Clinical Decision Support Systems for the Practice of Evidence-based Medicine
- 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 19 February 2001
- Accepted 11 July 2001
Abstract
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.
Footnotes
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This work was supported in part by a United States Presidential Early Career Award for Scientists and Engineers awarded to Dr. Sim and administered through grant LM-06780 of the National Library of Medicine.
