Complementing the Net Benefit approach: A new framework for Bayesian cost--effectiveness analysis

Presenter: Miguel Negrín, University of Las Palmas de G.C.

Abstract

The general aim and rationale of cost-effectiveness analysis is to maximize health benefits from a given budget, taking a societal perspective. Consequently, the comparison of alternative treatments or technologies is solely based on their expected effectiveness and cost. However the expectation, or mean, poses important limitations as it might be a poor summary of the underlying distribution, for instance when the effectiveness is a categorical variable, or when the distributions of effectiveness or cost present a high degree of asymmetry. Clinical variables often present these characteristics.

In this paper we present a framework for cost-effectiveness analysis based on the whole posterior distribution of effectiveness and cost, conditional on the data. It overcomes some limitations of the mean and offers complementary information for the decision maker. Decision-making measures such as the incremental cost-effectiveness ratio, incremental net-benefit and cost-effectiveness acceptability curves, can also be defined under the new framework. An application with real data is included to illustrate the analysis.