Clinical decision support systems for the practice of evidence-based medicine
Open accessAbstract
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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Early medical informatics CDS systems used deterministic logic derived directly from curated guidelines, making them intrinsically auditable.
“Because these systems used deterministic logic derived directly from curated guidelines, they were intrinsically auditable: the chain from input to recommendation could be reconstructed, and the underlying rules could be manually inspected.”
From An auditable and source-verified framework for clinical AI decision support: integrating retrieval-augmented generation with data provenance (2026) · cites this paper as Sim et al., 2001
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“Initial informatics initiatives in Clinical Decision Support (CDS) reflected this notion: Sim et al. (2001) advocated for the incorporation of both literature-derived and practice-derived data into machine-interpretable knowledge bases to facilitate decision-making (Sim et al., 2001).”
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- Authors
- Sim, I., Gorman, P., Greenes, R. A., Haynes, R. B., Kaplan, B., Lehmann, H., & Tang, P. C.
- Affiliations
- Palo Alto Medical Foundation (US)
- Corresponding author
- Sim, I.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2001-11-01
- Volume
- 8
- Issue
- 6
- Pages
- 527-534
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC130063
- OpenAlex
- W2098044946
- Cited by
- 732
- References
- 4
- Citations by year
- 2026: 30 · 2025: 43 · 2024: 54 · 2023: 48 · 2022: 45 · 2021: 42 · 2020: 32 · 2019: 35 · 2018: 34 · 2017: 30 · 2016: 31 · 2015: 33 · 2014: 28 · 2013: 25 · 2012: 28
- FWCI
- 39.89
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. National Library of Medicine (LM 06780, R01LM006780)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › General Health Professions › Health Sciences Research and Education
- Keywords
- clinical decision support systems, evidence-based medicine, practice-based evidence, clinical workflow integration, quality of care
- MeSH terms
- Decision Support Techniques, Humans, Medical Records Systems, Computerized, Practice Guidelines as Topic, Evidence-Based Medicine, Decision Support Systems, Clinical
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