STATISTICAL-METHODS FOR COST-EFFECTIVENESS ANALYSES

A statistical framework is presented for examining cost and effect dat a on competing interventions obtained from an RCT or from an observati onal study. Parameters of the joint distribution of costs and effects or a regression function linking costs and effects are used to define cost-effectiveness (c-e) measures. Several new c-e measures are propos ed that utilize the linkage between costs and effects on the patient l evel. These measures reflect perspectives that are different from thos e of the commonly used measures, such as the ratio of expected cost to expected effect, and they can lead to different relative rankings of the interventions. The cost-effectiveness of interventions are assesse d statistically in a two stage procedure that first eliminates clearly inferior interventions. Members of the remaining admissible set are t hen rank ordered according to a c-e preference measure. Statistical te chniques, particularly in the multivariate normal case, are given for several commonly used c-e measures. These techniques provide methods f or obtaining confidence intervals, for testing the hypothesis of admis sibility and for the equality of interventions, and for ranking interv entions. The ideas are illustrated for a hypothetical clinical trial o f antipsychotic agents for community-based persons with mental illness . (C) Elsevier Science Inc.