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Selecting treatments: a decision theoretic approach

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  • Karl Claxton
  • Larry F. Lacey
  • Stephen G. Walker

Abstract

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.

Suggested Citation

  • Karl Claxton & Larry F. Lacey & Stephen G. Walker, 2000. "Selecting treatments: a decision theoretic approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(2), pages 211-225.
  • Handle: RePEc:bla:jorssa:v:163:y:2000:i:2:p:211-225
    DOI: 10.1111/1467-985X.00166
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    Cited by:

    1. Bernie J. O'Brien & Kirsten Gertsen & Andrew R. Willan & A. Faulkner, 2002. "Is there a kink in consumers' threshold value for cost‐effectiveness in health care?," Health Economics, John Wiley & Sons, Ltd., vol. 11(2), pages 175-180, March.
    2. Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & NegrI´n, M.A., 2010. "Optimal healthcare decisions: Comparing medical treatments on a cost-effectiveness basis," European Journal of Operational Research, Elsevier, vol. 204(1), pages 180-187, July.
    3. Andrew Willan & Simon Eckermann, 2012. "Value of Information and Pricing New Healthcare Interventions," PharmacoEconomics, Springer, vol. 30(6), pages 447-459, June.
    4. Francisco-José Polo & Miguel Negrín & Xavier Badía & Montse Roset, 2005. "Bayesian regression models for cost-effectiveness analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 6(1), pages 45-52, March.
    5. Andres Alban & Stephen E. Chick & Martin Forster, 2023. "Value-Based Clinical Trials: Selecting Recruitment Rates and Trial Lengths in Different Regulatory Contexts," Management Science, INFORMS, vol. 69(6), pages 3516-3535, June.
    6. Nicola J. Cooper & Keith R. Abrams & Alex J. Sutton & David Turner & Paul C. Lambert, 2003. "A Bayesian approach to Markov modelling in cost‐effectiveness analyses: application to taxane use in advanced breast cancer," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(3), pages 389-405, October.

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