a cost effective means for testing before full deployment in clinical practice. PMID:26361268

  4. Enabling active and healthy ageing decision support systems with the smart collection of TV usage patterns.

    PubMed

    Billis, Antonis S; Batziakas, Asterios; Bratsas, Charalampos; Tsatali, Marianna S; Karagianni, Maria; Bamidis, Panagiotis D

    2016-03-01

    Smart monitoring of seniors behavioural patterns and more specifically activities of daily living have attracted immense research interest in recent years. Development of smart decision support systems to support the promotion of health smart homes has also emerged taking advantage of the plethora of smart, inexpensive and unobtrusive monitoring sensors, devices and software tools. To this end, a smart monitoring system has been used in order to extract meaningful information about television (TV) usage patterns and subsequently associate them with clinical findings of experts. The smart TV operating state remote monitoring system was installed in four elderly women homes and gathered data for more than 11 months. Results suggest that TV daily usage (time the TV is turned on) can predict mental health change. Conclusively, the authors suggest that collection of smart device usage patterns could strengthen the inference capabilities of existing health DSSs applied in uncontrolled settings such as real senior homes.

  5. Enabling active and healthy ageing decision support systems with the smart collection of TV usage patterns

    PubMed Central

    Billis, Antonis S.; Batziakas, Asterios; Bratsas, Charalampos; Tsatali, Marianna S.; Karagianni, Maria

    2016-01-01

    Smart monitoring of seniors behavioural patterns and more specifically activities of daily living have attracted immense research interest in recent years. Development of smart decision support systems to support the promotion of health smart homes has also emerged taking advantage of the plethora of smart, inexpensive and unobtrusive monitoring sensors, devices and software tools. To this end, a smart monitoring system has been used in order to extract meaningful information about television (TV) usage patterns and subsequently associate them with clinical findings of experts. The smart TV operating state remote monitoring system was installed in four elderly women homes and gathered data for more than 11 months. Results suggest that TV daily usage (time the TV is turned on) can predict mental health change. Conclusively, the authors suggest that collection of smart device usage patterns could strengthen the inference capabilities of existing health DSSs applied in uncontrolled settings such as real senior homes. PMID:27284457

  6. Clinical decision support and acute low back pain: evidence-based order sets.

    PubMed

    Forseen, Scott E; Corey, Amanda S

    2012-10-01

    Low back pain is one of the most common reasons for visits to physicians in the ambulatory care setting. Estimated medical expenditures related to low back pain have increased disproportionately relative to the more modest increase in the prevalence of self-reported low back pain in the past decade. The increase in spine care expenditures has not been associated with improved patient outcomes. Evidence-based order templates presented in this article are designed to assist practitioners through the process of managing patients with acute low back pain. A logical method of choosing, developing, and implementing clinical decision support interventions is presented that is based on the best available scientific evidence. These templates may be reasonably expected to improve patient care, decrease inappropriate imaging utilization, reduce the inappropriate use of steroids and narcotics, and potentially decrease the number of inappropriate invasive procedures. PMID:23025864

  7. The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems

    NASA Technical Reports Server (NTRS)

    Kerstman, Eric; Minard, Charles; Saile, Lynn; deCarvalho, Mary Freire; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David

    2009-01-01

    The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.

  8. Decision Support System Based on Computational Collective Intelligence in Campus Information Systems

    NASA Astrophysics Data System (ADS)

    Saito, Yoshihito; Matsuo, Tokuro

    Education institutions such as universities have a lot of information including book information, equipment administrative information, student information, and several others. The institutions also have multiple information in time series. As collective intelligence in campus, integrating and reusing these preserved information regarding career and taking a class, university can effectively support students' decision making of their getting jobs and subjects choice. Our purpose of support is to increase student's motivation. In this paper, we focus on course record and job information included in students' information, and propose the method to analyze correlation between a pattern of taking class and job lined up. Afterwards, we propose a support system regarding getting a job and taking class by using our proposed method. For a student who has his/her favorite job to get, the system supports his/her decision making of lecture choice by recommending a set of appropriate lecture groups. On another hand, for a student who does not have favorite job to get, the system supports his/her decision making of getting job by presenting appropriate job families related with lecture group in which he/she has ever taken. The contribution of this paper is showing a concrete method to reuse the campus collective information, implementing a system, and user perspectives.

  9. Decision Support System in the Management of Resource-Sharing Networks.

    ERIC Educational Resources Information Center

    Dubey, Yogendra P.

    1984-01-01

    Reports on emergence of decision support system (DSS) as a practical approach for applying computers and information to problems facing management. Information processing and decision making in organizations, simulation-model-based DSS in management of library resource sharing networks, and a resource-sharing simulation system are highlighted.…

  10. Using clinical decision support as a means of implementing a universal postpartum depression screening program.

    PubMed

    Loudon, Holly; Nentin, Farida; Silverman, Michael E

    2016-06-01

    A major barrier to the diagnosis of postpartum depression (PPD) includes symptom detection. The lack of awareness and understanding of PPD among new mothers, the variability in clinical presentation, and the various diagnostic strategies can increase this further. The purpose of this study was to test the feasibility of adding clinical decision support (CDS) to the electronic health record (EHR) as a means of implementing a universal standardized PPD screening program within a large, at high risk, population. All women returning to the Mount Sinai Hospital OB/GYN Ambulatory Practice for postpartum care between 2010 and 2013 were presented with the Edinburgh Postnatal Depression Scale (EPDS) in response to a CDS "hard stop" built into the EHR. Of the 2102 women who presented for postpartum care, 2092 women (99.5 %) were screened for PPD in response to a CDS hard stop module. Screens were missing on ten records (0.5 %) secondary to refusal, language barrier, or lack of clarity in the EHR. Technology is becoming increasingly important in addressing the challenges faced by health care providers. While the identification of PPD has become the recent focus of public health concerns secondary to the significant social burden, numerous barriers to screening still exist within the clinical setting. The utility of adding CDS in the form of a hard stop, requiring clinicians to enter a standardized PPD mood assessment score to the patient EHR, offers a sufficient way to address a primary barrier to PPD symptom identification at the practitioner level.

  11. Methodical Approach to Developing a Decision Support System for Well Interventions Planning

    NASA Astrophysics Data System (ADS)

    Silich, V. A.; Savelev, A. O.; Isaev, A. N.

    2016-04-01

    The paper contains aspects of developing a decision support systems aimed for well interventions planning within the process of oil production engineering. The specific approach described by authors is based on system analysis methods and object model for system design. Declared number of problem-decision principles as follows: the principle of consolidated information area, the principle of integrated control, the principle of development process transparency. Also observed a set of models (class model, object model, attribute interdependence model, component model, coordination model) specified for designing decision support system for well intervention planning.

  12. A mobile decision support system for red eye diseases diagnosis: experience with medical students.

    PubMed

    López, Marta Manovel; López, Miguel Maldonado; de la Torre Díez, Isabel; Jimeno, José Carlos Pastor; López-Coronado, Miguel

    2016-06-01

    A good primary health care is the base for a better healthcare system. Taking a good decision on time by the primary health care physician could have a huge repercussion. In order to ease the diagnosis task arise the Decision Support Systems (DSS), which offer counselling instead of refresh the medical knowledge, in a profession where it is still learning every day. The implementation of these systems in diseases which are a frequent cause of visit to the doctor like ophthalmologic pathologies are, which affect directly to our quality of life, takes more importance. This paper aims to develop OphthalDSS, a totally new mobile DSS for red eye diseases diagnosis. The main utilities that OphthalDSS offers will be a study guide for medical students and a clinical decision support system for primary care professionals. Other important goal of this paper is to show the user experience results after OphthalDSS being used by medical students of the University of Valladolid. For achieving the main purpose of this research work, a decision algorithm will be developed and implemented by an Android mobile application. Moreover, the Quality of Experience (QoE) has been evaluated by the students through the questions of a short inquiry. The app developed which implements the algorithm OphthalDSS is capable of diagnose more than 30 eye's anterior segment diseases. A total of 67 medical students have evaluated the QoE. The students find the diseases' information presented very valuable, the appearance is adequate, it is always available and they have ever found what they were looking for. Furthermore, the students think that their quality of life has not been improved using the app and they can do the same without using the OphthalDSS app. OphthalDSS is easy to use, which is capable of diagnose more than 30 ocular diseases in addition to be used as a DSS tool as an educational tool at the same time.

  13. A mobile decision support system for red eye diseases diagnosis: experience with medical students.

    PubMed

    López, Marta Manovel; López, Miguel Maldonado; de la Torre Díez, Isabel; Jimeno, José Carlos Pastor; López-Coronado, Miguel

    2016-06-01

    A good primary health care is the base for a better healthcare system. Taking a good decision on time by the primary health care physician could have a huge repercussion. In order to ease the diagnosis task arise the Decision Support Systems (DSS), which offer counselling instead of refresh the medical knowledge, in a profession where it is still learning every day. The implementation of these systems in diseases which are a frequent cause of visit to the doctor like ophthalmologic pathologies are, which affect directly to our quality of life, takes more importance. This paper aims to develop OphthalDSS, a totally new mobile DSS for red eye diseases diagnosis. The main utilities that OphthalDSS offers will be a study guide for medical students and a clinical decision support system for primary care professionals. Other important goal of this paper is to show the user experience results after OphthalDSS being used by medical students of the University of Valladolid. For achieving the main purpose of this research work, a decision algorithm will be developed and implemented by an Android mobile application. Moreover, the Quality of Experience (QoE) has been evaluated by the students through the questions of a short inquiry. The app developed which implements the algorithm OphthalDSS is capable of diagnose more than 30 eye's anterior segment diseases. A total of 67 medical students have evaluated the QoE. The students find the diseases' information presented very valuable, the appearance is adequate, it is always available and they have ever found what they were looking for. Furthermore, the students think that their quality of life has not been improved using the app and they can do the same without using the OphthalDSS app. OphthalDSS is easy to use, which is capable of diagnose more than 30 ocular diseases in addition to be used as a DSS tool as an educational tool at the same time. PMID:27142275

  14. GET SMARTE: A DECISION SUPPORT SYSTEM TO REVITALIZE COMMUNITIES - CABERNET 2007

    EPA Science Inventory

    Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...

  15. GREENER CHEMICAL PROCESS DESIGN ALTERNATIVES ARE REVEALED USING THE WASTE REDUCTION DECISION SUPPORT SYSTEM (WAR DSS)

    EPA Science Inventory

    The Waste Reduction Decision Support System (WAR DSS) is a Java-based software product providing comprehensive modeling of potential adverse environmental impacts (PEI) predicted to result from newly designed or redesigned chemical manufacturing processes. The purpose of this so...

  16. Formative Evaluation of Clinician Experience with Integrating Family History-Based Clinical Decision Support into Clinical Practice

    PubMed Central

    Doerr, Megan; Edelman, Emily; Gabitzsch, Emily; Eng, Charis; Teng, Kathryn

    2014-01-01

    Family health history is a leading predictor of disease risk. Nonetheless, it is underutilized to guide care and, therefore, is ripe for health information technology intervention. To fill the family health history practice gap, Cleveland Clinic has developed a family health history collection and clinical decision support tool, MyFamily. This report describes the impact and process of implementing MyFamily into primary care, cancer survivorship and cancer genetics clinics. Ten providers participated in semi-structured interviews that were analyzed to identify opportunities for process improvement. Participants universally noted positive effects on patient care, including increases in quality, personalization of care and patient engagement. The impact on clinical workflow varied by practice setting, with differences observed in the ease of integration and the use of specific report elements. Tension between the length of the report and desired detail was appreciated. Barriers and facilitators to the process of implementation were noted, dominated by the theme of increased integration with the electronic medical record. These results fed real-time improvement cycles to reinforce clinician use. This model will be applied in future institutional efforts to integrate clinical genomic applications into practice and may be useful for other institutions considering the implementation of tools for personalizing medical management. PMID:25563219

  17. Decision-support systems for natural-hazards and land-management issues

    USGS Publications Warehouse

    Dinitz, Laura; Forney, William; Byrd, Kristin

    2012-01-01

    Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.

  18. Recycling decision support system: Design and development of a Web-based DSS. Master thesis

    SciTech Connect

    Tettelbach, C.G.

    1997-03-01

    The explosive growth of the World Wide Web creates new opportunities for the development and deployment of Decision Support Systems. No longer restricted by machine-specific limitations, Web-based Decision Support Systems (DSS) provide global access to widely diversified and geographically dispersed users through sharing of data, models, algorithms, and modeling environments. This thesis examines the design and development processes involved in the creation of a Web-based DSS. The Recycling Decision Support System utilizes a rapid prototype and refinement process to create a Web-based system focusing on supporting ordinary people and industrial users in making good decisions for recycling and disposal of household and industrial waste. Through abstraction of details from the specific Web-based DSS design, a generalized framework for supporting decision-making via the WWW is built which supports functionality in education, queries, and analysis of complex problems. An important aspect of this research is the development of a new architecture which conforms to the complexities specific to Web-based Decision Support Systems. Prompted by the additional interactions required for WWW connectivity, this architecture incorporates agents for negotiating transactions between the functional components of a standard DSS.

  19. Counseling About Medication-Induced Birth Defects with Clinical Decision Support in Primary Care

    PubMed Central

    Parisi, Sara M.; Handler, Steven M.; Koren, Gideon; Shevchik, Grant; Fischer, Gary S.

    2013-01-01

    Abstract Background We evaluated how computerized clinical decision support (CDS) affects the counseling women receive when primary care physicians (PCPs) prescribe potential teratogens and how this counseling affects women's behavior. Methods Between October 2008 and April 2010, all women aged 18–50 years visiting one of three community-based family practice clinics or an academic general internal medicine clinic were invited to complete a survey 5–30 days after their clinic visit. Women who received prescriptions were asked if they were counseled about teratogenic risks or contraception and if they used contraception at last intercourse. Results Eight hundred one women completed surveys; 27% received a prescription for a potential teratogen. With or without CDS, women prescribed potential teratogens were more likely than women prescribed safer medications to report counseling about teratogenic risks. However, even with CDS 43% of women prescribed potential teratogens reported no counseling. In multivariable models, women were more likely to report counseling if they saw a female PCP (odds ratio: 1.97; 95% confidence interval: 1.26–3.09). Women were least likely to report counseling if they received angiotensin-converting enzyme inhibitors or angiotensin receptor blockers. Women who were pregnant or trying to conceive were not more likely to report counseling. Nonetheless, women who received counseling about contraception or teratogenic risks were more likely to use contraception after being prescribed potential teratogens than women who received no counseling. Conclusions Physician counseling can reduce risk of medication-induced birth defects. However, efforts are needed to ensure that PCPs consistently inform women of teratogenic risks and provide access to highly effective contraception. PMID:23930947

  20. An Integrated Web-based Decision Support System in Disaster Risk Management

    NASA Astrophysics Data System (ADS)

    Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

    2012-04-01

    Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact

  1. Using Group Decision Support Systems in Teaching the Small Group Communication Course.

    ERIC Educational Resources Information Center

    Scott, Craig R.

    The nature of group decision support systems (GDSS), its key advantages, and the experience of using it with several classes help illustrate that this type of computer technology can serve an important function in supplementing instruction of the small group course. The primary purpose of a GDSS is to improve group decision-making and…

  2. Effectiveness of an Electronic Performance Support System on Computer Ethics and Ethical Decision-Making Education

    ERIC Educational Resources Information Center

    Kert, Serhat Bahadir; Uz, Cigdem; Gecu, Zeynep

    2014-01-01

    This study examined the effectiveness of an electronic performance support system (EPSS) on computer ethics education and the ethical decision-making processes. There were five different phases to this ten month study: (1) Writing computer ethics scenarios, (2) Designing a decision-making framework (3) Developing EPSS software (4) Using EPSS in a…

  3. Decision Support Systems (DSSs) For Contaminated Land Management - Gaps And Challenges

    EPA Science Inventory

    A plethora of information is available when considering decision support systems for risk-based management of contaminated land. Broad issues of what is contaminated land, what is a brownfield, and what is remediation are discussed in EU countries and the U.S. Making decisions ...

  4. Representing Human Expertise by the OWL Web Ontology Language to Support Knowledge Engineering in Decision Support Systems.

    PubMed

    Ramzan, Asia; Wang, Hai; Buckingham, Christopher

    2014-01-01

    Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

  5. An international observational study suggests that artificial intelligence for clinical decision support optimizes anemia management in hemodialysis patients.

    PubMed

    Barbieri, Carlo; Molina, Manuel; Ponce, Pedro; Tothova, Monika; Cattinelli, Isabella; Ion Titapiccolo, Jasmine; Mari, Flavio; Amato, Claudia; Leipold, Frank; Wehmeyer, Wolfgang; Stuard, Stefano; Stopper, Andrea; Canaud, Bernard

    2016-08-01

    Managing anemia in hemodialysis patients can be challenging because of competing therapeutic targets and individual variability. Because therapy recommendations provided by a decision support system can benefit both patients and doctors, we evaluated the impact of an artificial intelligence decision support system, the Anemia Control Model (ACM), on anemia outcomes. Based on patient profiles, the ACM was built to recommend suitable erythropoietic-stimulating agent doses. Our retrospective study consisted of a 12-month control phase (standard anemia care), followed by a 12-month observation phase (ACM-guided care) encompassing 752 patients undergoing hemodialysis therapy in 3 NephroCare clinics located in separate countries. The percentage of hemoglobin values on target, the median darbepoetin dose, and individual hemoglobin fluctuation (estimated from the intrapatient hemoglobin standard deviation) were deemed primary outcomes. In the observation phase, median darbepoetin consumption significantly decreased from 0.63 to 0.46 μg/kg/month, whereas on-target hemoglobin values significantly increased from 70.6% to 76.6%, reaching 83.2% when the ACM suggestions were implemented. Moreover, ACM introduction led to a significant decrease in hemoglobin fluctuation (intrapatient standard deviation decreased from 0.95 g/dl to 0.83 g/dl). Thus, ACM support helped improve anemia outcomes of hemodialysis patients, minimizing erythropoietic-stimulating agent use with the potential to reduce the cost of treatment.

  6. An international observational study suggests that artificial intelligence for clinical decision support optimizes anemia management in hemodialysis patients.

