Complementing the net benefit approach: A new framework for Bayesian cost-effectiveness analysis

Objectives: The aim 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 either effectiveness or cost present a high degree of asymmetry. Clinical variables often present these characteristics. Methods: In this study, we present a framework for cost-effectiveness analysis based on the whole posterior distribution of effectiveness and cost. Results: An application with real data is included to illustrate the analysis. 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. Conclusions: This framework overcomes limitations of the mean and offers complementary information for the decision maker.