• R L Coleman.
• Memorial Hospital, Meriden, Connecticut.
• QRB Qual Rev Bull. 1989 Dec 1;15(12):383-91.

AbstractNow that major efforts are being made to develop clinical indicators, it is also imperative that participants in quality assurance programs have useful mechanisms to review data derived on the basis of these indicators. The decision tree is one means of conceptualizing clinical problems in a manner that can enhance both the development and review of clinical indicators. The decision tree can assist in presentation of clinical decisions and outcomes. When applied to specific clinical indicator data, such as a failure to order diagnostic tests, or to a trend of failure to follow a standard protocol for admissions, decision trees and decision analysis can assist in the review of quality and appropriateness of care. Both individual cases and trends lend themselves to decision analysis, which can help determine the decisions likely to be appropriate. When numerical data are available, decision analysis can provide quantitative evaluations of clinical and quality assurance data.

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