Article ID: | iaor20121348 |
Volume: | 218 |
Issue: | 2 |
Start Page Number: | 538 |
End Page Number: | 547 |
Publication Date: | Apr 2012 |
Journal: | European Journal of Operational Research |
Authors: | Soyer Refik, Musal R Muzaffer, McCabe Christopher, Kharroubi Samer A |
Keywords: | statistics: inference, statistics: regression, programming: probabilistic |
In this paper we consider the health utility index mark II for quantifying and describing a population’s health related quality of life over health states composed of multiple attributes. This measure can be used for various purposes such as evaluating the severity of the effect of a disease or comparing different treatment methods. We present a Bayesian framework for population utility estimation and health policy evaluation by introducing a probabilistic interpretation of the multi‐attribute utility theory (MAUT) used in health economics. In doing so, our approach combines ideas from the MAUT and Bayesian statistics and provides an alternative method of modeling preferences and utility estimation.