    PubMed

    Barbieri, Carlo; Molina, Manuel; Ponce, Pedro; Tothova, Monika; Cattinelli, Isabella; Ion Titapiccolo, Jasmine; Mari, Flavio; Amato, Claudia; Leipold, Frank; Wehmeyer, Wolfgang; Stuard, Stefano; Stopper, Andrea; Canaud, Bernard

    2016-08-01

    Managing anemia in hemodialysis patients can be challenging because of competing therapeutic targets and individual variability. Because therapy recommendations provided by a decision support system can benefit both patients and doctors, we evaluated the impact of an artificial intelligence decision support system, the Anemia Control Model (ACM), on anemia outcomes. Based on patient profiles, the ACM was built to recommend suitable erythropoietic-stimulating agent doses. Our retrospective study consisted of a 12-month control phase (standard anemia care), followed by a 12-month observation phase (ACM-guided care) encompassing 752 patients undergoing hemodialysis therapy in 3 NephroCare clinics located in separate countries. The percentage of hemoglobin values on target, the median darbepoetin dose, and individual hemoglobin fluctuation (estimated from the intrapatient hemoglobin standard deviation) were deemed primary outcomes. In the observation phase, median darbepoetin consumption significantly decreased from 0.63 to 0.46 μg/kg/month, whereas on-target hemoglobin values significantly increased from 70.6% to 76.6%, reaching 83.2% when the ACM suggestions were implemented. Moreover, ACM introduction led to a significant decrease in hemoglobin fluctuation (intrapatient standard deviation decreased from 0.95 g/dl to 0.83 g/dl). Thus, ACM support helped improve anemia outcomes of hemodialysis patients, minimizing erythropoietic-stimulating agent use with the potential to reduce the cost of treatment. PMID:27262365

  7. Formative assessment and design of a complex clinical decision support tool for pulmonary embolism.

    PubMed

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

    2016-02-01

    Electronic health record (EHR)-based clinical decision support (CDS) tools are rolled out with the urgency to meet federal requirements without time for usability testing and refinement of the user interface. As part of a larger project to design, develop and integrate a pulmonary embolism CDS tool for emergency physicians, we conducted a formative assessment to determine providers' level of interest and input on designs and content. This was a study to conduct a formative assessment of emergency medicine (EM) physicians that included focus groups and key informant interviews. The focus of this study was twofold, to determine the general attitude towards CDS tool integration and the ideal integration point into the clinical workflow. To accomplish this, we first approached EM physicians in a focus group, then, during key informant interviews, we presented workflow designs and gave a scenario to help the providers visualise how the CDS tool works. Participants were asked questions regarding the trigger location, trigger words, integration into their workflow, perceived utility and heuristic of the tool. Results from the participants' survey responses to trigger location, perceived utility and efficiency, indicated that the providers felt the tool would be more of a hindrance than an aid. However, some providers commented that they had not had exposure to CDS tools but had used online calculators, and thought the tools would be helpful at the point-of-care if integrated into the EHR. Furthermore, there was a preference for an order entry wireframe. This study highlights several factors to consider when designing CDS tools: (1) formative assessment of EHR functionality and clinical environment workflow, (2) focus groups and key informative interviews to incorporate providers' perceptions of CDS and workflow integration and/or (3) the demonstration of proposed workflows through wireframes to help providers visualise design concepts.

  8. DECISION-SUPPORT TOOLS FOR MANAGING WASTEWATER COLLECTION SYSTEMS

    EPA Science Inventory

    Wastewater collection systems are an extensive part of the nation's infrastructure. As these systems become older, more preventative maintenance and renewal are required. For municipalities to cost-effectively plan, organize, and implement this effort, they require improved inf...

  9. Mathematical Modeling of spatial disease variables by Spatial Fuzzy Logic for Spatial Decision Support Systems

    NASA Astrophysics Data System (ADS)

    Platz, M.; Rapp, J.; Groessler, M.; Niehaus, E.; Babu, A.; Soman, B.

    2014-11-01

    A Spatial Decision Support System (SDSS) provides support for decision makers and should not be viewed as replacing human intelligence with machines. Therefore it is reasonable that decision makers are able to use a feature to analyze the provided spatial decision support in detail to crosscheck the digital support of the SDSS with their own expertise. Spatial decision support is based on risk and resource maps in a Geographic Information System (GIS) with relevant layers e.g. environmental, health and socio-economic data. Spatial fuzzy logic allows the representation of spatial properties with a value of truth in the range between 0 and 1. Decision makers can refer to the visualization of the spatial truth of single risk variables of a disease. Spatial fuzzy logic rules that support the allocation of limited resources according to risk can be evaluated with measure theory on topological spaces, which allows to visualize the applicability of this rules as well in a map. Our paper is based on the concept of a spatial fuzzy logic on topological spaces that contributes to the development of an adaptive Early Warning And Response System (EWARS) providing decision support for the current or future spatial distribution of a disease. It supports the decision maker in testing interventions based on available resources and apply risk mitigation strategies and provide guidance tailored to the geo-location of the user via mobile devices. The software component of the system would be based on open source software and the software developed during this project will also be in the open source domain, so that an open community can build on the results and tailor further work to regional or international requirements and constraints. A freely available EWARS Spatial Fuzzy Logic Demo was developed wich enables a user to visualize risk and resource maps based on individual data in several data formats.

  10. At the Intersection of Health Information Technology and Decision Support: Measurement Feedback Systems... and Beyond.

    PubMed

    Chorpita, Bruce F; Daleiden, Eric L; Bernstein, Adam D

    2016-05-01

    We select and comment on concepts and examples from the target articles in this special issue on measurement feedback systems, placing them in the context of some of our own insights and ideas about measurement feedback systems, and where those systems lie at the intersection of technology and decision making. We contend that, connected to the many implementation challenges relevant to many new technologies, there are fundamental design challenges that await a more elaborate specification of the clinical information and decision models that underlie these systems. Candidate features of such models are discussed, which include referencing multiple evidence bases, facilitating observed and expected value comparisons, fostering collaboration, and allowing translation across multiple ontological systems. We call for a new metaphor for these technologies that goes beyond measurement feedback and encourages a deeper consideration of the increasingly complex clinical decision models needed to manage the uncertainty of delivering clinical care. PMID:26604202

  11. Decision support systems in water and wastewater treatment process selection and design: a review.

    PubMed

    Hamouda, M A; Anderson, W B; Huck, P M

    2009-01-01

    The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach. PMID:19809138

  12. A decision support system for map projections of small scale data

    USGS Publications Warehouse

    Finn, Michael P.; Usery, E. Lynn; Posch, Stephan T.; Seong, Jeong Chang

    2004-01-01

    The use of commercial geographic information system software to process large raster datasets of terrain elevation, population, land cover, vegetation, soils, temperature, and rainfall requires both projection from spherical coordinates to plane coordinate systems and transformation from one plane system to another. Decision support systems deliver information resulting in knowledge that assists in policies, priorities, or processes. This paper presents an approach to handling the problems of raster dataset projection and transformation through the development of a Web-enabled decision support system to aid users of transformation processes with the selection of appropriate map projections based on data type, areal extent, location, and preservation properties.

  13. DECISION SUPPORT TOOLS FOR MANAGING WASTEWATER COLLECTION SYSTEMS

    EPA Science Inventory

    Wastewater collection systems are an extensive part of the nation's infrastructure. In the US approximately 150M people are served by about 19,000 municipal wastewater collection systems representing about 500,000 miles of sewer pipe (not including privately owned service lateria...

  14. Intelligent decision support algorithm for distribution system restoration.

    PubMed

    Singh, Reetu; Mehfuz, Shabana; Kumar, Parmod

    2016-01-01

    Distribution system is the means of revenue for electric utility. It needs to be restored at the earliest if any feeder or complete system is tripped out due to fault or any other cause. Further, uncertainty of the loads, result in variations in the distribution network's parameters. Thus, an intelligent algorithm incorporating hybrid fuzzy-grey relation, which can take into account the uncertainties and compare the sequences is discussed to analyse and restore the distribution system. The simulation studies are carried out to show the utility of the method by ranking the restoration plans for a typical distribution system. This algorithm also meets the smart grid requirements in terms of an automated restoration plan for the partial/full blackout of network.

  15. Intelligent decision support algorithm for distribution system restoration.

    PubMed

    Singh, Reetu; Mehfuz, Shabana; Kumar, Parmod

    2016-01-01

    Distribution system is the means of revenue for electric utility. It needs to be restored at the earliest if any feeder or complete system is tripped out due to fault or any other cause. Further, uncertainty of the loads, result in variations in the distribution network's parameters. Thus, an intelligent algorithm incorporating hybrid fuzzy-grey relation, which can take into account the uncertainties and compare the sequences is discussed to analyse and restore the distribution system. The simulation studies are carried out to show the utility of the method by ranking the restoration plans for a typical distribution system. This algorithm also meets the smart grid requirements in terms of an automated restoration plan for the partial/full blackout of network. PMID:27512634

  16. An ontology-driven, case-based clinical decision support model for removable partial denture design

    PubMed Central

    Chen, Qingxiao; Wu, Ji; Li, Shusen; Lyu, Peijun; Wang, Yong; Li, Miao

    2016-01-01

    We present the initial work toward developing a clinical decision support model for specific design of removable partial dentures (RPDs) in dentistry. We developed an ontological paradigm to represent knowledge of a patient’s oral conditions and denture component parts. During the case-based reasoning process, a cosine similarity algorithm was applied to calculate similarity values between input patients and standard ontology cases. A group of designs from the most similar cases were output as the final results. To evaluate this model, the output designs of RPDs for 104 randomly selected patients were compared with those selected by professionals. An area under the curve of the receiver operating characteristic (AUC-ROC) was created by plotting true-positive rates against the false-positive rate at various threshold settings. The precision at position 5 of the retrieved cases was 0.67 and at the top of the curve it was 0.96, both of which are very high. The mean average of precision (MAP) was 0.61 and the normalized discounted cumulative gain (NDCG) was 0.74 both of which confirmed the efficient performance of our model. All the metrics demonstrated the efficiency of our model. This methodology merits further research development to match clinical applications for designing RPDs. This paper is organized as follows. After the introduction and description of the basis for the paper, the evaluation and results are presented in Section 2. Section 3 provides a discussion of the methodology and results. Section 4 describes the details of the ontology, similarity algorithm, and application. PMID:27297679

  17. An ontology-driven, case-based clinical decision support model for removable partial denture design.

    PubMed

    Chen, Qingxiao; Wu, Ji; Li, Shusen; Lyu, Peijun; Wang, Yong; Li, Miao

    2016-06-14

    We present the initial work toward developing a clinical decision support model for specific design of removable partial dentures (RPDs) in dentistry. We developed an ontological paradigm to represent knowledge of a patient's oral conditions and denture component parts. During the case-based reasoning process, a cosine similarity algorithm was applied to calculate similarity values between input patients and standard ontology cases. A group of designs from the most similar cases were output as the final results. To evaluate this model, the output designs of RPDs for 104 randomly selected patients were compared with those selected by professionals. An area under the curve of the receiver operating characteristic (AUC-ROC) was created by plotting true-positive rates against the false-positive rate at various threshold settings. The precision at position 5 of the retrieved cases was 0.67 and at the top of the curve it was 0.96, both of which are very high. The mean average of precision (MAP) was 0.61 and the normalized discounted cumulative gain (NDCG) was 0.74 both of which confirmed the efficient performance of our model. All the metrics demonstrated the efficiency of our model. This methodology merits further research development to match clinical applications for designing RPDs. This paper is organized as follows. After the introduction and description of the basis for the paper, the evaluation and results are presented in Section 2. Section 3 provides a discussion of the methodology and results. Section 4 describes the details of the ontology, similarity algorithm, and application.

  18. A Computerized Clinical Support System and Psychological Laboratory.

    ERIC Educational Resources Information Center

    Cassel, Russell N.

    1978-01-01

    Advocating "holistic" medicine, this article details the benefits to be derived from using a computerized clinical support system in a psychological laboratory focusing on internal healing where the client/patient becomes a committed partner utilizing biofeedback equipment, gaming, and simulation to achieve self-understanding and self-control. (JC)

  19. Towards an intelligent decision support system for public health surveillance - a qualitative analysis of information needs.

    PubMed

    Mera, Maritza; González, Carolina; López, Diego M

    2014-01-01

    Public health information systems are often implemented considering the functionalities and requirements established by administrative staff or researchers, but sometimes ignoring the particular needs of decision makers. This paper describes a proposal to support the design of a Decision Support System for Public Health Surveillance in Colombia, by conducting a qualitative study to identify the real needs of people involved in decision making processes. Based on the study results, an intelligent computational component that supports Data Analysis Automation, Prediction of future scenarios and the identification of new Behavioral Patterns is proposed. The component will be implemented using the Case Based Reasoning methodology, which will be integrated as a new component of the Open Source DHIS2 Platform, enabling public health decision-making.

  20. Decision Support Alerts for Medication Ordering in a Computerized Provider Order Entry (CPOE) System

    PubMed Central

    Beccaro, M. A. Del; Villanueva, R.; Knudson, K. M.; Harvey, E. M.; Langle, J. M.; Paul, W.

    2010-01-01

    Objective We sought to determine the frequency and type of decision support alerts by location and ordering provider role during Computerized Provider Order Entry (CPOE) medication ordering. Using these data we adjusted the decision support tools to reduce the number of alerts. Design Retrospective analyses were performed of dose range checks (DRC), drug-drug interaction and drug-allergy alerts from our electronic medical record. During seven sampling periods (each two weeks long) between April 2006 and October 2008 all alerts in these categories were analyzed. Another audit was performed of all DRC alerts by ordering provider role from November 2008 through January 2009. Medication ordering error counts were obtained from a voluntary error reporting system. Measurement/Results Between April 2006 and October 2008 the percent of medication orders that triggered a dose range alert decreased from 23.9% to 7.4%. The relative risk (RR) for getting an alert was higher at the start of the interventions versus later (RR= 2.40, 95% CI 2.28-2.52; p< 0.0001). The percentage of medication orders that triggered alerts for drug-drug interactions also decreased from 13.5% to 4.8%. The RR for getting a drug interaction alert at the start was 1.63, 95% CI 1.60-1.66; p< 0.0001. Alerts decreased in all clinical areas without an increase in reported medication errors. Conclusion We reduced the quantity of decision support alerts in CPOE using a systematic approach without an increase in reported medication errors PMID:23616845

  1. Prioritization of information using decision support systems for seismic risk in Bucharest city

    NASA Astrophysics Data System (ADS)

    Armas, Iuliana; Gheorghe, Diana

    2014-05-01

    Nowadays, because of the ever increasing volume of information, policymakers are faced with decision making problems. Achieving an objective and suitable decision making may become a challenge. In such situations decision support systems (DSS) have been developed. DSS can assist in the decision making process, offering support on how a decision should be made, rather than what decision should be made (Simon, 1979). This in turn potentially involves a huge number of stakeholders and criteria. Regarding seismic risk, Bucharest City is highly vulnerable (Mandrescu et al., 2007). The aim of this study is to implement a spatial decision support system in order to secure a suitable shelter in case of an earthquake occurrence in the historical centre of Bucharest City. In case of a seismic risk, a shelter is essential for sheltering people who lost their homes or whose homes are in danger of collapsing while people at risk receive first aid in the post-disaster phase. For the present study, the SMCE Module for ILWIS 3.4 was used. The methodology included structuring the problem by creating a decision tree, standardizing and weighting of the criteria. The results showed that the most suitable buildings are Tania Hotel, Hanul lui Manuc, The National Bank of Romania, The Romanian Commercial Bank and The National History Museum.

  2. A human performance modelling approach to intelligent decision support systems

    NASA Technical Reports Server (NTRS)

    Mccoy, Michael S.; Boys, Randy M.

    1987-01-01

    Manned space operations require that the many automated subsystems of a space platform be controllable by a limited number of personnel. To minimize the interaction required of these operators, artificial intelligence techniques may be applied to embed a human performance model within the automated, or semi-automated, systems, thereby allowing the derivation of operator intent. A similar application has previously been proposed in the domain of fighter piloting, where the demand for pilot intent derivation is primarily a function of limited time and high workload rather than limited operators. The derivation and propagation of pilot intent is presented as it might be applied to some programs.

  3. ESPRE: a knowledge-based system to support platelet transfusion decisions.

    PubMed

    Sielaff, B H; Connelly, D P; Scott, E P

    1989-05-01

    ESPRE is a knowledge-based system which aids in the review of requests for platelet transfusions in the hospital blood bank. It is a microcomputer-based decision support system written in LISP and utilizes a hybrid frame and rule architecture. By automatically obtaining most of the required patient data directly from the hospital's main laboratory computers via a direct link, very little keyboard entry is required. Assessment of time trends computed from the data constitutes an important aspect of this system. To aid the blood bank personnel in deciding on the appropriateness of the requested transfusion, the system provides an explanatory report which includes a list of patient-specific data, a list of the conditions for which a transfusion would be appropriate for the particular patient (given the clinical condition), and the conclusions drawn by the system. In an early clinical evaluation of ESPRE, out of a random sample of 75 platelet transfusion requests, there were only three disagreements between ESPRE and blood bank personnel. PMID:2656504

  4. Energy Signal Tool for Decision Support in Building Energy Systems

    SciTech Connect

    Henze, G. P.; Pavlak, G. S.; Florita, A. R.; Dodier, R. H.; Hirsch, A. I.

    2014-12-01

    A prototype energy signal tool is demonstrated for operational whole-building and system-level energy use evaluation. The purpose of the tool is to give a summary of building energy use which allows a building operator to quickly distinguish normal and abnormal energy use. Toward that end, energy use status is displayed as a traffic light, which is a visual metaphor for energy use that is either substantially different from expected (red and yellow lights) or approximately the same as expected (green light). Which light to display for a given energy end use is determined by comparing expected to actual energy use. As expected, energy use is necessarily uncertain; we cannot choose the appropriate light with certainty. Instead, the energy signal tool chooses the light by minimizing the expected cost of displaying the wrong light. The expected energy use is represented by a probability distribution. Energy use is modeled by a low-order lumped parameter model. Uncertainty in energy use is quantified by a Monte Carlo exploration of the influence of model parameters on energy use. Distributions over model parameters are updated over time via Bayes' theorem. The simulation study was devised to assess whole-building energy signal accuracy in the presence of uncertainty and faults at the submetered level, which may lead to tradeoffs at the whole-building level that are not detectable without submetering.

