Décision médicale et probabilités imprécises
Usually medical decisions (diagnosis, treatment, prevention etc.) are analyzed under the assumption that the probabilities of various health states or the outcomes from different medical decisions are unique and perfectly known. Preferences are then represented by the expected utility model. In reality however, for most medical decisions, the available information on probabilities is imprecise and can be represented as an interval of values. The purpose of this paper is to illustrate the impact of this type of ambiguity on treatment and prevention decisions. To achieve this goal we use a decision model where preferences depend on one side, on attitude towards ambiguity, represented by a Hurwicz pessimism-optimism and on the other side on attitude towards risk, represented by a standard utility function. Classification JEL : I12, D81
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