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J Biomed Inform. 2018 Feb;78:134-143. doi: 10.1016/j.jbi.2017.12.005. Epub 2017 Dec 12.

Clinical decision support models and frameworks: Seeking to address research issues underlying implementation successes and failures.

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Arizona State University, Scottsdale, AZ, USA; Mayo Clinic, Scottsdale, AZ, USA. Electronic address:
Partners Healthcare and Harvard Medical School, Boston, MA, USA.
University of Utah, Salt Lake City, UT, USA.
Apervita, Inc., Chicago, IL, USA; Harvard TH Chan School of Public Health, Boston, USA.
TMIT Consulting, LLC, Naples, FL, USA.
Ben Gurion University of the Negev, Beer-Sheba, Israel.


Computer-based clinical decision support (CDS) has been pursued for more than five decades. Despite notable accomplishments and successes, wide adoption and broad use of CDS in clinical practice has not been achieved. Many issues have been identified as being partially responsible for the relatively slow adoption and lack of impact, including deficiencies in leadership, recognition of purpose, understanding of human interaction and workflow implications of CDS, cognitive models of the role of CDS, and proprietary implementations with limited interoperability and sharing. To address limitations, many approaches have been proposed and evaluated, drawing on theoretical frameworks, as well as management, technical and other disciplines and experiences. It seems clear, because of the multiple perspectives involved, that no single model or framework is adequate to encompass these challenges. This Viewpoint paper seeks to review the various foci of CDS and to identify aspects in which theoretical models and frameworks for CDS have been explored or could be explored and where they might be expected to be most useful.


Clinical decision support; Knowledge models; Knowledge representation

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