title: Is expected utility theory normative for medical decision making?
abstract: Expected utility theory is felt by its proponents to be a normative theory of decision making under uncertainty. The theory starts with some simple axioms that are held to be rules that any rational person would follow. It can be shown that if one adheres to these axioms, a numerical quantity, generally referred to as utility, can be assigned to each possible outcome, with the preferred course of action being that which has the highest expected utility. One of these axioms, the independence principle, is controversial, and is frequently violated in experimental situations. Proponents of the theory hold that these violations are irrational. The independence principle is simply an axiom dictating consistency among preferences, in that it dictates that a rational agent should hold a specified preference given another stated preference. When applied to preferences between lotteries, the independence principle can be demonstrated to be a rule that is followed only when preferences are formed in a particular way. The logic of expected utility theory is that this demonstration proves that preferences should be formed in this way. An alternative interpretation is that this demonstrates that the independence principle is not a valid general rule of consistency, but in particular, is a rule that must be followed if one is to consistently apply the decision rule "choose the lottery that has the highest expected utility." This decision rule must be justified on its own terms as a valid rule of rationality by demonstration that violation would lead to decisions that conflict with the decision maker's goals. This rule does not appear to be suitable for medical decisions because often these are one-time decisions in which expectation, a long-run property of a random variable, would not seem to be applicable. This is particularly true for those decisions involving a non-trivial risk of death.
authors.affiliation: Division of Clinical Decision Making, Department of Medicine, New England Medical Center, Tufts University School of Medicine, Boston, Massachusetts, USA.
authors.forename: B J
authors.initials: BJ
authors.lastname: Cohen
mesh_terms: D002755:Choice Behavior; D003362:Cost-Benefit Analysis; D003657:Decision Making; D003661:Decision Support Techniques; D006040:Goals; D009042:Motivation; D011336:Probability; D015203:Reproducibility of Results; D012307:Risk Factors; D012945:Social Values; D016896:Treatment Outcome