Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48774
Title: Bayesian regression models for cost-effectiveness analysis
Authors: Polo, Francisco José Vázquez 
Negrín, Miguel 
Badía, Xavier
Roset, Montse
Issue Date: 2005
Publisher: 1618-7598
Journal: European Journal of Health Economics 
Abstract: Recent studies have shown how cost-effectiveness analysis can be undertaken in a regression framework. This contribution explores the use of practical regression models for estimating cost-effectiveness from a Bayesian perspective. Two different Bayesian models are described. The first considers the outcome measure to be a quantitative variable. In the second model the individual outcome measure is a binary variable with value 1 if any objective has been achieved. We describe the implementation of the model using data from a trial that compares two highly active antiretroviral therapies in HIV asymptomatic patients. Data on direct cost and data effectiveness (percentage of patients with undetectable viral load and quality of life) were recorded. If we consider the quality of life as an effectiveness measure, the new treatment is preferred for a willingness to pay more than 142.3 € for an increase in the quality of life. For illustrative purposes, if we compare the results with an analogous model that does not include covariates, the critical value becomes 247.4 €. For the binary measure of effectiveness the control treatment dominates the new treatment. © Springer Medizin Verlag 2004.
URI: http://hdl.handle.net/10553/48774
ISSN: 1618-7598
DOI: 10.1007/s10198-004-0256-z
Source: European Journal of Health Economics[ISSN 1618-7598],v. 6, p. 45-52
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