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Selecting treatments: a decision theoretic approach
Author(s) -
Claxton Karl,
Lacey Larry F.,
Walker Stephen G.
Publication year - 2000
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/1467-985x.00166
Subject(s) - bayesian probability , decision theory , expected utility hypothesis , decision rule , decision analysis , function (biology) , population , optimal decision , cost–benefit analysis , actuarial science , risk analysis (engineering) , computer science , mathematical optimization , economics , mathematics , mathematical economics , decision tree , medicine , artificial intelligence , microeconomics , ecology , environmental health , evolutionary biology , biology
The paper looks at the problem of comparing two treatments, for a particular population of patients, where one is the current standard treatment and the other a possible alternative under investigation. With limited (finite) financial resources the decision whether to replace one by the other will not be based on health benefits alone. This motivates an economic evaluation of the two competing treatments where the cost of any gain in health benefit is scrutinized; it is whether this cost is acceptable to the relevant authorities which decides whether the new treatment can become the standard. We adopt a Bayesian decision theoretic framework in which a utility function is introduced describing the consequences of making a particular decision when the true state of nature is expressed via an unknown parameter θ (this parameter denotes cost, effectiveness, etc.). The treatment providing the maximum posterior expected utility summarizes the decision rule, expectations taken over the posterior distribution of the parameter θ.