The sampling information for the cost-effectiveness analysis typically comes from different health care centers, and, as far as we know, it is taken for granted that the distribution of the cost and the effectiveness does not vary across centers. We argue that this assumption is unrealistic, and prove that to not consider the sample heterogeneity will typically give misleading results. Consequently, a cost-effectiveness procedure for heterogeneous samples is here proposed. The proposed cost-effectiveness procedure consists of a Bayesian clustering to measure the sample heterogeneity, and a meta-analysis to account for the specific clustering structure of the data. Examples with real data illustrate this methodology for normal and lognormal models, and the results are compared with those we would obtain if homogeneity of the samples is assumed. 
Cost-effectiveness analysis for heterogeneous samples