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Optimal healthcare decisions: The importance of the covariates in cost–effectiveness analysis

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Listed:
  • Moreno, Elías
  • Girón, F.J.
  • Vázquez-Polo, F.J.
  • Negrín, M.A.

Abstract

This paper deals with the decision problem of choosing an optimal medical treatment, among M possible candidates, when the states of nature are the net benefit of the treatments, and regression models for the treatment cost and effectiveness are assumed. In this setting a crucial step in the analysis is the construction of the population subgroups sharing characteristics specified by the covariates, so that optimal decisions are now not for the whole population of patients but for patient population subgroups.

Suggested Citation

  • Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & Negrín, M.A., 2012. "Optimal healthcare decisions: The importance of the covariates in cost–effectiveness analysis," European Journal of Operational Research, Elsevier, vol. 218(2), pages 512-522.
  • Handle: RePEc:eee:ejores:v:218:y:2012:i:2:p:512-522
    DOI: 10.1016/j.ejor.2011.10.030
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    16. Elías Moreno & F. Girón, 2008. "Comparison of Bayesian objective procedures for variable selection in linear regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 491-492, November.
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    Cited by:

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    2. Theodoros Mantopoulos & Paul M. Mitchell & Nicky J. Welton & Richard McManus & Lazaros Andronis, 2016. "Choice of statistical model for cost-effectiveness analysis and covariate adjustment: empirical application of prominent models and assessment of their results," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 927-938, November.
    3. Moreno, E. & Girón, F.J. & Martínez, M.L. & Vázquez-Polo, F.J. & Negrín, M.A., 2013. "Optimal treatments in cost-effectiveness analysis in the presence of covariates: Improving patient subgroup definition," European Journal of Operational Research, Elsevier, vol. 226(1), pages 173-182.
    4. Aquila, Giancarlo & de Oliveira Pamplona, Edson & Ferreira Filho, José Alberto & da Silva, Antônio Sergio & de Azevedo Mataveli, João Victor & Correa, João Ederson & de Maria, Mateus Sanches & Garcia,, 2019. "Quantitative regulatory impact analysis: Experience of regulatory agencies in Brazil," Utilities Policy, Elsevier, vol. 59(C), pages 1-1.

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