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      To Share is Human! Advancing Evidence into Practice through a National Repository of Interoperable Clinical Decision Support

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          Background  Healthcare systems devote substantial resources to the development of clinical decision support (CDS) largely independently. The process of translating evidence-based practice into useful and effective CDS may be more efficient and less duplicative if healthcare systems shared knowledge about the translation, including workflow considerations, key assumptions made during the translation process, and technical details.

          Objective  Describe how a national repository of CDS can serve as a public resource for healthcare systems, academic researchers, and informaticists seeking to share and reuse CDS knowledge resources or “artifacts.”

          Methods  In 2016, the Agency for Healthcare Research and Quality (AHRQ) launched CDS Connect as a public, web-based platform for authoring and sharing CDS knowledge artifacts. Researchers evaluated early use and impact of the platform by collecting user experiences of AHRQ-sponsored and community-led dissemination efforts and through quantitative/qualitative analysis of site metrics. Efforts are ongoing to quantify efficiencies gained by healthcare systems that leverage shared, interoperable CDS artifacts rather than developing similar CDS de novo and in isolation.

          Results  Federal agencies, academic institutions, and others have contributed over 50 entries to CDS Connect for sharing and dissemination. Analysis indicates shareable CDS resources reduce team sizes and the number of tasks and time required to design, develop, and deploy CDS. However, the platform needs further optimization to address sociotechnical challenges. Benefits of sharing include inspiring others to undertake similar CDS projects, identifying external collaborators, and improving CDS artifacts as a result of feedback. Organizations are adapting content available through the platform for continued research, innovation, and local implementations.

          Conclusion  CDS Connect has provided a functional platform where CDS developers are actively sharing their work. CDS sharing may lead to improved implementation efficiency through numerous pathways, and further research is ongoing to quantify efficiencies gained.

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          Most cited references 10

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          Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality.

          While evidence-based medicine has increasingly broad-based support in health care, it remains difficult to get physicians to actually practice it. Across most domains in medicine, practice has lagged behind knowledge by at least several years. The authors believe that the key tools for closing this gap will be information systems that provide decision support to users at the time they make decisions, which should result in improved quality of care. Furthermore, providers make many errors, and clinical decision support can be useful for finding and preventing such errors. Over the last eight years the authors have implemented and studied the impact of decision support across a broad array of domains and have found a number of common elements important to success. The goal of this report is to discuss these lessons learned in the interest of informing the efforts of others working to make the practice of evidence-based medicine a reality.
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            A multi-layered framework for disseminating knowledge for computer-based decision support.

            There are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patient data representations, and of workflows. We have developed a multi-layered knowledge representation framework for structuring guideline recommendations for implementation in a variety of CDS contexts. In this framework, guideline recommendations are increasingly structured through four layers, successively transforming a narrative text recommendation into input for a CDS system. We have used this framework to implement rules for a CDS service based on three guidelines. We also conducted a preliminary evaluation, where we asked CDS experts at four institutions to rate the implementability of six recommendations from the three guidelines. The experience in using the framework and the preliminary evaluation indicate that this approach has promise in creating structured knowledge, to implement in CDS systems, that is usable across organizations.
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              The clinical decision support consortium.

              Clinical decision support (CDS) can impact the outcomes of care when used at the point of care in electronic medical records (EMR). CDS has been shown to increase quality and patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Systematic reviews have shown that CDS can be useful across a variety of clinical purposes and topics. Despite broad national policy objectives to increase EMR adoption in the US, current adoption of advanced clinical decision support is limited due to a variety of reasons, including: limited implementation of EMR, CPOE, PHR, etc., difficulty developing clinical practice guidelines ready for implementation in EMR, lack of standards, absence of a central repository or knowledge resource, poor support for CDS in commercial EMRs, challenges in integrating CDS into the clinical workflow, and limited understanding of organizational and cultural issues relating to clinical decision support. To better understand and overcome these barriers, and accelerate the translation of clinical practice guideline knowledge into CDS in EMRs, the CDS Consortium is established 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 EHR technology platforms.

                Author and article information

                Appl Clin Inform
                Appl Clin Inform
                Applied Clinical Informatics
                Georg Thieme Verlag KG (Stuttgart · New York )
                January 2020
                12 February 2020
                : 11
                : 1
                : 112-121
                [1 ]Division of Digital Healthcare Research, Center for Evidence and Practice Improvement, Agency for Healthcare Research and Quality, Rockville, Maryland, United States
                [2 ]Clinical Quality and Informatics, Health Transformation Technical Center, The MITRE Corporation, Atlanta, Georgia, United States
                [3 ]Centers for Disease Control and Prevention, Atlanta, Georgia, United States
                [4 ]Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
                [5 ]Department of Biomedical Informatics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
                [6 ]ECRI Guidelines Trust, ECRI Institute, Plymouth Meeting, Pennsylvania, United States
                [7 ]National Center for Human Factors in Healthcare, MedStar Health, Washington, District of Columbia, United States
                [8 ]Georgetown University School of Medicine, Washington, District of Columbia, United States
                Author notes
                Address for correspondence Edwin A. Lomotan, MD Agency for Healthcare Research and Quality Rockville, MarylandUnited States edwin.lomotan@ 123456ahrq.hhs.gov

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.

                Funded by: AHRQ
                Award ID: HHSA290201600001U
                Funded by: AHRQ
                Award ID: HHSP233201500022I/AHRQ216963
                Funding This work has been supported by AHRQ contracts HHSA290201600001U and HHSP233201500022I/AHRQ216963.
                AMIA CIC 2019


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