  5. Key principles for a national clinical decision support knowledge sharing framework: synthesis of insights from leading subject matter experts

    PubMed Central

    Hongsermeier, Tonya; Wright, Adam; Lewis, Janet; Bell, Douglas S; Middleton, Blackford

    2013-01-01

    Objective To identify key principles for establishing a national clinical decision support (CDS) knowledge sharing framework. Materials and methods As part of an initiative by the US Office of the National Coordinator for Health IT (ONC) to establish a framework for national CDS knowledge sharing, key stakeholders were identified. Stakeholders' viewpoints were obtained through surveys and in-depth interviews, and findings and relevant insights were summarized. Based on these insights, key principles were formulated for establishing a national CDS knowledge sharing framework. Results Nineteen key stakeholders were recruited, including six executives from electronic health record system vendors, seven executives from knowledge content producers, three executives from healthcare provider organizations, and three additional experts in clinical informatics. Based on these stakeholders' insights, five key principles were identified for effectively sharing CDS knowledge nationally. These principles are (1) prioritize and support the creation and maintenance of a national CDS knowledge sharing framework; (2) facilitate the development of high-value content and tooling, preferably in an open-source manner; (3) accelerate the development or licensing of required, pragmatic standards; (4) acknowledge and address medicolegal liability concerns; and (5) establish a self-sustaining business model. Discussion Based on the principles identified, a roadmap for national CDS knowledge sharing was developed through the ONC's Advancing CDS initiative. Conclusion The study findings may serve as a useful guide for ongoing activities by the ONC and others to establish a national framework for sharing CDS knowledge and improving clinical care. PMID:22865671

  6. The Adoption of Electronic Medical Records and Decision Support Systems in Korea

    PubMed Central

    Yoo, Ki Bong; Kim, Eun Sook; Chae, Hogene

    2011-01-01

    Objectives To examine the current status of hospital information systems (HIS), analyze the effects of Electronic Medical Records (EMR) and Clinical Decision Support Systems (CDSS) have upon hospital performance, and examine how management issues change over time according to various growth stages. Methods Data taken from the 2010 survey on the HIS status and management issues for 44 tertiary hospitals and 2009 survey on hospital performance appraisal were used. A chi-square test was used to analyze the association between the EMR and CDSS characteristics. A t-test was used to analyze the effects of EMR and CDSS on hospital performance. Results Hospital size and top management support were significantly associated with the adoption of EMR. Unlike the EMR results, however, only the standardization characteristic was significantly associated with CDSS adoption. Both EMR and CDSS were associated with the improvement of hospital performance. The EMR adoption rates and outsourcing consistently increased as the growth stage increased. The CDSS, Knowledge Management System, standardization, and user training adoption rates for Stage 3 hospitals were higher than those found for Stage 2 hospitals. Conclusions Both EMR and CDSS influenced the improvement of hospital performance. As hospitals advanced to Stage 3, i.e. have more experience with information systems, they adopted EMRs and realized the importance of each management issue. PMID:22084812

  7. Fuzzy Cognitive Map scenario-based medical decision support systems for education.

    PubMed

    Georgopoulos, Voula C; Chouliara, Spyridoula; Stylios, Chrysostomos D

    2014-01-01

    Soft Computing (SC) techniques are based on exploiting human knowledge and experience and they are extremely useful to model any complex decision making procedure. Thus, they have a key role in the development of Medical Decision Support Systems (MDSS). The soft computing methodology of Fuzzy Cognitive Maps has successfully been used to represent human reasoning and to infer conclusions and decisions in a human-like way and thus, FCM-MDSSs have been developed. Such systems are able to assist in critical decision-making, support diagnosis procedures and consult medical professionals. Here a new methodology is introduced to expand the utilization of FCM-MDSS for learning and educational purposes using a scenario-based learning (SBL) approach. This is particularly important in medical education since it allows future medical professionals to safely explore extensive "what-if" scenarios in case studies and prepare for dealing with critical adverse events.

  8. Factors of accepting pain management decision support systems by nurse anesthetists

    PubMed Central

    2013-01-01

    Background Pain management is a critical but complex issue for the relief of acute pain, particularly for postoperative pain and severe pain in cancer patients. It also plays important roles in promoting quality of care. The introduction of pain management decision support systems (PM-DSS) is considered a potential solution for addressing the complex problems encountered in pain management. This study aims to investigate factors affecting acceptance of PM-DSS from a nurse anesthetist perspective. Methods A questionnaire survey was conducted to collect data from nurse anesthetists in a case hospital. A total of 113 questionnaires were distributed, and 101 complete copies were returned, indicating a valid response rate of 89.3%. Collected data were analyzed by structure equation modeling using the partial least square tool. Results The results show that perceived information quality (γ=.451, p<.001), computer self-efficacy (γ=.315, p<.01), and organizational structure (γ=.210, p<.05), both significantly impact nurse anesthetists’ perceived usefulness of PM-DSS. Information quality (γ=.267, p<.05) significantly impacts nurse anesthetists’ perceptions of PM-DSS ease of use. Furthermore, both perceived ease of use (β=.436, p<.001, R2=.487) and perceived usefulness (β=.443, p<.001, R2=.646) significantly affected nurse anesthetists’ PM-DSS acceptance (R2=.640). Thus, the critical role of information quality in the development of clinical decision support system is demonstrated. Conclusions The findings of this study enable hospital managers to understand the important considerations for nurse anesthetists in accepting PM-DSS, particularly for the issues related to the improvement of information quality, perceived usefulness and perceived ease of use of the system. In addition, the results also provide useful suggestions for designers and implementers of PM-DSS in improving system development. PMID:23360305

  9. Analysis of a multilevel diagnosis decision support system and its implications: a case study.

    PubMed

    Rodríguez-González, Alejandro; Torres-Niño, Javier; Mayer, Miguel A; Alor-Hernandez, Giner; Wilkinson, Mark D

    2012-01-01

    Medical diagnosis can be performed in an automatic way with the use of computer-based systems or algorithms. Such systems are usually called diagnostic decision support systems (DDSSs) or medical diagnosis systems (MDSs). An evaluation of the performance of a DDSS called ML-DDSS has been performed in this paper. The methodology is based on clinical case resolution performed by physicians which is then used to evaluate the behavior of ML-DDSS. This methodology allows the calculation of values for several well-known metrics such as precision, recall, accuracy, specificity, and Matthews correlation coefficient (MCC). Analysis of the behavior of ML-DDSS reveals interesting results about the behavior of the system and of the physicians who took part in the evaluation process. Global results show how the ML-DDSS system would have significant utility if used in medical practice. The MCC metric reveals an improvement of about 30% in comparison with the experts, and with respect to sensitivity the system returns better results than the experts.

  10. DESIGN OF A DECISION SUPPORT SYSTEM FOR SELECTION AND PLACEMENT OF BMPS IN URBAN WATERSHEDS

    EPA Science Inventory

    The U.S. Environmental Protection Agency (USEPA) has funded the development of a decision support system for selection and placement of best management practices (BMPs) at strategic locations in urban watersheds. The primary objective of the system is to provide stormwater manag...

  11. Funder Report on Decision Support Systems Project Dissemination Activities, Fiscal Year 1985.

    ERIC Educational Resources Information Center

    Tetlow, William L.

    Dissemination activities for the Decision Support Systems (DSS) for fiscal year (FY) 1985 are reported by the National Center for Higher Education Management Systems (NCHEMS). The main means for disseminating results of the DSS research and development project has been through computer-generated video presentations at meetings of higher education…

  12. Design of decision support system when undertaking medical-diagnostic action

    NASA Astrophysics Data System (ADS)

    Povoroznyuk, Anatoliy I.; Filatova, Anna E.; Surtel, Wojciech; Burlibay, Aron; Zhassandykyzy, Maral

    2015-12-01

    In the work the formalization of the problem of diagnostic and treatment activities (DTA) steps complex estimation for increasing of their efficiency and minimization of the risk of doctor's mistakes was completed. The decision support system during conducting of DTA based on formalizations of steps of DTA performing with theirs complex estimation was developed that allows to minimize the risks of doctor's mistakes, raise validity of decisions.

  13. Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

    USGS Publications Warehouse

    Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.

    2006-01-01

    There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

  14. Designing a decision support system for distinguishing ADHD from similar children behavioral disorders.

    PubMed

    Delavarian, Mona; Towhidkhah, Farzad; Dibajnia, Parvin; Gharibzadeh, Shahriar

    2012-06-01

    In this study, a decision support system was designed to distinguish children with ADHD from other similar children behavioral disorders such as depression, anxiety, comorbid depression and anxiety and conduct disorder based on the signs and symptoms. Accuracy of classifying with Radial basis function and multilayer neural networks were compared. Finally, the average accuracy of the networks in classification reached to 95.50% and 96.62% by multilayer and radial basis function networks respectively. Our results indicate that a decision support system, especially RBF, may be a good preliminary assistant for psychiatrists in diagnosing high risk behavioral disorders of children.

  15. A Decision Support System For Assisting With Stocking Rate Decisions During And Following Drought

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ranchers and range managers in the West are at the mercy of climatic conditions that determine the amount of annual forge available on rangeland. Typically, stocking or de-stocking decisions need to be made before the final forage production level is known. Erroneous stocking rate decisions can have...

  16. Development and application of the decision support system for municipal solid waste management in central Taiwan.

    PubMed

    Chang, Yao-Jen; Lin, Min-Der

    2013-05-01

    Municipal solid waste management (MSWM) is an important, practical and challenging environmental subject. The processes of a MSWM system include household collection, transportation, treatment, material recycling, compost and disposal. A regional program of MSWM is more complicated owing to the involvement of multi-municipality and multi-facility issues. Therefore, an effective decision support system capable of solving regional MSWM problems is necessary for decision-makers. This article employs linear programming techniques to establish a MSWM decision support system (MSWM-DSS) that is able to determine the least costs of regional MSWM strategies. The results of investigating a real-world case in central Taiwan indicate that a regional program is more economical and efficient. For the redeployment of MSW streams, the relatively least cost of operation for the MSWM system can still be achieved through the re-estimation of the MSWM-DSS. This tool and results are useful for MSWM policy-making in central Taiwan.

  17. Performance Evaluation of the Machine Learning Algorithms Used in Inference Mechanism of a Medical Decision Support System

    PubMed Central

    Bal, Mert; Amasyali, M. Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

    2014-01-01

    The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets. PMID:25295291

  18. A qualitative study of the activities performed by people involved in clinical decision support: recommended practices for success

    PubMed Central

    Wright, Adam; Ash, Joan S; Erickson, Jessica L; Wasserman, Joe; Bunce, Arwen; Stanescu, Ana; St Hilaire, Daniel; Panzenhagen, Morgan; Gebhardt, Eric; McMullen, Carmit; Middleton, Blackford; Sittig, Dean F

    2014-01-01

    Objective To describe the activities performed by people involved in clinical decision support (CDS) at leading sites. Materials and methods We conducted ethnographic observations at seven diverse sites with a history of excellence in CDS using the Rapid Assessment Process and analyzed the data using a series of card sorts, informed by Linstone's Multiple Perspectives Model. Results We identified 18 activities and grouped them into four areas. Area 1: Fostering relationships across the organization, with activities (a) training and support, (b) visibility/presence on the floor, (c) liaising between people, (d) administration and leadership, (e) project management, (f) cheerleading/buy-in/sponsorship, (g) preparing for CDS implementation. Area 2: Assembling the system with activities (a) providing technical support, (b) CDS content development, (c) purchasing products from vendors (d) knowledge management, (e) system integration. Area 3: Using CDS to achieve the organization's goals with activities (a) reporting, (b) requirements-gathering/specifications, (c) monitoring CDS, (d) linking CDS to goals, (e) managing data. Area 4: Participation in external policy and standards activities (this area consists of only a single activity). We also identified a set of recommendations associated with these 18 activities. Discussion All 18 activities we identified were performed at all sites, although the way they were organized into roles differed substantially. We consider these activities critical to the success of a CDS program. Conclusions A series of activities are performed by sites strong in CDS, and sites adopting CDS should ensure they incorporate these activities into their efforts. PMID:23999670

  19. Design of Clinical Support Systems Using Integrated Genetic Algorithm and Support Vector Machine

    NASA Astrophysics Data System (ADS)

    Chen, Yung-Fu; Huang, Yung-Fa; Jiang, Xiaoyi; Hsu, Yuan-Nian; Lin, Hsuan-Hung

    Clinical decision support system (CDSS) provides knowledge and specific information for clinicians to enhance diagnostic efficiency and improving healthcare quality. An appropriate CDSS can highly elevate patient safety, improve healthcare quality, and increase cost-effectiveness. Support vector machine (SVM) is believed to be superior to traditional statistical and neural network classifiers. However, it is critical to determine suitable combination of SVM parameters regarding classification performance. Genetic algorithm (GA) can find optimal solution within an acceptable time, and is faster than greedy algorithm with exhaustive searching strategy. By taking the advantage of GA in quickly selecting the salient features and adjusting SVM parameters, a method using integrated GA and SVM (IGS), which is different from the traditional method with GA used for feature selection and SVM for classification, was used to design CDSSs for prediction of successful ventilation weaning, diagnosis of patients with severe obstructive sleep apnea, and discrimination of different cell types form Pap smear. The results show that IGS is better than methods using SVM alone or linear discriminator.

  20. Real-time decision support systems: the famine early warning system network

    USGS Publications Warehouse

    Funk, Christopher C.; Verdin, James P.

    2010-01-01

    A multi-institutional partnership, the US Agency for International Development’s Famine Early Warning System Network (FEWS NET) provides routine monitoring of climatic, agricultural, market, and socioeconomic conditions in over 20 countries. FEWS NET supports and informs disaster relief decisions that impact millions of people and involve billions of dollars. In this chapter, we focus on some of FEWS NET’s hydrologic monitoring tools, with a specific emphasis on combining “low frequency” and “high frequency” assessment tools. Low frequency assessment tools, tied to water and food balance estimates, enable us to evaluate and map long-term tendencies in food security. High frequency assessments are supported by agrohydrologic models driven by satellite rainfall estimates, such as the Water Requirement Satisfaction Index (WRSI). Focusing on eastern Africa, we suggest that both these high and low frequency approaches are necessary to capture the interaction of slow variations in vulnerability and the relatively rapid onset of climatic shocks.

  1. Design of a decision support system, trained on GPU, for assisting melanoma diagnosis in dermatoscopy images

    NASA Astrophysics Data System (ADS)

    Glotsos, Dimitris; Kostopoulos, Spiros; Lalissidou, Stella; Sidiropoulos, Konstantinos; Asvestas, Pantelis; Konstandinou, Christos; Xenogiannopoulos, George; Konstantina Nikolatou, Eirini; Perakis, Konstantinos; Bouras, Thanassis; Cavouras, Dionisis

    2015-09-01

    The purpose of this study was to design a decision support system for assisting the diagnosis of melanoma in dermatoscopy images. Clinical material comprised images of 44 dysplastic (clark's nevi) and 44 malignant melanoma lesions, obtained from the dermatology database Dermnet. Initially, images were processed for hair removal and background correction using the Dull Razor algorithm. Processed images were segmented to isolate moles from surrounding background, using a combination of level sets and an automated thresholding approach. Morphological (area, size, shape) and textural features (first and second order) were calculated from each one of the segmented moles. Extracted features were fed to a pattern recognition system assembled with the Probabilistic Neural Network Classifier, which was trained to distinguish between benign and malignant cases, using the exhaustive search and the leave one out method. The system was designed on the GPU card (GeForce 580GTX) using CUDA programming framework and C++ programming language. Results showed that the designed system discriminated benign from malignant moles with 88.6% accuracy employing morphological and textural features. The proposed system could be used for analysing moles depicted on smart phone images after appropriate training with smartphone images cases. This could assist towards early detection of melanoma cases, if suspicious moles were to be captured on smartphone by patients and be transferred to the physician together with an assessment of the mole's nature.

  2. Strengthening Resiliency in Coastal Watersheds: An Ecosystem Services and Ecological Integrity Decision Support System

    EPA Science Inventory

    This product provides an integrated assessment framework linked to a decision support system (DSS) that incorporates the ecological integrity (EI) principles and goals described in detail in the US EPA’s Office of Water’s Healthy Watersheds Program (HWP), with Ecosyst...

  3. A Data Analytical Framework for Improving Real-Time, Decision Support Systems in Healthcare

    ERIC Educational Resources Information Center

    Yahav, Inbal

    2010-01-01

    In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to…

  4. OASIS: A GEOGRAPHICAL DECISION SUPPORT SYSTEM FOR GROUND-WATER CONTAMINANT MODELING

    EPA Science Inventory

    Three new software technologies were applied to develop an efficient and easy to use decision support system for ground-water contaminant modeling. Graphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces...

  5. Computerizing the Budget Office: An On-Line Decision Support System.

    ERIC Educational Resources Information Center

    Rosenberg, Glenn R.; Peterson, William R.

    The implementation process and resource requirements of the University of Connecticut Budget Office's online decision support system are described. Successes and failures of shifting to a fully interactive budget review and development process are also reviewed. Special attention is given to the personnel problems and analytical challenges…

  6. Decision Support Systems: An Institutional Research Perspective. AIR Forum 1982 Paper.

    ERIC Educational Resources Information Center

    Sheehan, Bernard S.

    Ideas that have been developed in the decision support systems (DSS) literature that seem particularly relevant to institutional research, planning, and analysis (IRPA) are reviewed. In addition, a survey of practitioners in Canadian universities that provides new information on the rapidly changing current state of information technology,…

  7. The Contribution of Decision Support Systems (DSS) to Consolidation of Educational Policies

    ERIC Educational Resources Information Center

    Klein, Joseph; Wasserstein, Mark

    2005-01-01

    Educational policies proposed with and without the aid of Decision Support Systems (DSS) were compared. 120 teachers responded to a questionnaire describing two hypothetical incidents and presenting a series of options with respect to homogeneous and heterogeneous grouping of pupils according to achievement level. After selection of preferred…

  8. WAR DSS: A DECISION SUPPORT SYSTEM FOR ENVIRONMENTALLY CONSCIOUS CHEMICAL PROCESS DESIGN

    EPA Science Inventory

    The second generation of the Waste Reduction (WAR) Algorithm is constructed as a decision support system (DSS) in the design of chemical manufacturing facilities. The WAR DSS is a software tool that can help reduce the potential environmental impacts (PEIs) of industrial chemical...

  9. Future perspectives toward the early definition of a multivariate decision-support scheme employed in clinical decision making for senior citizens.

    PubMed

    Frantzidis, Christos A; Gilou, Sotiria; Billis, Antonis; Karagianni, Maria; Bratsas, Charalampos D; Bamidis, Panagiotis

    2016-03-01

    Recent neuroscientific studies focused on the identification of pathological neurophysiological patterns (emotions, geriatric depression, memory impairment and sleep disturbances) through computerised clinical decision-support systems. Almost all these research attempts employed either resting-state condition (e.g. eyes-closed) or event-related potentials extracted during a cognitive task known to be affected by the disease under consideration. This Letter reviews existing data mining techniques and aims to enhance their robustness by proposing a holistic decision framework dealing with comorbidities and early symptoms' identification, while it could be applied in realistic occasions. Multivariate features are elicited and fused in order to be compared with average activities characteristic of each neuropathology group. A proposed model of the specific cognitive function which may be based on previous findings (a priori information) and/or validated by current experimental data should be then formed. So, the proposed scheme facilitates the early identification and prevention of neurodegenerative phenomena. Neurophysiological semantic annotation is hypothesised to enhance the importance of the proposed framework in facilitating the personalised healthcare of the information society and medical informatics research community. PMID:27222732

  10. Future perspectives toward the early definition of a multivariate decision-support scheme employed in clinical decision making for senior citizens.

