Physicians have developed a number of implicit and explicit approaches to complex medical decisions. Decision analysis is an explicit, quantitative method of clinical decision making that involves the separation of the probabilities of events from their relative values, or utilities. Its use can help physicians make difficult choices in a manner that promotes true patient participation. Decision analysis also provides a framework for the incorporation of data from multiple sources and for the assessment of the impact of uncertain data on the final decision. Although this approach is imperfect, it represents a significant advance in clinical decision making.
"In this paper, we use a broad definition for utilities associated with clinical outcomes in the manner proposed by Pauker & Kassirer (1975, 1980), who followed its usage according to principles of classic decision analysis (Weinstein et al. 1980; Zarin & Pauker 1984). The value of clinical outcomes can be expressed in different units, such as length of life, morbidity or mortality rates, absence of pain, cost, or the strength of individual or societal preference for a given outcome (Pauker & Kassirer 1975, 1980; Hozo & Djulbegovic 1999; Djulbegovic et al. 2000a). "
[Show abstract][Hide abstract] ABSTRACT: Randomized controlled trials (RCTs) have emerged as the most reliable method of assessing the effects of health care interventions in clinical medicine. However, RCTs should be undertaken only if there is substantial uncertainty about which of the trial treatments would benefit a patient most. The purpose of this study is to determine the degree of uncertainty in a research hypothesis before it can empirically be tested in an RCT.
We integrated arguments from three independent lines of research - on ethics, principles of the design and conduct of clinical trials, and medical decision making - to develop a decision model to help solve the dilemma of under which circumstances innovative treatments should be tested in an RCT.
We showed that RCTs are the preferable option to resolve uncertainties about competing treatment alternatives whenever we desire reliable, undisputed, high-quality evidence with a low likelihood of false-positive or false-negative results.
When the expected benefit:risk ratio of a new treatment is small, an RCT is justified to resolve uncertainties over a wide range of prior belief (e.g. 10-90) in the accuracy of the research hypothesis. Randomized controlled trials represent the best means for resolving uncertainties about health care interventions.
Journal of Evaluation in Clinical Practice 06/2002; 8(2):269-76. DOI:10.1046/j.1365-2753.2002.00347.x · 1.08 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Two distinct views of the nature of clinical judgment are identified and contrasted. The dominant view that clinical judgment is a fully explicit process is compared to the relatively neglected view that tacit knowledge plays a substantial role in the clinician's mental operations. The tacit dimension of medical thinking is explored at length. The discussion suggests severe limits when applying decision analysis, expert systems, and computer-aided cost-benefit review to medicine. The goals and practices of postgraduate medical education are also examined from this perspective, as are various other implications for the clinician. The paper concludes that it is valuable to explore the nature of medical thinking in order to improve clinical practice and education. Such explorations should, however, take cognizance of the often overlooked tacit dimension of clinical judgment. Possible constraints on the medical applicability of both formal expert systems and heavily didactic instructional programs are considered.
The Yale journal of biology and medicine 11/1989; 63(1):47-61.
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