title: A model for medical decision making and problem solving.
abstract: Clinicians confront the classical problem of decision making under uncertainty, but a universal procedure by which they deal with this situation, both in diagnosis and therapy, can be defined. This consists in the choice of a specific course of action from available alternatives so as to reduce uncertainty. Formal analysis evidences that the expected value of this process depends on the a priori probabilities confronted, the discriminatory power of the action chosen, and the values and costs associated with possible outcomes. Clinical problem-solving represents the construction of a systematic strategy from multiple decisional building blocks. Depending on the level of uncertainty the physicians attach to their working hypothesis, they can choose among at least four prototype strategies: pattern recognition, the hypothetico-deductive process, arborization, and exhaustion. However, the resolution of real-life problems can involve a combination of these game plans. Formal analysis of each strategy permits definition of its appropriate a priori probabilities, action characteristics, and cost implications.
authors.affiliation: Department of Pathology, George Washington University Medical Center, Washington, DC 20037, USA.
authors.forename: M
authors.initials: M
authors.lastname: Werner
mesh_terms: D001185:Artificial Intelligence; D003661:Decision Support Techniques; D003662:Decision Theory; D003933:Diagnosis