    PubMed

    Frantzidis, Christos A; Gilou, Sotiria; Billis, Antonis; Karagianni, Maria; Bratsas, Charalampos D; Bamidis, Panagiotis

    2016-03-01

    Recent neuroscientific studies focused on the identification of pathological neurophysiological patterns (emotions, geriatric depression, memory impairment and sleep disturbances) through computerised clinical decision-support systems. Almost all these research attempts employed either resting-state condition (e.g. eyes-closed) or event-related potentials extracted during a cognitive task known to be affected by the disease under consideration. This Letter reviews existing data mining techniques and aims to enhance their robustness by proposing a holistic decision framework dealing with comorbidities and early symptoms' identification, while it could be applied in realistic occasions. Multivariate features are elicited and fused in order to be compared with average activities characteristic of each neuropathology group. A proposed model of the specific cognitive function which may be based on previous findings (a priori information) and/or validated by current experimental data should be then formed. So, the proposed scheme facilitates the early identification and prevention of neurodegenerative phenomena. Neurophysiological semantic annotation is hypothesised to enhance the importance of the proposed framework in facilitating the personalised healthcare of the information society and medical informatics research community.

  11. Urbanization suitability maps: a dynamic spatial decision support system for sustainable land use

    NASA Astrophysics Data System (ADS)

    Cerreta, M.; De Toro, P.

    2012-11-01

    Recent developments in land consumption assessment identify the need to implement integrated evaluation approaches, with particular attention to the development of multidimensional tools for guiding and managing sustainable land use. Land use policy decisions are implemented mostly through spatial planning and its related zoning. This involves trade-offs between many sectorial interests and conflicting challenges seeking win-win solutions. In order to identify a decision-making process for land use allocation, this paper proposes a methodological approach for developing a Dynamic Spatial Decision Support System (DSDSS), denominated Integrated Spatial Assessment (ISA), supported by Geographical Information Systems (GIS) combined with the Analytic Hierarchy Process (AHP). Through empirical investigation in an operative case study, an integrated evaluation approach implemented in a DSDSS helps produce "urbanization suitability maps" in which spatial analysis combined with multi-criteria evaluation methods proved to be useful for both facing the main issues relating to land consumption as well as minimizing environmental impacts of spatial planning.

  12. IONIO Project: Computer-mediated Decision Support System and Communication in Ocean Science

    NASA Astrophysics Data System (ADS)

    Oddo, Paolo; Acierno, Arianna; Cuna, Daniela; Federico, Ivan; Galati, Maria Barbara; Awad, Esam; Korres, Gerasimos; Lecci, Rita; Manzella, Giuseppe M. R.; Merico, Walter; Perivoliotis, Leonidas; Pinardi, Nadia; Shchekinova, Elena; Mannarini, Gianandrea; Vamvakaki, Chrysa; Pecci, Leda; Reseghetti, Franco

    2013-04-01

    A decision Support System is composed by four main steps. The first one is the definition of the problem, the issue to be covered, decisions to be taken. Different causes can provoke different problems, for each of the causes or its effects it is necessary to define a list of information and/or data that are required in order to take the better decision. The second step is the determination of sources from where information/data needed for decision-making can be obtained and who has that information. Furthermore it must be possible to evaluate the quality of the sources to see which of them can provide the best information, and identify the mode and format in which the information is presented. The third step is relying on the processing of knowledge, i.e. if the information/data are fitting for purposes. It has to be decided which parts of the information/data need to be used, what additional data or information is necessary to access, how can information be best presented to be able to understand the situation and take decisions. Finally, the decision making process is an interactive and inclusive process involving all concerned parties, whose different views must be taken into consideration. A knowledge based discussion forum is necessary to reach a consensus. A decision making process need to be examined closely and refined, and modified to meet differing needs over time. The report is presenting legal framework and knowledge base for a scientific based decision support system and a brief exploration of some of the skills that enhances the quality of decisions taken.

  13. The Contribution of a Decision Support System to Complex Educational Decisions

    ERIC Educational Resources Information Center

    Klein, Joseph

    2005-01-01

    This study examined the effect of complexity of problems on the degree of disparity between intuitive (PDM) and computer-assisted (DSS) decision-making. 840 teachers chose intuitive solutions for educational dilemmas, and recorded the relative importance of the guiding criteria. Utilizing this information, DSS calculated preferred solutions. Of…

  14. A Decision Support System for Evaluatingquality Safety Risk Contaminated By Water Pollution in Aquaculture Pond

    NASA Astrophysics Data System (ADS)

    Tian, Dong; Li, Nan; Huang, Honghui; Fu, Zetian; Zhang, Xiaoshuan

    Water pollution is becoming the major factor damaging the sustainable development of aquaculture and the quality security of aquatic product in China. This paper introduces a decision support system for evaluating and managing quality risk contaminated by water pollution. The architecture, main components and their functions, especially a series of risk evaluation methods and models are described. At present, the system is in pilot in the city of Beijing in China. The stage achievements in developing the system are summarized.

  15. The countryside information system: A strategic-level decision support system.

    PubMed

    Howard, D C; Bunce, R G

    1996-01-01

    The Institute of Terrestrial Ecology (ITE) has monitored ecological change in Great Britain (GB) since 1978. The task has been undertaken using a stratified sampling scheme working with a 1 km square as the sample unit. In more recent years, scientific researchers at ITE have been working closely with the policy-makers of the United Kingdom Department of the Environment. The presentation of information to policy advisors and planners was a component within a large project investigating the ecological consequences of land-use change. A simple PC-based decision support system was developed during the project and subsequently has been expanded to produce a marketable product. The system, called the Countryside Information System (CIS), presents and links information at national, regional and thematic levels along with qualifying data describing accuracy and appropriateness of use (i.e., metadata). An integral part of the CIS is the ITE Land Classification, which divides GB into 32 environmental land classes; all 250 000 squares have been classified. The classification allows sampled data to be presented and, as the co-ordinate system is widely used in GB, it allows census datasets to be linked and compared. CIS has been described as a Geographical Information System, but the classification, data held within the system, and the use of metadata to assist in interpretation of results make the system much more decision-support oriented. Indeed, government departments have been involved in directing the development and are now starting to use the system to answer parliamentary questions and formulate, assess and monitor environmental policy. The CIS is an open system, running on a standard PC in Microsoft Windows. Tools for loading and editing new datasets (both sample and census) are incorporated in the suite of programs. The Windows environment and users comments during development have produced a system with an intuitive feel, removing some of the overhead of acquiring

  16. CO2-PENS: A CO2 Sequestration Systems Model Supporting Risk-Based Decisions

    NASA Astrophysics Data System (ADS)

    Stauffer, P. H.; Viswanathan, H. S.; Guthrie, G. D.; Pawar, R. J.; Kaszuba, J. P.; Carey, J. W.; Lichtner, P. C.; Ziock, H. J.; Dubey, M. K.; Olsen, S. C.; Chipera, S. J.; Fessenden-Rahn, J. E.

    2005-12-01

    The Zero Emissions Research and Technology (ZERT) project at the Los Alamos National Laboratory is studying the injection of CO2 into geologic repositories. We are formulating the problem as science based decision framework that can address issues of risk, cost, and technical requirements at all stages of the sequestration process. The framework is implemented in a system model that is capable of performing stochastic simulations to address uncertainty in different geologic sequestration scenarios, including injection into poorly characterized brine aquifers. Processes level laboratory experiments, field experiments, modeling, economic data, and risk theory are used to support the system level model that will be the basis for decision making. The current system model, CO2-PENS, is already proving to be useful in showing complex interactions between the different components of the framework. The system model also provides a consistent platform to document decisions made during the site selection, implementation, and closure periods.

  17. Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

    NASA Astrophysics Data System (ADS)

    Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

    2014-05-01

    Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in

  18. Designing a Decision Support System (DSS) for Academic Library Managers Using Preprogrammed Application Software on a Microcomputer.

    ERIC Educational Resources Information Center

    McDonald, Joseph

    1986-01-01

    Focusing on management decisions in academic libraries, this article compares management information systems (MIS) with decision support systems (DSS) and discusses the decision-making process, information needs of library managers, sources of data, reasons for choosing microcomputer, preprogrammed application software, prototyping a system, and…

  19. Future of electronic health records: implications for decision support.

    PubMed

    Rothman, Brian; Leonard, Joan C; Vigoda, Michael M

    2012-01-01

    The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data

  20. Physician and consumer acceptance of the traditional chinese medicine clinical practice support system (TCMCPSS).

    PubMed

    Lai, Tsai-Ya; Tseng, Yu-Ting; Lee, Chin-Ni

    2014-01-01

    Although ICT-enabled clinical practices have been widely accepted by the Western medical society, informatics applications for traditional Chinese medicine (TCM) are under developed. An integrated traditional Chinese medicine clinical practice support system (TCMCPSS) has been developed to enhance data integration automation and treatment planning decision support of clinical practice of TCM. The acceptance of TCMCPSS had been assessed by 26 TCM physicians based on information clarity, clinical relevancy, and theoretical relevancy through a survey questionnaire using the 5-points Likert Scale. The average acceptance rate was 3.76. One hundred and fifty-four participants were recruited for the TCMCPSS feasibility study and reported the acceptance rate of 90%. The results indicated that while consumers were ready to embrace TCM practice assisted by informatics technologies, TCM physicians concerned more about the usefulness of the system and preserved caution to adopt TCMCPSS.

  1. Using Clinical Decision Support and Dashboard Technology to Improve Heart Team Efficiency and Accuracy in a Transcatheter Aortic Valve Implantation (TAVI) Program.

    PubMed

    Clarke, Sarah; Wilson, Marisa L; Terhaar, Mary

    2016-01-01

    Heart Team meetings are becoming the model of care for patients undergoing transcatheter aortic valve implantations (TAVI) worldwide. While Heart Teams have potential to improve the quality of patient care, the volume of patient data processed during the meeting is large, variable, and comes from different sources. Thus, consolidation is difficult. Also, meetings impose substantial time constraints on the members and financial pressure on the institution. We describe a clinical decision support system (CDSS) designed to assist the experts in treatment selection decisions in the Heart Team. Development of the algorithms and visualization strategy required a multifaceted approach and end-user involvement. An innovative feature is its ability to utilize algorithms to consolidate data and provide clinically useful information to inform the treatment decision. The data are integrated using algorithms and rule-based alert systems to improve efficiency, accuracy, and usability. Future research should focus on determining if this CDSS improves patient selection and patient outcomes. PMID:27332170

  2. An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

    PubMed

    Siddiqui, Muhammad Faisal; Reza, Ahmed Wasif; Kanesan, Jeevan

    2015-01-01

    A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the

  3. Development of a Fuzzy Decision Support System to Determine the Severity of Obstructive Pulmonary in Chemical Injured Victims

    PubMed Central

    Samad-Soltani, Taha; Ghanei, Mostafa; Langarizadeh, Mostafa

    2015-01-01

    Background: Chronic Obstructive Pulmonary Disease (COPD) is the most common known complication of exposure to mustard gas. Thus, all clinical guidelines have provided some recommendation for diagnosis, clinical management and treatment of this disease. Decision support systems are used to increase the acceptance of clinical guidelines. The purpose of this research is to develop a CDSS to determine the severity of COPD in chemical injured victims. Objectives: Development of a decision support system to determine the severity of COPD. Patients and Methods: First, the variables influencing to determining the severity of the disease was classified through studying the clinical guidelines. Then, the fuzzy model was implemented. To testing the system, the data from 50 patients were used. Results: the overall accuracy in determining the severity of the injury is equal to 92%, these indicators reflect the proper functioning of the system to assist the physician regarding the diagnosis of chronic obstructive pulmonary disease and determining its severity. Conclusions: The CDSS has efficient results and satisfactory performance. Although, the medical expert systems cannot be expected to provide 100 percent correct responses, however, they can be useful in the areas of patient management, diagnosis and treatment planning. PMID:26236078

  4. An Integrated Decision Support System for Water Quality Management of Songhua River Basin

    NASA Astrophysics Data System (ADS)

    Zhang, Haiping; Yin, Qiuxiao; Chen, Ling

    2010-11-01

    In the Songhua River Basin of China, many water resource and water environment conflicts interact. A Decision Support System (DSS) for the water quality management has been established for the Basin. The System is featured by the incorporation of a numerical water quality model system into a conventional water quality management system which usually consists of geographic information system (GIS), WebGIS technology, database system and network technology. The model system is built based on DHI MIKE software comprising of a basin rainfall-runoff module, a basin pollution load evaluation module, a river hydrodynamic module and a river water quality module. The DSS provides a friendly graphical user interface that enables the rapid and transparent calculation of various water quality management scenarios, and also enables the convenient access and interpretation of the modeling results to assist the decision-making.

  5. Fuzzy Based Decision Support System for Condition Assessment and Rating of Bridges

    NASA Astrophysics Data System (ADS)

    Srinivas, Voggu; Sasmal, Saptarshi; Karusala, Ramanjaneyulu

    2016-09-01

    In this work, a knowledge based decision support system has been developed to efficiently handle the issues such as distress diagnosis, assessment of damages and condition rating of existing bridges towards developing an exclusive and robust Bridge Management System (BMS) for sustainable bridges. The Knowledge Based Expert System (KBES) diagnoses the distresses and finds the cause of distress in the bridge by processing the data which are heuristic and combined with site inspection results, laboratory test results etc. The coupling of symbolic and numeric type of data has been successfully implemented in the expert system to strengthen its decision making process. Finally, the condition rating of the bridge is carried out using the assessment results obtained from the KBES and the information received from the bridge inspector. A systematic procedure has been developed using fuzzy mathematics for condition rating of bridges by combining the fuzzy weighted average and resolution identity technique. The proposed methodologies and the decision support system will facilitate in developing a robust and exclusive BMS for a network of bridges across the country and allow the bridge engineers and decision makers to carry out maintenance of bridges in a rational and systematic way.

  6. Fuzzy Based Decision Support System for Condition Assessment and Rating of Bridges

    NASA Astrophysics Data System (ADS)

    Srinivas, Voggu; Sasmal, Saptarshi; Karusala, Ramanjaneyulu

    2016-06-01

    In this work, a knowledge based decision support system has been developed to efficiently handle the issues such as distress diagnosis, assessment of damages and condition rating of existing bridges towards developing an exclusive and robust Bridge Management System (BMS) for sustainable bridges. The Knowledge Based Expert System (KBES) diagnoses the distresses and finds the cause of distress in the bridge by processing the data which are heuristic and combined with site inspection results, laboratory test results etc. The coupling of symbolic and numeric type of data has been successfully implemented in the expert system to strengthen its decision making process. Finally, the condition rating of the bridge is carried out using the assessment results obtained from the KBES and the information received from the bridge inspector. A systematic procedure has been developed using fuzzy mathematics for condition rating of bridges by combining the fuzzy weighted average and resolution identity technique. The proposed methodologies and the decision support system will facilitate in developing a robust and exclusive BMS for a network of bridges across the country and allow the bridge engineers and decision makers to carry out maintenance of bridges in a rational and systematic way.

  7. Design document for landfill capping Prototype Decision Support System. Draft 1.0

    SciTech Connect

    Stone, J.J.; Paige, G.; Hakonson, T.E.; Lane, L.J.

    1994-01-01

    The overall objective of the Prototype Decision Support System for shallow land burial project is to ``Develop a Decision Support System tool which incorporates simulation modeling and multi-objective decision theory for the purpose of designing and evaluating alternative trench cap designs for mixed waste landfill covers. The goal is to improve the quality of technical information used by the risk manager to select landfill cover designs while taking into account technological, economical, and regulatory factors.`` The complexity of the technical and non-technical information, and how the information varies in importance across sites, points to the need for decision analysis tools that provide a common basis for integrating, synthesizing, and valuing the decision input. Because the cost of remediating thousands of contaminated DOE sites is projected to be in the 10`s--100`s of billions of dollars, methods will be needed to establish cleanup priorities and to help in the selection and evaluation of cost effective remediation alternatives. Even at this early stage in DOE`s cleanup program, it is certain that capping technologies will be heavily relied upon to remediate the 3000+ landfills on DOE property. Capping is favored in remediating most DOE landfills because, based on preliminary baseline risk assessments, human and ecological risks are considered to be low at most of these sites and the regulatory requirements for final closure of old landfills can be met using a well designed cap to isolate the buried waste. This report describes a program plan to design, develop, and test a decision support system (DSS) for assisting the DOE risk manager in evaluating capping alternatives for radioactive and hazardous waste landfills. The DOE DSS will incorporate methods for calculating, integrating and valuing technical, regulatory, and economic criteria.

