The Case for Stratified Cost-Effectiveness Analysis by Baseline Health-Related QOL: Theory and Sensitivity Analysis

The purpose of this paper is to argue that systematic data heterogeneity exists when the objective of pharmacotherapy is improved health-related quality of life (HR-QOL), and that the pharmacotherapy's cost effectiveness will vary inversely with the patient's baseline HR-QOL (BHR-QOL), the patient's HR-QOL just prior to treatment. It is argued that when improved HR-QOL is the primary objective of a pharmacotherapy, the magnitude of the HR-QOL response to treatment may be negatively correlated with BHR-QOL and that the net cost of the pharmacotherapy may be positively correlated with BHR-QOL. It is also argued that the value placed on a given increment in HR-QOL declines as BHR-QOL rises. The case for _sample stratification by BHR-QOL, _and for conducting cost- effectiveness analysis (CEA) at the stratum level, is illustrated with numerical examples using hypothetical data and the incremental net monetary benefit (INMB) criterion. Sensitivity analysis is used to explore the response of the INMB at the stratum level to different degrees of data heterogeneity across the BHR-QOL strata. This paper demonstrates that because of cumulative effects, even relatively minor data heterogeneity related to BHR-QOL results in substantial differences in the cost effectiveness of treatments across BHR-QOL strata. CEA stratified by BHR-QOL enables a more efficient and equitable allocation of public healthcare funding than standard cost-effectiveness screening of pharmaceutical drugs based on full-sample averages.