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Affiliations of the authors: University of California–San Francisco, California (IS); Oregon Health and Science University, Portland, Oregon (PG); Harvard Medical School (RAG); McMaster University, Hamilton, Ontario, Canada (RBH); Yale University School of Medicine, Hamden, Connecticut (BK); Johns Hopkins University School of Medicine, Baltimore, Maryland (HL); Palo Alto Medical Foundation, Palo Alto, California (PCT).
Correspondence and reprints: Ida Sim, MD, PhD, Department of Medicine and Program in Biological and Medical Informatics, University of California–San Francisco, 400 Parnassus Avenue, Room A-405, San Francisco, CA 94143-0320; e-mail: <sim{at}medicine.ucsf.edu>.
Received for publication: 02/19/01; accepted for publication: 07/11/01.
Background: The use of clinical decision support systems to facilitate the practice of evidence-based medicine promises to substantially improve health care quality.
Objective: To describe, on the basis of the proceedings of the Evidence and Decision Support track at the 2000 AMIA Spring Symposium, the research and policy challenges for capturing research and practice-based evidence in machine-interpretable repositories, and to present recommendations for accelerating the development and adoption of clinical decision support systems for evidence-based medicine.
Results: The recommendations fall into five broad areas—capture literature-based and practice-based evidence in machine-interpretable knowledge bases; develop maintainable technical and methodological foundations for computer-based decision support; evaluate the clinical effects and costs of clinical decision support systems and the ways clinical decision support systems affect and are affected by professional and organizational practices; identify and disseminate best practices for work flow–sensitive implementations of clinical decision support systems; and establish public policies that provide incentives for implementing clinical decision support systems to improve health care quality.
Conclusions: Although the promise of clinical decision support system–facilitated evidence-based medicine is strong, substantial work remains to be done to realize the potential benefits.
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