  8. A Decision Support System for Climate Change Adaptation in Rainfed Sectors of Agriculture for Central Europe

    NASA Astrophysics Data System (ADS)

    Mátyás, Csaba; Berki, Imre; Drüszler, Áron; Eredics, Attila; Gálos, Borbála; Illés, Gábor; Móricz, Norbert; Rasztovits, Ervin; Czimber, Kornél

    2013-04-01

    • Background and aims: Rainfed sectors of agriculture such as nature-close forestry, non-irrigated agriculture and animal husbandry on nature-close pastures are threatened by projected climate change especially in low-elevation regions in Southeast Europe, where precipitation is the limiting factor of production and ecosystem stability. Therefore the importance of complex, long term management planning and of land use optimization is increasing. The aim of the Decision Support System under development is to raise awareness and initiate preparation for frequency increase of extreme events, disasters and economic losses in the mentioned sectors. • Services provided: The Decision Support System provides GIS-supported information about the most important regional and local risks and mitigation options regarding climate change impacts, projected for reference periods until 2100 (e.g. land cover/use and expectable changes, potential production, water and carbon cycle, biodiversity and other ecosystem services, potential pests and diseases, tolerance limits etc.). The projections are referring first of all on biological production (natural produce), but the System includes also social and economic consequences. • Methods: In the raster based system, the latest image processing technology is used. We apply fuzzy membership functions, Support Vector Machine and Maximum Likelihood classifier. The System is developed in the first step for a reference area in SW Hungary (Zala county). • Novelty: The coherent, fine-scale regional system integrates the basic information about present and projected climates, extremes, hydrology and soil conditions and expected production potential for three sectors of agriculture as options for land use and conservation. • Funding: The development of the Decision Support System "Agrárklíma" is supported by TÁMOP-4.2.2.A-11/1/KONV and 4.2.2.B-10/1-2010-0018 "Talentum" joint EU-national research projects. Keywords: climate change

  9. Co-Design of a Computer-Assisted Medical Decision Support System to Manage Antibiotic Prescription in an ICU Ward.

    PubMed

    Gil, Miguel; Pinto, Pedro; Simões, Alexandra S; Póvoa, Pedro; Da Silva, Miguel Mira; Lapão, Luís Velez

    2016-01-01

    About 37 thousand people die per year in Europe due to infections by resistant bacteria. Fighting antimicrobial resistances (AR) is a top priority to save lives and reduce costs. AR is triggered mostly by uncritical antibiotic prescription. This paper presents HAITool, a decision-making information system to support antibiotic prescription. The system was co-developed together with health professionals using Design Science Research Methodology, empowered with innovative data visualization techniques to improve AR management. HAITool includes integrated visualizations of patient, microbiology, and pharmacy data, facilitating clinical decision support, antibiotic prescriptions quality and antibiotic-resistant bacteria monitoring. It also includes an alert module that monitors conformance of antibiotic prescriptions with norms and guidelines. HAITool is evaluated using both the Österle principles and interviews with physicians and infection control team from three participant hospitals. PMID:27577433

  10. Structural and functional design of WWTP operation decision support system with a case study.

    PubMed

    Xu, J; Shi, H C; Ke, X Y

    2006-01-01

    This paper developes the WWTP operation decision support system (ODSS) to simulate the dynamic behavior of the WWTP treatment process based on ASMs (activated sludge models) and WWTP experiential knowledge. The novel structure and functions of ODSS can offer more flexible and general instructions to the WWTP operations. The three independent sub-systems, namely expert system, simulation system and training system, can cooperate to achieve many more functions such as operation alert, fault diagnosis, process simulation and so forth. The expert system based on the dynamic simulation, an essential part of WWTP ODSS, has been proved to be feasible and effective by the implementation at Fang Zhuang WWTP. Our results indicated that the WWTP ODSS has significant potential for improving plant performance and reducing treatment costs by assisting the operators at the decision-making level.

  11. Collaborative modelling and integrated decision support system analysis of a developed terminal lake basin

    USGS Publications Warehouse

    Niswonger, Richard; Allander, Kip K.; Jeton, Anne E.

    2014-01-01

    A terminal lake basin in west-central Nevada, Walker Lake, has undergone drastic change over the past 90 yrs due to upstream water use for agriculture. Decreased inflows to the lake have resulted in 100 km2 decrease in lake surface area and a total loss of fisheries due to salinization. The ecologic health of Walker Lake is of great concern as the lake is a stopover point on the Pacific route for migratory birds from within and outside the United States. Stakeholders, water institutions, and scientists have engaged in collaborative modeling and the development of a decision support system that is being used to develop and analyze management change options to restore the lake. Here we use an integrated management and hydrologic model that relies on state-of-the-art simulation capabilities to evaluate the benefits of using integrated hydrologic models as components of a decision support system. Nonlinear feedbacks among climate, surface-water and groundwater exchanges, and water use present challenges for simulating realistic outcomes associated with management change. Integrated management and hydrologic modeling provides a means of simulating benefits associated with management change in the Walker River basin where drastic changes in the hydrologic landscape have taken place over the last century. Through the collaborative modeling process, stakeholder support is increasing and possibly leading to management change options that result in reductions in Walker Lake salt concentrations, as simulated by the decision support system.

  12. Collaborative modelling and integrated decision support system analysis of a developed terminal lake basin

    NASA Astrophysics Data System (ADS)

    Niswonger, Richard G.; Allander, Kip K.; Jeton, Anne E.

    2014-09-01

    A terminal lake basin in west-central Nevada, Walker Lake, has undergone drastic change over the past 90 yrs due to upstream water use for agriculture. Decreased inflows to the lake have resulted in 100 km2 decrease in lake surface area and a total loss of fisheries due to salinization. The ecologic health of Walker Lake is of great concern as the lake is a stopover point on the Pacific route for migratory birds from within and outside the United States. Stakeholders, water institutions, and scientists have engaged in collaborative modeling and the development of a decision support system that is being used to develop and analyze management change options to restore the lake. Here we use an integrated management and hydrologic model that relies on state-of-the-art simulation capabilities to evaluate the benefits of using integrated hydrologic models as components of a decision support system. Nonlinear feedbacks among climate, surface-water and groundwater exchanges, and water use present challenges for simulating realistic outcomes associated with management change. Integrated management and hydrologic modeling provides a means of simulating benefits associated with management change in the Walker River basin where drastic changes in the hydrologic landscape have taken place over the last century. Through the collaborative modeling process, stakeholder support is increasing and possibly leading to management change options that result in reductions in Walker Lake salt concentrations, as simulated by the decision support system.

  13. Supporting clinical decision making during deep brain stimulation surgery by means of a stochastic dynamical model

    NASA Astrophysics Data System (ADS)

    Karamintziou, Sofia D.; Tsirogiannis, George L.; Stathis, Pantelis G.; Tagaris, George A.; Boviatsis, Efstathios J.; Sakas, Damianos E.; Nikita, Konstantina S.

    2014-10-01

    Objective. During deep brain stimulation (DBS) surgery for the treatment of advanced Parkinson's disease (PD), microelectrode recording (MER) in conjunction with functional stimulation techniques are commonly applied for accurate electrode implantation. However, the development of automatic methods for clinical decision making has to date been characterized by the absence of a robust single-biomarker approach. Moreover, it has only been restricted to the framework of MER without encompassing intraoperative macrostimulation. Here, we propose an integrated series of novel single-biomarker approaches applicable to the entire electrophysiological procedure by means of a stochastic dynamical model. Approach. The methods are applied to MER data pertinent to ten DBS procedures. Considering the presence of measurement noise, we initially employ a multivariate phase synchronization index for automatic delineation of the functional boundaries of the subthalamic nucleus (STN) and determination of the acceptable MER trajectories. By introducing the index into a nonlinear stochastic model, appropriately fitted to pre-selected MERs, we simulate the neuronal response to periodic stimuli (130 Hz), and examine the Lyapunov exponent as an indirect indicator of the clinical effectiveness yielded by stimulation at the corresponding sites. Main results. Compared with the gold-standard dataset of annotations made intraoperatively by clinical experts, the STN detection methodology demonstrates a false negative rate of 4.8% and a false positive rate of 0%, across all trajectories. Site eligibility for implantation of the DBS electrode, as implicitly determined through the Lyapunov exponent of the proposed stochastic model, displays a sensitivity of 71.43%. Significance. The suggested comprehensive method exhibits remarkable performance in automatically determining both the acceptable MER trajectories and the optimal stimulation sites, thereby having the potential to accelerate precise

  14. A National Crop Progress Monitoring and Decision Support System Based on NASA Earth Science Results

    NASA Astrophysics Data System (ADS)

    di, L.; Yang, Z.

    2009-12-01

    Timely and accurate information on weekly crop progress and development is essential to a dynamic agricultural industry in the U. S. and the world. By law, the National Agricultural Statistics Service (NASS) of the U. S. Department of Agriculture’s (USDA) is responsible for monitoring and assessing U.S. agricultural production. Currently NASS compiles and issues weekly state and national crop progress and development reports based on reports from knowledgeable state and county agricultural officials and farmers. Such survey-based reports are subjectively estimated for an entire county, lack spatial coverage, and are labor intensive. There has been limited use of remote sensing data to assess crop conditions. NASS produces weekly 1-km resolution un-calibrated AVHRR-based NDVI static images to represent national vegetation conditions but there is no quantitative crop progress information. This presentation discusses the early result for developing a National Crop Progress Monitoring and Decision Support System. The system will overcome the shortcomings of the existing systems by integrating NASA satellite and model-based land surface and weather products, NASS’ wealth of internal crop progress and condition data and Cropland Data Layers (CDL), and the Farm Service Agency’s (FSA) Common Land Units (CLU). The system, using service-oriented architecture and web service technologies, will automatically produce and disseminate quantitative national crop progress maps and associated decision support data at 250-m resolution, as well as summary reports to support NASS and worldwide users in their decision-making. It will provide overall and specific crop progress for individual crops from the state level down to CLU field level to meet different users’ needs on all known croplands. This will greatly enhance the effectiveness and accuracy of the NASS aggregated crop condition data and charts of and provides objective and scientific evidence and guidance for the

  15. Including long-term biological index performance in a multi-criteria Decision Support System

    USGS Publications Warehouse

    Waddle, T.; Bowen, Z.; Bovee, K.D.

    1999-01-01

    A Decision Support System (DSS) was developed for the reservoirs operated by the U.S. Bureau of Reclamation that incorporates biological resources in a palette of decision variables. A scoring technique was developed for the DSS to help to evaluate the long-term effects of proposed reservoir system operations on those variables. The biological component of the DSS was developed to help Bureau of Reclamation reservoir operators evaluate the effects of different scenarios of reservoir operations on a variety of water-related biological resources. In this DSS, Reclamation's Reservoir Operations Modeling System (ROMS) is linked to modules evaluating power production, flood control benefits, irrigation water deliveries, municipal and industrial water supplies, habitat for endemic fish communities, tailwater fisheries, nesting habitat for shorebirds, reservoir recreation, reservoir fisheries, and regeneration of riparian cottonwood forests. Operation scenarios generated in ROMS are scored for each decision variable by comparison to a target range of a decision variable for a reference location and time period. The score for a variable is calculated based on the ratio between the percent of time that target conditions are met under alternative operating conditions and under the reference condition, respectively. A scoring technique was developed that recognizes that under either natural or highly managed conditions the reference target is not met at all times. Higher scores are achieved for environmental decision variables by operations scenarios that approach natural seasonal and annual variability in habitat availability.

  16. A decision support system for drinking water production integrating health risks assessment.

    PubMed

    Delpla, Ianis; Monteith, Donald T; Freeman, Chris; Haftka, Joris; Hermens, Joop; Jones, Timothy G; Baurès, Estelle; Jung, Aude-Valérie; Thomas, Olivier

    2014-07-01

    The issue of drinking water quality compliance in small and medium scale water services is of paramount importance in relation to the 98/83/CE European Drinking Water Directive (DWD). Additionally, concerns are being expressed over the implementation of the DWD with respect to possible impacts on water quality from forecast changes in European climate with global warming and further anticipated reductions in north European acid emissions. Consequently, we have developed a decision support system (DSS) named ARTEM-WQ (AwaReness Tool for the Evaluation and Mitigation of drinking Water Quality issues resulting from environmental changes) to support decision making by small and medium plant operators and other water stakeholders. ARTEM-WQ is based on a sequential risk analysis approach that includes consideration of catchment characteristics, climatic conditions and treatment operations. It provides a holistic evaluation of the water system, while also assessing human health risks of organic contaminants potentially present in treated waters (steroids, pharmaceuticals, pesticides, bisphenol-a, polychlorobiphenyls, polycyclic aromatic hydrocarbons, petrochemical hydrocarbons and disinfection by-products; n = 109). Moreover, the system provides recommendations for improvement while supporting decision making in its widest context. The tool has been tested on various European catchments and shows a promising potential to inform water managers of risks and appropriate mitigative actions. Further improvements should include toxicological knowledge advancement, environmental background pollutant concentrations and the assessment of the impact of distribution systems on water quality variation. PMID:25046634

  17. A decision support system for drinking water production integrating health risks assessment.

    PubMed

    Delpla, Ianis; Monteith, Donald T; Freeman, Chris; Haftka, Joris; Hermens, Joop; Jones, Timothy G; Baurès, Estelle; Jung, Aude-Valérie; Thomas, Olivier

    2014-07-18

    The issue of drinking water quality compliance in small and medium scale water services is of paramount importance in relation to the 98/83/CE European Drinking Water Directive (DWD). Additionally, concerns are being expressed over the implementation of the DWD with respect to possible impacts on water quality from forecast changes in European climate with global warming and further anticipated reductions in north European acid emissions. Consequently, we have developed a decision support system (DSS) named ARTEM-WQ (AwaReness Tool for the Evaluation and Mitigation of drinking Water Quality issues resulting from environmental changes) to support decision making by small and medium plant operators and other water stakeholders. ARTEM-WQ is based on a sequential risk analysis approach that includes consideration of catchment characteristics, climatic conditions and treatment operations. It provides a holistic evaluation of the water system, while also assessing human health risks of organic contaminants potentially present in treated waters (steroids, pharmaceuticals, pesticides, bisphenol-a, polychlorobiphenyls, polycyclic aromatic hydrocarbons, petrochemical hydrocarbons and disinfection by-products; n = 109). Moreover, the system provides recommendations for improvement while supporting decision making in its widest context. The tool has been tested on various European catchments and shows a promising potential to inform water managers of risks and appropriate mitigative actions. Further improvements should include toxicological knowledge advancement, environmental background pollutant concentrations and the assessment of the impact of distribution systems on water quality variation.

  18. A Decision Support System for Drinking Water Production Integrating Health Risks Assessment

    PubMed Central

    Delpla, Ianis; Monteith, Donald T.; Freeman, Chris; Haftka, Joris; Hermens, Joop; Jones, Timothy G.; Baurès, Estelle; Jung, Aude-Valérie; Thomas, Olivier

    2014-01-01

    The issue of drinking water quality compliance in small and medium scale water services is of paramount importance in relation to the 98/83/CE European Drinking Water Directive (DWD). Additionally, concerns are being expressed over the implementation of the DWD with respect to possible impacts on water quality from forecast changes in European climate with global warming and further anticipated reductions in north European acid emissions. Consequently, we have developed a decision support system (DSS) named ARTEM-WQ (AwaReness Tool for the Evaluation and Mitigation of drinking Water Quality issues resulting from environmental changes) to support decision making by small and medium plant operators and other water stakeholders. ARTEM-WQ is based on a sequential risk analysis approach that includes consideration of catchment characteristics, climatic conditions and treatment operations. It provides a holistic evaluation of the water system, while also assessing human health risks of organic contaminants potentially present in treated waters (steroids, pharmaceuticals, pesticides, bisphenol-a, polychlorobiphenyls, polycyclic aromatic hydrocarbons, petrochemical hydrocarbons and disinfection by-products; n = 109). Moreover, the system provides recommendations for improvement while supporting decision making in its widest context. The tool has been tested on various European catchments and shows a promising potential to inform water managers of risks and appropriate mitigative actions. Further improvements should include toxicological knowledge advancement, environmental background pollutant concentrations and the assessment of the impact of distribution systems on water quality variation. PMID:25046634

  19. Service-oriented medical system for supporting decisions with missing and imbalanced data.

    PubMed

    Zieba, Maciej

    2014-09-01

    In this paper, we propose a service-oriented support decision system (SOSDS) for diagnostic problems that is insensitive to the problems of the imbalanced data and missing values of the attributes, which are widely observed in the medical domain. The system is composed of distributed Web services, which implement machine-learning solutions dedicated to constructing the decision models directly from the datasets impaired by the high percentage of missing values of the attributes and imbalanced class distribution. The issue of the imbalanced data is solved by the application of a cost-sensitive support vector machine and the problem of missing values of attributes is handled by proposing the novel ensemble-based approach that splits the incomplete data space into complete subspaces that are further used to construct base learners. We evaluate the quality of the SOSDS components using three ontological datasets.

  20. Diverting the tourists: a spatial decision-support system for tourism planning on a developing island

    NASA Astrophysics Data System (ADS)

    Beedasy, Jaishree; Whyatt, Duncan

    Mauritius is a small island (1865 km 2) in the Indian Ocean. Tourism is the third largest economic sector of the country, after manufacturing and agriculture. A limitation of space and the island's vulnerable ecosystem warrants a rational approach to tourism development. The main problems so far have been to manipulate and integrate all the factors affecting tourism planning and to match spatial data with their relevant attributes. A Spatial Decision Support System (SDSS) for sustainable tourism planning is therefore proposed. The proposed SDSS design would include a GIS as its core component. A first GIS model has already been constructed with available data. Supporting decision-making in a spatial context is implicit in the use of GIS. However the analytical capability of the GIS has to be enhanced to solve semi-structured problems, where subjective judgements come into play. The second part of the paper deals with the choice, implementation and customisation of a relevant model to develop a specialised SDSS. Different types of models and techniques are discussed, in particular a comparison of compensatory and non-compensatory approaches to multicriteria evaluation (MCE). It is concluded that compensatory multicriteria evaluation techniques increase the scope of the present GIS model as a decision-support tool. This approach gives the user or decision-maker the flexibility to change the importance of each criterion depending on relevant objectives.

  1. Approaches to verification/validation of imbedded decision support systems applied to launch vehicle operations

    NASA Astrophysics Data System (ADS)

    Szatkowski, G. P.

    A methodology for incorporating expert decision support systems into launch vehicle operations is suggested based on a review of the current state of the art in verification and validation (V & V). Particular attention is given to the following areas that are believed to contribute to the overall V & V process: rapid prototyping, checking toolset utilities, and dynamic simulation analysis. Opportunities in operations that reduce costs and improve autonomy are considered.

  2. Visualization-based decision support for value-driven system design

    NASA Astrophysics Data System (ADS)

    Tibor, Elliott

    In the past 50 years, the military, communication, and transportation systems that permeate our world, have grown exponentially in size and complexity. The development and production of these systems has seen ballooning costs and increased risk. This is particularly critical for the aerospace industry. The inability to deal with growing system complexity is a crippling force in the advancement of engineered systems. Value-Driven Design represents a paradigm shift in the field of design engineering that has potential to help counteract this trend. The philosophy of Value-Driven Design places the desires of the stakeholder at the forefront of the design process to capture true preferences and reveal system alternatives that were never previously thought possible. Modern aerospace engineering design problems are large, complex, and involve multiple levels of decision-making. To find the best design, the decision-maker is often required to analyze hundreds or thousands of combinations of design variables and attributes. Visualization can be used to support these decisions, by communicating large amounts of data in a meaningful way. Understanding the design space, the subsystem relationships, and the design uncertainties is vital to the advancement of Value-Driven Design as an accepted process for the development of more effective, efficient, robust, and elegant aerospace systems. This research investigates the use of multi-dimensional data visualization tools to support decision-making under uncertainty during the Value-Driven Design process. A satellite design system comprising a satellite, ground station, and launch vehicle is used to demonstrate effectiveness of new visualization methods to aid in decision support during complex aerospace system design. These methods are used to facilitate the exploration of the feasible design space by representing the value impact of system attribute changes and comparing the results of multi-objective optimization formulations

  3. Automatic decision support system based on SAR data for oil spill detection

    NASA Astrophysics Data System (ADS)

    Mera, David; Cotos, José M.; Varela-Pet, José; Rodríguez, Pablo G.; Caro, Andrés

    2014-11-01

    Global trade is mainly supported by maritime transport, which generates important pollution problems. Thus, effective surveillance and intervention means are necessary to ensure proper response to environmental emergencies. Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillages on the oceans surface. Several decision support systems have been based on this technology. This paper presents an automatic oil spill detection system based on SAR data which was developed on the basis of confirmed spillages and it was adapted to an important international shipping route off the Galician coast (northwest Iberian Peninsula). The system was supported by an adaptive segmentation process based on wind data as well as a shape oriented characterization algorithm. Moreover, two classifiers were developed and compared. Thus, image testing revealed up to 95.1% candidate labeling accuracy. Shared-memory parallel programming techniques were used to develop algorithms in order to improve above 25% of the system processing time.

