Clinical decision support systems for the practice of evidence-based medicine

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.

Figure 1

Architecture for the capture and use of literature-based and practice-based evidence, showing the distributed nature of the knowledge and functionality involved in the use of CDSSs to support evidence-based medicine. Vocabulary and interface standards are needed for inter-operation of the various systems.