  4. Spatial decision support system to evaluate crop residue energy potential by anaerobic digestion.

    PubMed

    Escalante, Humberto; Castro, Liliana; Gauthier-Maradei, Paola; Rodríguez De La Vega, Reynel

    2016-11-01

    Implementing anaerobic digestion (AD) in energy production from crop residues requires development of decision tools to assess its feasibility and sustainability. A spatial decision support system (SDSS) was constructed to assist decision makers to select appropriate feedstock according to biomethanation potential, identify the most suitable location for biogas facilities, determine optimum plant capacity and supply chain, and evaluate associated risks and costs. SDSS involves a spatially explicit analysis, fuzzy multi-criteria analysis, and statistical and optimization models. The tool was validated on seven crop residues located in Santander, Colombia. For example, fique bagasse generates about 0.21millionm(3)CH4year(-1) (0.329m(3)CH4kg(-1) volatile solids) with a minimum profitable plant of about 2000tonyear(-1) and an internal rate of return of 10.5%. SDSS can be applied to evaluate other biomass resources, availability periods, and co-digestion potential.

  5. Spatial decision support system to evaluate crop residue energy potential by anaerobic digestion.

    PubMed

    Escalante, Humberto; Castro, Liliana; Gauthier-Maradei, Paola; Rodríguez De La Vega, Reynel

    2016-11-01

    Implementing anaerobic digestion (AD) in energy production from crop residues requires development of decision tools to assess its feasibility and sustainability. A spatial decision support system (SDSS) was constructed to assist decision makers to select appropriate feedstock according to biomethanation potential, identify the most suitable location for biogas facilities, determine optimum plant capacity and supply chain, and evaluate associated risks and costs. SDSS involves a spatially explicit analysis, fuzzy multi-criteria analysis, and statistical and optimization models. The tool was validated on seven crop residues located in Santander, Colombia. For example, fique bagasse generates about 0.21millionm(3)CH4year(-1) (0.329m(3)CH4kg(-1) volatile solids) with a minimum profitable plant of about 2000tonyear(-1) and an internal rate of return of 10.5%. SDSS can be applied to evaluate other biomass resources, availability periods, and co-digestion potential. PMID:27479798

  6. Systems Analysis - a new paradigm and decision support tools for the water framework directive

    NASA Astrophysics Data System (ADS)

    Bruen, M.

    2008-05-01

    In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness.

  7. Systems analysis - a new paradigm and decision support tools for the water framework directive

    NASA Astrophysics Data System (ADS)

    Bruen, M.

    2007-06-01

    In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness. This is best done by trained sociologists fully integrated into the processes. The WINCOMS research project is an example applied to the implementation of the WFD in Ireland.

  8. A Conceptual Framework for Decision-making Support in Uncertainty- and Risk-based Diagnosis of Rare Clinical Cases by Specialist Physicians.

    PubMed

    Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis

    2015-01-01

    Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model. PMID:26262173

  9. Medical diagnostic decision support systems--past, present, and future: a threaded bibliography and brief commentary.

    PubMed Central

    Miller, R A

    1994-01-01

    Articles about medical diagnostic decision support (MDDS) systems often begin with a disclaimer such as, "despite many years of research and millions of dollars of expenditures on medical diagnostic systems, none is in widespread use at the present time." While this statement remains true in the sense that no single diagnostic system is in widespread use, it is misleading with regard to the state of the art of these systems. Diagnostic systems, many simple and some complex, are now ubiquitous, and research on MDDS systems is growing. The nature of MDDS systems has diversified over time. The prospects for adoption of large-scale diagnostic systems are better now than ever before, due to enthusiasm for implementation of the electronic medical record in academic, commercial, and primary care settings. Diagnostic decision support systems have become an established component of medical technology. This paper provides a review and a threaded bibliography for some of the important work on MDDS systems over the years from 1954 to 1993. PMID:7719792

  10. Imaging informatics-based multimedia ePR system for data management and decision support in rehabilitation research

    NASA Astrophysics Data System (ADS)

    Wang, Ximing; Verma, Sneha; Qin, Yi; Sterling, Josh; Zhou, Alyssa; Zhang, Jeffrey; Martinez, Clarisa; Casebeer, Narissa; Koh, Hyunwook; Winstein, Carolee; Liu, Brent

    2013-03-01

    With the rapid development of science and technology, large-scale rehabilitation centers and clinical rehabilitation trials usually involve significant volumes of multimedia data. Due to the global aging crisis, millions of new patients with age-related chronic diseases will produce huge amounts of data and contribute to soaring costs of medical care. Hence, a solution for effective data management and decision support will significantly reduce the expenditure and finally improve the patient life quality. Inspired from the concept of the electronic patient record (ePR), we developed a prototype system for the field of rehabilitation engineering. The system is subject or patient-oriented and customized for specific projects. The system components include data entry modules, multimedia data presentation and data retrieval. To process the multimedia data, the system includes a DICOM viewer with annotation tools and video/audio player. The system also serves as a platform for integrating decision-support tools and data mining tools. Based on the prototype system design, we developed two specific applications: 1) DOSE (a phase 1 randomized clinical trial to determine the optimal dose of therapy for rehabilitation of the arm and hand after stroke.); and 2) NEXUS project from the Rehabilitation Engineering Research Center(RERC, a NIDRR funded Rehabilitation Engineering Research Center). Currently, the system is being evaluated in the context of the DOSE trial with a projected enrollment of 60 participants over 5 years, and will be evaluated by the NEXUS project with 30 subjects. By applying the ePR concept, we developed a system in order to improve the current research workflow, reduce the cost of managing data, and provide a platform for the rapid development of future decision-support tools.

  11. DESYRE: DEcision Support sYstem for the REhabilitation of contaminated megasites.

    PubMed

    Carlon, Claudio; Critto, Andrea; Ramieri, Emiliano; Marcomini, Antonio

    2007-04-01

    DESYRE (DEcision Support sYstem for the REqualification of contaminated sites) is a GIS-based decision support system (DSS) specifically developed to address the integrated management and remediation of contaminated megasites (i.e., large contaminated areas or impacted areas characterized by multiple site owners and multiple stakeholders). In the DESYRE conceptual design and development the main aspects pertaining to a remediation process--analysis of social and economic benefits and constrains, site characterization, risk assessment, selection of best available technologies, creation of sets of technologies to be applied, analysis of the residual risk, and comparison of different remediation scenarios--were included. The DESYRE DSS is a GIS-based software composed of 6 interconnected modules. In the characterization module, chemical and hydrogeological data are organized in a relational database and contaminants' distributions are mapped by using geostatistic tools. The socioeconomic module addresses the socioeconomic constraints though a fuzzy logic analysis to select the best land use. The risk assessment module is divided into 2 phases. In the preremediation phase, an original procedure allows assessing and representing the spatial distribution of risks posed by contaminants in soil and groundwater, providing a risk-based zoning of the site. Then, in the technology assessment module, a selection of suitable technologies and creation of different technology sets, taking into account both technical requirements and site-specific features, are performed by experts supported by multicriteria decision analysis tools. In the postremediation risk assessment, a simulation of applied technologies provides residual risk maps with related uncertainty maps. Finally, in the decision module, alternative remediation scenarios are described by a set of indices and can be compared and ranked by interested stakeholders using multicriteria decision analysis methodologies. The

  12. A decision-support system for sustainable urban metabolism in Europe

    SciTech Connect

    Gonzalez, Ainhoa; Donnelly, Alison; Jones, Mike; Chrysoulakis, Nektarios; Lopes, Myriam

    2013-01-15

    Urban metabolism components define the energy and material exchanges within a city and, therefore, can provide valuable information on the environmental quality of urban areas. Assessing the potential impact of urban planning alternatives on urban metabolism components (such as energy, water, carbon and pollutants fluxes) can provide a quantitative estimation of their sustainability performance. Urban metabolism impact assessment can, therefore, contribute to the identification of sustainable urban structures with regards, for example, to building types, materials and layout, as well as to location and capacity of transportation and infrastructural developments. In this way, it enables the formulation of planning and policy recommendations to promote efficient use of resources and enhance environmental quality in urban areas. The European FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) has developed a decision-support system (DSS) that systematically integrates urban metabolism components into impact assessment processes with the aim of accurately quantifying the potential effects of proposed planning interventions. The DSS enables integration of multiple spatial and non-spatial datasets (e.g. physical flows of energy and material with variables of social and economic change) in a systematic manner to obtain spatially defined assessment results and to thus inform planners and decision-makers. This multi-criteria approach also enables incorporation of stakeholders' perceptions in order to prioritise decisive assessment criteria. This paper describes the methodological framework used to develop the DSS and critically examines the results of its practical application in five European cities. - Highlights: Black-Right-Pointing-Pointer Urban metabolism in sustainability assessment of planning alternatives. Black-Right-Pointing-Pointer European FP7 project applied to 5 real life case studies across Europe. Black

  13. DESYRE: DEcision Support sYstem for the REhabilitation of contaminated megasites.

    PubMed

    Carlon, Claudio; Critto, Andrea; Ramieri, Emiliano; Marcomini, Antonio

    2007-04-01

    DESYRE (DEcision Support sYstem for the REqualification of contaminated sites) is a GIS-based decision support system (DSS) specifically developed to address the integrated management and remediation of contaminated megasites (i.e., large contaminated areas or impacted areas characterized by multiple site owners and multiple stakeholders). In the DESYRE conceptual design and development the main aspects pertaining to a remediation process--analysis of social and economic benefits and constrains, site characterization, risk assessment, selection of best available technologies, creation of sets of technologies to be applied, analysis of the residual risk, and comparison of different remediation scenarios--were included. The DESYRE DSS is a GIS-based software composed of 6 interconnected modules. In the characterization module, chemical and hydrogeological data are organized in a relational database and contaminants' distributions are mapped by using geostatistic tools. The socioeconomic module addresses the socioeconomic constraints though a fuzzy logic analysis to select the best land use. The risk assessment module is divided into 2 phases. In the preremediation phase, an original procedure allows assessing and representing the spatial distribution of risks posed by contaminants in soil and groundwater, providing a risk-based zoning of the site. Then, in the technology assessment module, a selection of suitable technologies and creation of different technology sets, taking into account both technical requirements and site-specific features, are performed by experts supported by multicriteria decision analysis tools. In the postremediation risk assessment, a simulation of applied technologies provides residual risk maps with related uncertainty maps. Finally, in the decision module, alternative remediation scenarios are described by a set of indices and can be compared and ranked by interested stakeholders using multicriteria decision analysis methodologies. The

  14. A decision support system for real-time hydropower scheduling in a competitive power market environment

    NASA Astrophysics Data System (ADS)

    Shawwash, Ziad Khaled Elias

    2000-10-01

    The electricity supply market is rapidly changing from a monopolistic to a competitive environment. Being able to operate their system of reservoirs and generating facilities to get maximum benefits out of existing assets and resources is important to the British Columbia Hydro Authority (B.C. Hydro). A decision support system has been developed to help B.C. Hydro operate their system in an optimal way. The system is operational and is one of the tools that are currently used by the B.C. Hydro system operations engineers to determine optimal schedules that meet the hourly domestic load and also maximize the value B.C. Hydro obtains from spot transactions in the Western U.S. and Alberta electricity markets. This dissertation describes the development and implementation of the decision support system in production mode. The decision support system consists of six components: the input data preparation routines, the graphical user interface (GUI), the communication protocols, the hydraulic simulation model, the optimization model, and the results display software. A major part of this work involved the development and implementation of a practical and detailed large-scale optimization model that determines the optimal tradeoff between the long-term value of water and the returns from spot trading transactions in real-time operations. The postmortem-testing phase showed that the gains in value from using the model accounted for 0.25% to 1.0% of the revenues obtained. The financial returns from using the decision support system greatly outweigh the costs of building it. Other benefits are the savings in the time needed to prepare the generation and trading schedules. The system operations engineers now can use the time saved to focus on other important aspects of their job. The operators are currently experimenting with the system in production mode, and are gradually gaining confidence that the advice it provides is accurate, reliable and sensible. The main lesson

  15. Clinical Decision Support-based Quality Measurement (CDS-QM) Framework: Prototype Implementation, Evaluation, and Future Directions

    PubMed Central

    Kukhareva, Polina V; Kawamoto, Kensaku; Shields, David E; Barfuss, Darryl T; Halley, Anne M; Tippetts, Tyler J; Warner, Phillip B; Bray, Bruce E; Staes, Catherine J

    2014-01-01

    Electronic quality measurement (QM) and clinical decision support (CDS) are closely related but are typically implemented independently, resulting in significant duplication of effort. While it seems intuitive that technical approaches could be re-used across these two related use cases, such reuse is seldom reported in the literature, especially for standards-based approaches. Therefore, we evaluated the feasibility of using a standards-based CDS framework aligned with anticipated EHR certification criteria to implement electronic QM. The CDS-QM framework was used to automate a complex national quality measure (SCIP-VTE-2) at an academic healthcare system which had previously relied on time-consuming manual chart abstractions. Compared with 305 manually-reviewed reference cases, the recall of automated measurement was 100%. The precision was 96.3% (CI:92.6%-98.5%) for ascertaining the denominator and 96.2% (CI:92.3%-98.4%) for the numerator. We therefore validated that a standards-based CDS-QM framework can successfully enable automated QM, and we identified benefits and challenges with this approach. PMID:25954389

  16. Multi-National, Multi-Institutional Analysis of Clinical Decision Support Data Needs to Inform Development of the HL7 Virtual Medical Record Standard

    PubMed Central

    Kawamoto, Kensaku; Del Fiol, Guilherme; Strasberg, Howard R.; Hulse, Nathan; Curtis, Clayton; Cimino, James J.; Rocha, Beatriz H.; Maviglia, Saverio; Fry, Emory; Scherpbier, Harm J.; Huser, Vojtech; Redington, Patrick K.; Vawdrey, David K.; Dufour, Jean-Charles; Price, Morgan; Weber, Jens H.; White, Thomas; Hughes, Kevin S.; McClay, James C.; Wood, Carla; Eckert, Karen; Bolte, Scott; Shields, David; Tattam, Peter R.; Scott, Peter; Liu, Zhijing; McIntyre, Andrew K.

    2010-01-01

    An important barrier to the widespread dissemination of clinical decision support (CDS) is the heterogeneity of information models and terminologies used across healthcare institutions, health information systems, and CDS resources such as knowledge bases. To address this problem, the Health Level 7 (HL7) Virtual Medical Record project (an open, international standards development effort) is developing community consensus on the clinical information exchanged between CDS engines and clinical information systems. As a part of this effort, the HL7 CDS Work Group embarked on a multinational, collaborative effort to identify a representative set of clinical data elements required for CDS. Based on an analysis of CDS systems from 20 institutions representing 4 nations, 131 data elements were identified as being currently utilized for CDS. These findings will inform the development of the emerging HL7 Virtual Medical Record standard and will facilitate the achievement of scalable, standards-based CDS. PMID:21347004

  17. Multi-National, Multi-Institutional Analysis of Clinical Decision Support Data Needs to Inform Development of the HL7 Virtual Medical Record Standard.

    PubMed

    Kawamoto, Kensaku; Del Fiol, Guilherme; Strasberg, Howard R; Hulse, Nathan; Curtis, Clayton; Cimino, James J; Rocha, Beatriz H; Maviglia, Saverio; Fry, Emory; Scherpbier, Harm J; Huser, Vojtech; Redington, Patrick K; Vawdrey, David K; Dufour, Jean-Charles; Price, Morgan; Weber, Jens H; White, Thomas; Hughes, Kevin S; McClay, James C; Wood, Carla; Eckert, Karen; Bolte, Scott; Shields, David; Tattam, Peter R; Scott, Peter; Liu, Zhijing; McIntyre, Andrew K

    2010-11-13

    An important barrier to the widespread dissemination of clinical decision support (CDS) is the heterogeneity of information models and terminologies used across healthcare institutions, health information systems, and CDS resources such as knowledge bases. To address this problem, the Health Level 7 (HL7) Virtual Medical Record project (an open, international standards development effort) is developing community consensus on the clinical information exchanged between CDS engines and clinical information systems. As a part of this effort, the HL7 CDS Work Group embarked on a multinational, collaborative effort to identify a representative set of clinical data elements required for CDS. Based on an analysis of CDS systems from 20 institutions representing 4 nations, 131 data elements were identified as being currently utilized for CDS. These findings will inform the development of the emerging HL7 Virtual Medical Record standard and will facilitate the achievement of scalable, standards-based CDS.

  18. Science and Systems in Support of Multi-hazard Early Warnings and Decisions

    NASA Astrophysics Data System (ADS)

    Pulwarty, R. S.

    2015-12-01

    The demand for improved climate knowledge and information is well documented. As noted in the IPCC (SREX, AR5), the UNISDR Global Assessment Reports and other assessments, this demand has increased pressure for information to support planning under changing rates and emergence of multiple hazards including climate extremes (drought, heat waves, floods). "Decision support" is now a popular term in the climate applications research community. While existing decision support activities can be identified in many disparate settings (e.g. federal, academic, private), the challenge of changing environments (coupled physical and social) is actually one of crafting implementation strategies for improving decision quality (not just meeting "user needs"). This includes overcoming weaknesses in co-production models, moving beyond DSSs as simply "software", coordinating innovation mapping and diffusion, and providing fora and gaming tools to identify common interests and differences in the way risks are perceived and managed among the affected groups. We outline the development and evolution of multi-hazard early warning systems in the United States and elsewhere, focusing on climate-related hazards. In particular, the presentation will focus on the climate science and information needed for (1) improved monitoring and modeling, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds, (4) the net benefits of using new information (5) characterizing and bridging the "last mile" in the context of longer-term risk management.

  19. Clinical Decision Support Using Electronic Medical Records: For the Improvement of Diabetes Care and Proper Use of Insulin for Inpatients.

    PubMed

    Seto, Ryoma; Wakabayashi, Susumu

    2015-01-01

    The aim of the study is to develop a scheme of a decision support system concerning insulin intervention for inpatients. Transaction data for 32,637 inpatients were collected from the EMR. As a result, antidiabetic agents were not taken by 38.9%-41.7% of patients with a Disease Complicated by DM. It is recommended that the EMR should provide a suggestion about insulin level for diseases with DM as a complicating factor. PMID:26262263

  20. Will decision-support systems be widely used for the management of plant diseases?

    PubMed

    Shtienberg, Dani

    2013-01-01

    Decision-support systems (DSSs) are interactive computer-based systems that help decision makers solve unstructured problems under complex, uncertain conditions. Experimental use of DSSs has resulted in improved disease suppression and lowered risks of crop damage. In many cases, it has also led to the use of smaller quantities of active substances, as compared with standard spraying practices. Hundreds of DSSs have been developed over the years and are readily available and affordable. However, most farm managers do not use them as part of their integrated pest management (IPM) practices. Since the mid-1980s, the author of this paper, together with numerous colleagues, has developed DSSs and decision rules for the management of diseases in a variety of crops, including extensive crops, such as wheat, sunflower, and pea; semi-intensive crops, such as pear, chickpea, cotton, and tarragon; and intensive crops, such as tomato, potato, cucumber, sweet pepper, carrot, and grapevine. Some of these systems were used widely, but others were not. This experience may allow us to draw general conclusions regarding the use of DSSs and decision rules. Possible explanations for the widely varying acceptance rates are presented, and the effects of anticipated changes in the agribusiness sector on the future use of DSSs are discussed.

  1. A collaborative framework for contributing DICOM RT PHI (Protected Health Information) to augment data mining in clinical decision support

    NASA Astrophysics Data System (ADS)

    Deshpande, Ruchi; Thuptimdang, Wanwara; DeMarco, John; Liu, Brent J.

    2014-03-01

    We have built a decision support system that provides recommendations for customizing radiation therapy treatment plans, based on patient models generated from a database of retrospective planning data. This database consists of relevant metadata and information derived from the following DICOM objects - CT images, RT Structure Set, RT Dose and RT Plan. The usefulness and accuracy of such patient models partly depends on the sample size of the learning data set. Our current goal is to increase this sample size by expanding our decision support system into a collaborative framework to include contributions from multiple collaborators. Potential collaborators are often reluctant to upload even anonymized patient files to repositories outside their local organizational network in order to avoid any conflicts with HIPAA Privacy and Security Rules. We have circumvented this problem by developing a tool that can parse DICOM files on the client's side and extract de-identified numeric and text data from DICOM RT headers for uploading to a centralized system. As a result, the DICOM files containing PHI remain local to the client side. This is a novel workflow that results in adding only relevant yet valuable data from DICOM files to the centralized decision support knowledge base in such a way that the DICOM files never leave the contributor's local workstation in a cloud-based environment. Such a workflow serves to encourage clinicians to contribute data for research endeavors by ensuring protection of electronic patient data.

  2. Decision support system based on DPSIR framework for a low flow Mediterranean river basin

    NASA Astrophysics Data System (ADS)

    Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

    2013-04-01

    The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river

  3. Clinical diagnosis support system based on case based fuzzy cognitive maps and semantic web.

    PubMed

    Douali, Nassim; De Roo, Jos; Jaulent, Marie-Christine

    2012-01-01

    Incorrect or improper diagnostic tests uses have important implications for health outcomes and costs. Clinical Decision Support Systems purports to optimize the use of diagnostic tests in clinical practice. The computerized medical reasoning should not only focus on existing medical knowledge but also on physician's previous experiences and new knowledge. Such medical knowledge is vague and defines uncertain relationships between facts and diagnosis, in this paper, Case Based Fuzzy Cognitive Maps (CBFCM) are proposed as an evolution of Fuzzy Cognitive Maps. They allow more complete representation of knowledge since case-based fuzzy rules are introduced to improve diagnosis decision. We have developed a framework for interacting with patient's data and formalizing knowledge from Guidelines in the domain of Urinary Tract Infection. The conducted study allowed us to test cognitive approaches for implementing Guidelines with Semantic Web tools. The advantage of this approach is to enable the sharing and reuse of knowledge from Guidelines, physicians experiences and simplify maintenance.

  4. Leveraging Expert Knowledge to Improve Machine-Learned Decision Support Systems.

    PubMed

    Kuusisto, Finn; Dutra, Inês; Elezaby, Mai; Mendonça, Eneida A; Shavlik, Jude; Burnside, Elizabeth S

    2015-01-01

    While the use of machine learning methods in clinical decision support has great potential for improving patient care, acquiring standardized, complete, and sufficient training data presents a major challenge for methods relying exclusively on machine learning techniques. Domain experts possess knowledge that can address these challenges and guide model development. We present Advice-Based-Learning (ABLe), a framework for incorporating expert clinical knowledge into machine learning models, and show results for an example task: estimating the probability of malignancy following a non-definitive breast core needle biopsy. By applying ABLe to this task, we demonstrate a statistically significant improvement in specificity (24.0% with p=0.004) without missing a single malignancy.

  5. A DICOM-RT Based ePR radiation therapy information system for decision-support of brain tumor patients

    NASA Astrophysics Data System (ADS)

    Liu, B. J.; Law, M.; Huang, H. K.; Zee, C. S.; Chan, L.

    2006-03-01

    The need for comprehensive clinical image data and relevant information in image-guided Radiation Therapy (RT) is becoming steadily apparent. Multiple standalone systems utilizing the most technological advancements in imaging, therapeutic radiation, and computerized treatment planning systems acquire key data during the RT treatment course of a patient. One example are patients treated for brain tumors of greater sizes and irregular shapes that utilize state-of-the-art RT technology to deliver pinpoint accurate radiation doses. Various treatment options are available to the patient from Radiation Therapy to Stereotactic Radiosurgery and utilize different RT modalities. The disparate and complex data generated by the RT modalities along with related data scattered throughout the RT department in RT Information/Management systems, Record & Verify systems, and Treatment Planning Systems (TPS) compromise an efficient clinical workflow since the data crucial for a clinical decision may be time-consuming to retrieve, temporarily missing, or even lost. To address these shortcomings, the ACR-NEMA Standards Committee extended its DICOM (Digital Imaging & Communications in Medicine) Standard from Radiology to RT by ratifying seven DICOM RT objects starting in 1997. However, they are rarely used by the RT community in daily clinical operations. In the past, the research focus of an RT department has primarily been developing new protocols and devices to improve treatment process and outcomes of cancer patients with minimal effort dedicated to integration of imaging and information systems. By combining our past experience in medical imaging informatics research, DICOM-RT expertise, and system integration, our research involves using a brain tumor case model to show proof-of-concept that a DICOM-Standard electronic patient record (ePR) system can be developed as a foundation to perform medical imaging informatics research in developing decision-support tools and knowledge

  6. 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.

  7. 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. PMID:27209183

  8. Automating hypertext for decision support

    NASA Technical Reports Server (NTRS)

    Bieber, Michael

    1990-01-01

    A decision support system (DSS) shell is being constructed that can support applications in a variety of fields, e.g., engineering, manufacturing, finance. The shell provides a hypertext-style interface for 'navigating' among DSS application models, data, and reports. The traditional notion of hypertext had to be enhanced. Hypertext normally requires manually, pre-defined links. A DSS shell, however, requires that hypertext connections to be built 'on the fly'. The role of hypertext is discussed in augmenting DSS applications and the decision making process. Also discussed is how hypertext nodes, links, and link markers tailored to an arbitrary DSS application were automatically generated.

  9. A multi-agent-based, semantic-driven system for decision support in epidemic management.

    PubMed

    Li, Sen; Mackaness, William A

    2015-09-01

    Issues in epidemiology are truly multidisciplinary, requiring knowledge from diverse disciplines such as sociology, medicine, biology, geography and information science. Such inherent complexity has led to a challenge in developing decision support systems for epidemic information management, especially when data are from heterogeneous origins. In order to achieve a solution, an integrative framework is proposed. The Semantic Web is introduced in the context of enriching meaningful and machine-readable descriptions of epidemiological data. Software agents are utilised to achieve automation in semantic discovery, composition of data and process services. The objective is to enhance the performance in information retrieval in a dynamic decision-making environment while concealing technical complexity from inexperienced users. We illustrate how a prototype system can be developed by considering an epidemiology management scenario in which spatio-temporal analysis is undertaken of a specified epidemic. PMID:24448277

  10. A multi-agent-based, semantic-driven system for decision support in epidemic management.

    PubMed

    Li, Sen; Mackaness, William A

    2015-09-01

    Issues in epidemiology are truly multidisciplinary, requiring knowledge from diverse disciplines such as sociology, medicine, biology, geography and information science. Such inherent complexity has led to a challenge in developing decision support systems for epidemic information management, especially when data are from heterogeneous origins. In order to achieve a solution, an integrative framework is proposed. The Semantic Web is introduced in the context of enriching meaningful and machine-readable descriptions of epidemiological data. Software agents are utilised to achieve automation in semantic discovery, composition of data and process services. The objective is to enhance the performance in information retrieval in a dynamic decision-making environment while concealing technical complexity from inexperienced users. We illustrate how a prototype system can be developed by considering an epidemiology management scenario in which spatio-temporal analysis is undertaken of a specified epidemic.

  11. E-Estuary: Developing a Decision-support System for Coastal Management in the Conterminous United States

    EPA Science Inventory

    Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The United States Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E...

  12. E-Estuary: Developing a Decision-support System for Coastal Management in the Counterminous Untied States (Coastal Geotools 09)

    EPA Science Inventory

    Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The U.S. Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E-Estuary ...

  13. E-Estuary: Developing a Decision Support System for Coastal Management in the Conterminous United States (IAHR)

    EPA Science Inventory

    Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The U.S. Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E-Estuary ...

  14. E-estuary: A Decision Support System for Coastal Water and Ecosystem Management in the US (CZ09)

    EPA Science Inventory

    Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The U.S. Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E-Estuary ...

  15. Decision support system for emergency management of oil spill accidents in the Mediterranean Sea

    NASA Astrophysics Data System (ADS)

    Liubartseva, Svitlana; Coppini, Giovanni; Pinardi, Nadia; De Dominicis, Michela; Lecci, Rita; Turrisi, Giuseppe; Cretì, Sergio; Martinelli, Sara; Agostini, Paola; Marra, Palmalisa; Palermo, Francesco

    2016-08-01

    This paper presents an innovative web-based decision support system to facilitate emergency management in the case of oil spill accidents, called WITOIL (Where Is The Oil). The system can be applied to create a forecast of oil spill events, evaluate uncertainty of the predictions, and calculate hazards based on historical meteo-oceanographic datasets. To compute the oil transport and transformation, WITOIL uses the MEDSLIK-II oil spill model forced by operational meteo-oceanographic services. Results of the modeling are visualized through Google Maps. A special application for Android is designed to provide mobile access for competent authorities, technical and scientific institutions, and citizens.

  16. The Need for Clinical Decision Support Integrated with the Electronic Health Record for the Clinical Application of Whole Genome Sequencing Information

    PubMed Central

    Welch, Brandon M.; Kawamoto, Kensaku

    2013-01-01

    Whole genome sequencing (WGS) is rapidly approaching widespread clinical application. Technology advancements over the past decade, since the first human genome was decoded, have made it feasible to use WGS for clinical care. Future advancements will likely drive down the price to the point wherein WGS is routinely available for care. However, were this to happen today, most of the genetic information available to guide clinical care would go unused due to the complexity of genetics, limited physician proficiency in genetics, and lack of genetics professionals in the clinical workforce. Furthermore, these limitations are unlikely to change in the future. As such, the use of clinical decision support (CDS) to guide genome-guided clinical decision-making is imperative. In this manuscript, we describe the barriers to widespread clinical application of WGS information, describe how CDS can be an important tool for overcoming these barriers, and provide clinical examples of how genome-enabled CDS can be used in the clinical setting. PMID:25411643

  17. Coordinated management of combined sewer overflows by means of environmental decision support systems.

    PubMed

    Murla, Damian; Gutierrez, Oriol; Martinez, Montse; Suñer, David; Malgrat, Pere; Poch, Manel

    2016-04-15

    During heavy rainfall, the capacity of sewer systems and wastewater treatment plants may be surcharged producing uncontrolled wastewater discharges and a depletion of the environmental quality. Therefore there is a need of advanced management tools to tackle with these complex problems. In this paper an environmental decision support system (EDSS), based on the integration of mathematical modeling and knowledge-based systems, has been developed for the coordinated management of urban wastewater systems (UWS) to control and minimize uncontrolled wastewater spills. Effectiveness of the EDSS has been tested in a specially designed virtual UWS, including two sewers systems, two WWTP and one river subjected to typical Mediterranean rain conditions. Results show that sewer systems, retention tanks and wastewater treatment plants improve their performance under wet weather conditions and that EDSS can be very effective tools to improve the management and prevent the system from possible uncontrolled wastewater discharges.

  18. A spatial decision support system prototype for housing mobility program planning

    NASA Astrophysics Data System (ADS)

    Johnson, Michael P.

    This paper presents a GIS-based decision support system prototype intended for use by public housing authority (PHA) administrators and planners designing policy for housing mobility programs. Housing mobility programs enable low-income families, many of whom live in government-operated public housing, to move to more desirable private-market rentals via rent subsidies. Unfortunately, housing authority planners have limited ability to visualize alternative relocation schemes of cohorts of low-income families or the impacts associated with these relocation policies. Thus, they are often not able to give highest-quality advice to clients regarding places to search for private-market rental housing. Housing Location Planner assists PHA planners in three ways: it analyzes spatial, demographic and housing market characteristics of the study area, selects certain portions of the study area for input to an optimization model which generates alternative family allocations, and displays optimization model results in a way that links decision variable values and objective function values. Housing Location Planner is seen as a first step in the development of even more sophisticated multi-stakeholder spatial decision support systems for subsidized housing planning in which one or more alternative allocations of families across a study area is chosen as a basis for policy initiatives.

  19. Decision Support System for an efficient irrigation water management in semi arid environment

    NASA Astrophysics Data System (ADS)

    Khan, M. A.; Islam, M.; Hafeez, M. M.; Flugel, W. A.

    2009-12-01

    A significant increase in agricultural productivity over the last few decades has protected the world from episodes of hunger and food shortages. Water management in irrigated agriculture was instrumental in achieving those gains. Water resources are under high pressure due to rapid population growth and increased competition among various sectors. Access to reliable data on water availability, quantity and quality can provide the necessary foundation for sound management of water resources. There are many traditional methods for matching water demand and supply, however imbalances between demand and supply remain inevitable. It is possible to reduce the imbalances considerably through development of appropriate irrigation water management tool that take into account various factors such as soil type, irrigation water supply, and crop water demand. All components of water balance need to be understood and quantified for efficient and sustainable management of water resources. Application of an intelligent Decision Support System (DSS) is becoming significant. A DSS incorporates knowledge and expertise within the decision support framework. It is an integrated set of data, functions, models and other relevant information that efficiently processes input data, simulates models and displays the results in a user friendly format. It helps in decision-making process, to analyse the problem and explore various scenarios to make the most appropriate decision for water management. This paper deals with the Coleambally Irrigation Area (CIA) located in Murrumbidgee catchment, NSW, Australia. An Integrated River Information System called Coleambally IRIS has been developed to improve the irrigation water management ranging from farm to sub-system and system level. It is a web-based information management system with a focus on time series and geospatial hydrological, climatic and remote sensing data including land cover class, surface temperature, soil moisture, Normalized

  20. Operator decision support system for integrated wastewater management including wastewater treatment plants and receiving water bodies.

    PubMed

    Kim, Minsoo; Kim, Yejin; Kim, Hyosoo; Piao, Wenhua; Kim, Changwon

    2016-06-01

    An operator decision support system (ODSS) is proposed to support operators of wastewater treatment plants (WWTPs) in making appropriate decisions. This system accounts for water quality (WQ) variations in WWTP influent and effluent and in the receiving water body (RWB). The proposed system is comprised of two diagnosis modules, three prediction modules, and a scenario-based supporting module (SSM). In the diagnosis modules, the WQs of the influent and effluent WWTP and of the RWB are assessed via multivariate analysis. Three prediction modules based on the k-nearest neighbors (k-NN) method, activated sludge model no. 2d (ASM2d) model, and QUAL2E model are used to forecast WQs for 3 days in advance. To compare various operating alternatives, SSM is applied to test various predetermined operating conditions in terms of overall oxygen transfer coefficient (Kla), waste sludge flow rate (Qw), return sludge flow rate (Qr), and internal recycle flow rate (Qir). In the case of unacceptable total phosphorus (TP), SSM provides appropriate information for the chemical treatment. The constructed ODSS was tested using data collected from Geumho River, which was the RWB, and S WWTP in Daegu City, South Korea. The results demonstrate the capability of the proposed ODSS to provide WWTP operators with more objective qualitative and quantitative assessments of WWTP and RWB WQs. Moreover, the current study shows that ODSS, using data collected from the study area, can be used to identify operational alternatives through SSM at an integrated urban wastewater management level.

  1. Operator decision support system for integrated wastewater management including wastewater treatment plants and receiving water bodies.

    PubMed

    Kim, Minsoo; Kim, Yejin; Kim, Hyosoo; Piao, Wenhua; Kim, Changwon

    2016-06-01

    An operator decision support system (ODSS) is proposed to support operators of wastewater treatment plants (WWTPs) in making appropriate decisions. This system accounts for water quality (WQ) variations in WWTP influent and effluent and in the receiving water body (RWB). The proposed system is comprised of two diagnosis modules, three prediction modules, and a scenario-based supporting module (SSM). In the diagnosis modules, the WQs of the influent and effluent WWTP and of the RWB are assessed via multivariate analysis. Three prediction modules based on the k-nearest neighbors (k-NN) method, activated sludge model no. 2d (ASM2d) model, and QUAL2E model are used to forecast WQs for 3 days in advance. To compare various operating alternatives, SSM is applied to test various predetermined operating conditions in terms of overall oxygen transfer coefficient (Kla), waste sludge flow rate (Qw), return sludge flow rate (Qr), and internal recycle flow rate (Qir). In the case of unacceptable total phosphorus (TP), SSM provides appropriate information for the chemical treatment. The constructed ODSS was tested using data collected from Geumho River, which was the RWB, and S WWTP in Daegu City, South Korea. The results demonstrate the capability of the proposed ODSS to provide WWTP operators with more objective qualitative and quantitative assessments of WWTP and RWB WQs. Moreover, the current study shows that ODSS, using data collected from the study area, can be used to identify operational alternatives through SSM at an integrated urban wastewater management level. PMID:26893178

  2. Image data integration and analysis for natural disaster decision support systems

    NASA Astrophysics Data System (ADS)

    Roper, William E.

    2001-06-01

    Natural disasters have a major impact, globally and within the United States causing injury and loss of life, as well as economic losses. To better address disaster response needs, a task force has been established to leverage technological capabilities to improve disaster response management. Web based geospatial analysis is one of these important capabilities. Samples of geospatial technologies applicable to disaster management are presented. These include 3D visualization, hyperspectral imagery, LIDAR, use of spectral libraries, digital multispectral video, radar imaging systems, photogeologic analysis and geographic information systems. An example scenario of a hurricane with landfall at Mobile, Alabama is used to demonstrate the interoperable use of web-based geospatial information to support decision support systems and assist public information communication.

  3. Mortality Benefits of Antibiotic Computerised Decision Support System: Modifying Effects of Age

    NASA Astrophysics Data System (ADS)

    Chow, Angela L. P.; Lye, David C.; Arah, Onyebuchi A.

    2015-11-01

    Antibiotic computerised decision support systems (CDSSs) are shown to improve antibiotic prescribing, but evidence of beneficial patient outcomes is limited. We conducted a prospective cohort study in a 1500-bed tertiary-care hospital in Singapore, to evaluate the effectiveness of the hospital’s antibiotic CDSS on patients’ clinical outcomes, and the modification of these effects by patient factors. To account for clustering, we used multilevel logistic regression models. One-quarter of 1886 eligible inpatients received CDSS-recommended antibiotics. Receipt of antibiotics according to CDSS’s recommendations seemed to halve mortality risk of patients (OR 0.54, 95% CI 0.26-1.10, P = 0.09). Patients aged ≤65 years had greater mortality benefit (OR 0.45, 95% CI 0.20-1.00, P = 0.05) than patients that were older than 65 (OR 1.28, 95% CI 0.91-1.82, P = 0.16). No effect was observed on incidence of Clostridium difficile (OR 1.02, 95% CI 0.34-3.01), and multidrug-resistant organism (OR 1.06, 95% CI 0.42-2.71) infections. No increase in infection-related readmission (OR 1.16, 95% CI 0.48-2.79) was found in survivors. Receipt of CDSS-recommended antibiotics reduced mortality risk in patients aged 65 years or younger and did not increase the risk in older patients. Physicians should be informed of the benefits to increase their acceptance of CDSS recommendations.

  4. Mortality Benefits of Antibiotic Computerised Decision Support System: Modifying Effects of Age

    PubMed Central

    Chow, Angela L. P.; Lye, David C.; Arah, Onyebuchi A.

    2015-01-01

    Antibiotic computerised decision support systems (CDSSs) are shown to improve antibiotic prescribing, but evidence of beneficial patient outcomes is limited. We conducted a prospective cohort study in a 1500-bed tertiary-care hospital in Singapore, to evaluate the effectiveness of the hospital’s antibiotic CDSS on patients’ clinical outcomes, and the modification of these effects by patient factors. To account for clustering, we used multilevel logistic regression models. One-quarter of 1886 eligible inpatients received CDSS-recommended antibiotics. Receipt of antibiotics according to CDSS’s recommendations seemed to halve mortality risk of patients (OR 0.54, 95% CI 0.26–1.10, P = 0.09). Patients aged ≤65 years had greater mortality benefit (OR 0.45, 95% CI 0.20–1.00, P = 0.05) than patients that were older than 65 (OR 1.28, 95% CI 0.91–1.82, P = 0.16). No effect was observed on incidence of Clostridium difficile (OR 1.02, 95% CI 0.34–3.01), and multidrug-resistant organism (OR 1.06, 95% CI 0.42–2.71) infections. No increase in infection-related readmission (OR 1.16, 95% CI 0.48–2.79) was found in survivors. Receipt of CDSS-recommended antibiotics reduced mortality risk in patients aged 65 years or younger and did not increase the risk in older patients. Physicians should be informed of the benefits to increase their acceptance of CDSS recommendations. PMID:26617195

  5. Description and status update on GELLO: a proposed standardized object-oriented expression language for clinical decision support.

    PubMed

    Sordo, Margarita; Boxwala, Aziz A; Ogunyemi, Omolola; Greenes, Robert A

    2004-01-01

    A major obstacle to sharing computable clinical knowledge is the lack of a common language for specifying expressions and criteria. Such a language could be used to specify decision criteria, formulae, and constraints on data and action. Al-though the Arden Syntax addresses this problem for clinical rules, its generalization to HL7's object-oriented data model is limited. The GELLO Expression language is an object-oriented language used for expressing logical conditions and computations in the GLIF3 (GuideLine Interchange Format, v. 3) guideline modeling language. It has been further developed under the auspices of the HL7 Clinical Decision Support Technical Committee, as a proposed HL7 standard., GELLO is based on the Object Constraint Language (OCL), because it is vendor-independent, object-oriented, and side-effect-free. GELLO expects an object-oriented data model. Although choice of model is arbitrary, standardization is facilitated by ensuring that the data model is compatible with the HL7 Reference Information Model (RIM).

  6. Application of best practice approaches for designing decision support tools: The preparatory education about clinical trials (PRE-ACT) study

    PubMed Central

    Fleisher, Linda; Ruggieri, Dominique G.; Miller, Suzanne M.; Manne, Sharon; Albrecht, Terrance; Buzaglo, Joanne; Collins, Michael A.; Katz, Michael; Kinzy, Tyler G.; Liu, Tasnuva; Manning, Cheri; Charap, Ellen Specker; Millard, Jennifer; Miller, Dawn M.; Poole, David; Raivitch, Stephanie; Roach, Nancy; Ross, Eric A.; Meropol, Neal J.

    2014-01-01

    Objective This article describes the rigorous development process and initial feedback of the PRE-ACT (Preparatory Education About Clinical Trials) web-based- intervention designed to improve preparation for decision making in cancer clinical trials. Methods The multi-step process included stakeholder input, formative research, user testing and feedback. Diverse teams (researchers, advocates and developers) participated including content refinement, identification of actors, and development of video scripts. Patient feedback was provided in the final production period and through a vanguard group (N = 100) from the randomized trial. Results Patients/advocates confirmed barriers to cancer clinical trial participation, including lack of awareness and knowledge, fear of side effects, logistical concerns, and mistrust. Patients indicated they liked the tool’s user-friendly nature, the organized and comprehensive presentation of the subject matter, and the clarity of the videos. Conclusion The development process serves as an example of operationalizing best practice approaches and highlights the value of a multi-disciplinary team to develop a theory-based, sophisticated tool that patients found useful in their decision making process. Practice implications Best practice approaches can be addressed and are important to ensure evidence-based tools that are of value to patients and supports the usefulness of a process map in the development of e-health tools. PMID:24813474

  7. Intelligent decision support in process environments

    SciTech Connect

    Hollnagel, E.; Mancini, G.; Woods, D.D.

    1986-01-01

    This book deals with the basis for design of intelligent systems to support human decision-making in supervisory control, and provides a view of how human and artificial cognitive systems can interact. It covers the design and development of intelligent decision aiding systems, as well as the testing and evaluation. Topics discussed include: decision theory; cognitive engineering; systems engineering; and artificial intelligence.

  8. Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system.

    PubMed

    Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai

    2015-08-01

    This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts.

  9. An overview of emerging technologies in contemporary decision support system development

    SciTech Connect

    Nursal, Ahmad Taufik E-mail: faizal-omar@uum.edu.my; Omar, Mohd Faizal E-mail: faizal-omar@uum.edu.my; Nawi, Mohd Nasrun Mohd

    2014-12-04

    The rapid development of Web technology has opened a new approach to Decision Support System (DSS) development. For instance, Social Media is one of the Web 2.0 digital platforms that allow the creation and exchanges of user-generate content through an interactive interface, high user control and mass participation. The concept and characteristics of Web 2.0 such as remote, platform-independent, context-rich and easy to use, which is fulfill the concept and purpose of DSS. This paper outlines some of the elementary concepts of Web 2.0 and social media technology which can be potentially integrated within DSS to enhance the decision-making process. Our initial investigation indicates that there is limited study attempt to embed Web 2.0 into DSS. Thus, this paper highlights the importance of Web 2.0 technology in order to foster the betterment of DSS development and its usability.

  10. Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

    NASA Technical Reports Server (NTRS)

    Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

    1987-01-01

    In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

  11. An overview of emerging technologies in contemporary decision support system development

    NASA Astrophysics Data System (ADS)

    Nursal, Ahmad Taufik; Omar, Mohd Faizal; Nawi, Mohd Nasrun Mohd

    2014-12-01

    The rapid development of Web technology has opened a new approach to Decision Support System (DSS) development. For instance, Social Media is one of the Web 2.0 digital platforms that allow the creation and exchanges of user-generate content through an interactive interface, high user control and mass participation. The concept and characteristics of Web 2.0 such as remote, platform-independent, context-rich and easy to use, which is fulfill the concept and purpose of DSS. This paper outlines some of the elementary concepts of Web 2.0 and social media technology which can be potentially integrated within DSS to enhance the decision-making process. Our initial investigation indicates that there is limited study attempt to embed Web 2.0 into DSS. Thus, this paper highlights the importance of Web 2.0 technology in order to foster the betterment of DSS development and its usability.

  12. A decision support system for delivering optimal quality peach and tomato

    NASA Technical Reports Server (NTRS)

    Thai, C. N.; Pease, J. N.; Shewfelt, R. L.

    1990-01-01

    Several studies have indicated that color and firmness are the two quality attributes most important to consumers in making purchasing decisions of fresh peaches and tomatoes. However, at present, retail produce managers do not have the proper information for handling fresh produce so it has the most appealing color and firmness when it reaches the consumer. This information should help them predict the consumer color and firmness perception and preference for produce from various storage conditions. Since 1987, for 'Redglobe' peach and 'Sunny' tomato, we have been generating information about their physical quality attributes (firmness and color) and their corresponding consumer sensory scores. This article reports on our current progress toward the goal of integrating such information into a model-based decision support system for retail level managers in handling fresh peaches and tomatoes.

  13. Seismic slope-performance analysis: from hazard map to decision support system

    USGS Publications Warehouse

    Miles, Scott B.; Keefer, David K.; Ho, Carlton L.

    1999-01-01

    In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.

  14. LCA-IWM: a decision support tool for sustainability assessment of waste management systems.

    PubMed

    den Boer, J; den Boer, E; Jager, J

    2007-01-01

    The paper outlines the most significant result of the project 'The use of life cycle assessment tools for the development of integrated waste management strategies for cities and regions with rapid growing economies', which was the development of two decision-support tools: a municipal waste prognostic tool and a waste management system assessment tool. The article focuses on the assessment tool, which supports the adequate decision making in the planning of urban waste management systems by allowing the creation and comparison of different scenarios, considering three basic subsystems: (i) temporary storage; (ii) collection and transport and (iii) treatment, disposal and recycling. The design and analysis options, as well as the assumptions made for each subsystem, are shortly introduced, providing an overview of the applied methodologies and technologies. The sustainability assessment methodology used in the project to support the selection of the most adequate scenario is presented with a brief explanation of the procedures, criteria and indicators applied on the evaluation of each of the three sustainability pillars. PMID:17428653

  15. LCA-IWM: A decision support tool for sustainability assessment of waste management systems

    SciTech Connect

    Boer, J. den Boer, E. den; Jager, J.

    2007-07-01

    The paper outlines the most significant result of the project 'The use of life cycle assessment tools for the development of integrated waste management strategies for cities and regions with rapid growing economies', which was the development of two decision-support tools: a municipal waste prognostic tool and a waste management system assessment tool. The article focuses on the assessment tool, which supports the adequate decision making in the planning of urban waste management systems by allowing the creation and comparison of different scenarios, considering three basic subsystems: (i) temporary storage; (ii) collection and transport and (iii) treatment, disposal and recycling. The design and analysis options, as well as the assumptions made for each subsystem, are shortly introduced, providing an overview of the applied methodologies and technologies. The sustainability assessment methodology used in the project to support the selection of the most adequate scenario is presented with a brief explanation of the procedures, criteria and indicators applied on the evaluation of each of the three sustainability pillars.

  16. An Ontology-Based, Mobile-Optimized System for Pharmacogenomic Decision Support at the Point-of-Care

    PubMed Central

    Miñarro-Giménez, Jose Antonio; Blagec, Kathrin; Boyce, Richard D.; Adlassnig, Klaus-Peter; Samwald, Matthias

    2014-01-01

    Background The development of genotyping and genetic sequencing techniques and their evolution towards low costs and quick turnaround have encouraged a wide range of applications. One of the most promising applications is pharmacogenomics, where genetic profiles are used to predict the most suitable drugs and drug dosages for the individual patient. This approach aims to ensure appropriate medical treatment and avoid, or properly manage, undesired side effects. Results We developed the Medicine Safety Code (MSC) service, a novel pharmacogenomics decision support system, to provide physicians and patients with the ability to represent pharmacogenomic data in computable form and to provide pharmacogenomic guidance at the point-of-care. Pharmacogenomic data of individual patients are encoded as Quick Response (QR) codes and can be decoded and interpreted with common mobile devices without requiring a centralized repository for storing genetic patient data. In this paper, we present the first fully functional release of this system and describe its architecture, which utilizes Web Ontology Language 2 (OWL 2) ontologies to formalize pharmacogenomic knowledge and to provide clinical decision support functionalities. Conclusions The MSC system provides a novel approach for enabling the implementation of personalized medicine in clinical routine. PMID:24787444

  17. Design and Implementation of a Web-Based Collaborative Spatial Decision Support System: Organizational and Managerial Implications.

    ERIC Educational Resources Information Center

    Sikder, Iftikhar U.; Gangopadhyay, Aryya

    2002-01-01

    Discusses the development of collaborative spatial support systems and identifies research issues on the design and implementation of a Web-based collaborative spatial decision-making system, in the specific context of distributed environmental planning. Demonstrates the use of GEO-ELCA for decision-making tasks by urban or municipal planning…

  18. Increasing the Reliability of Decision-Support Systems for Nuclear Emergency Management

    NASA Astrophysics Data System (ADS)

    Ionescu, Tudor B.

    2013-04-01

    Decision support systems for nuclear emergency management (DSNE) are currently used worldwide to assist decision makers in taking emergency response countermeasures in case of accidental releases of radioactive materials from nuclear facilities. The present work has been motivated by the fact that, up until now, DSNE systems have not been regarded as safety critical software systems. The core of any DSNE system is represented by the different simulation codes linked together to form the dispersion simulation workflow. These codes require input emission and meteorological data to produce forecasts of the atmospheric dispersion of radioactive pollutants and other substances. However, the reliability of the system not only depends on the trustworthiness of the measured (or generated) input data but also on the reliability of the simulation codes used. The main goal of this work is to improve the reliability of DSNE systems by adapting current state of the art methods from the domain of software reliability engineering to the case of atmospheric dispersion simulation codes. The current approach is based on the "design by diversity principle" for improving the reliability of simulation codes and the trustworthiness of simulation results. The effectiveness of the approach has been tested using the results of two test versions of the RODOS DSNE system used in several European countries.

  19. Developing an Intelligent Reservoir Flood Control Decision Support System through Integrating Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Chang, L. C.; Kao, I. F.; Tsai, F. H.; Hsu, H. C.; Yang, S. N.; Shen, H. Y.; Chang, F. J.

    2015-12-01

    Typhoons and storms hit Taiwan several times every year and cause serious flood disasters. Because the mountainous terrain and steep landform rapidly accelerate the speed of flood flow, rivers cannot be a stable source of water supply. Reservoirs become one of the most important and effective floodwater storage facilities. However, real-time operation for reservoir flood control is a continuous and instant decision-making process based on rules, laws, meteorological nowcast, in addition to the immediate rainfall and hydrological data. The achievement of reservoir flood control can effectively mitigate flood disasters and store floodwaters for future uses. In this study, we construct an intelligent decision support system for reservoir flood control through integrating different types of neural networks and the above information to solve this problem. This intelligent reservoir flood control decision support system includes three parts: typhoon track classification, flood forecast and adaptive water release models. This study used the self-organizing map (SOM) for typhoon track clustering, nonlinear autoregressive with exogenous inputs (NARX) for multi-step-ahead reservoir inflow prediction, and adaptive neuro-fuzzy inference system (ANFIS) for reservoir flood control. Before typhoons landfall, we can estimate the entire flood hydrogragh of reservoir inflow by using SOM and make a pre-release strategy and real-time reservoir flood operating by using ANFIS. In the meanwhile, NARX can be constantly used real-time five-hour-ahead inflow prediction for providing the newest flood information. The system has been successfully implemented Typhoons Trami (2013), Fitow (2013) and Matmo (2014) in Shihmen Reservoir.

  20. Design and implementation of a risk assessment module in a spatial decision support system

    NASA Astrophysics Data System (ADS)

    Zhang, Kaixi; van Westen, Cees; Bakker, Wim

    2014-05-01

    The spatial decision support system named 'Changes SDSS' is currently under development. The goal of this system is to analyze changing hydro-meteorological hazards and the effect of risk reduction alternatives to support decision makers in choosing the best alternatives. The risk assessment module within the system is to assess the current risk, analyze the risk after implementations of risk reduction alternatives, and analyze the risk in different future years when considering scenarios such as climate change, land use change and population growth. The objective of this work is to present the detailed design and implementation plan of the risk assessment module. The main challenges faced consist of how to shift the risk assessment from traditional desktop software to an open source web-based platform, the availability of input data and the inclusion of uncertainties in the risk analysis. The risk assessment module is developed using Ext JS library for the implementation of user interface on the client side, using Python for scripting, as well as PostGIS spatial functions for complex computations on the server side. The comprehensive consideration of the underlying uncertainties in input data can lead to a better quantification of risk assessment and a more reliable Changes SDSS, since the outputs of risk assessment module are the basis for decision making module within the system. The implementation of this module will contribute to the development of open source web-based modules for multi-hazard risk assessment in the future. This work is part of the "CHANGES SDSS" project, funded by the European Community's 7th Framework Program.

  1. A GIS-based decision support system for rainwater harvesting (RHADESS)

    NASA Astrophysics Data System (ADS)

    Mwenge Kahinda, J.; Taigbenu, A. E.; Sejamoholo, B. B. P.; Lillie, E. S. B.; Boroto, R. J.

    Rainwater harvesting (RWH) is an unconventional water source that is increasingly adopted in South Africa. Its implementation is promoted by non-governmental organisations and government programmes to alleviate temporal and spatial water scarcity for domestic, crop and livestock production and support the overall water resources management. Unreliable water supply is one of the elements central to the poverty level of rural population. As the potential of RWH to improve water access f