UC Davis

Cost-effectiveness analysis (CEA) is a method for evaluating the outcomes and costs of competing strategies designed to improve health, and has been applied to a variety of different scientific fields. Yet there are inherent complexities in cost estimation and CEA from statistical perspectives (e.g., skewness, bidimensionality, and censoring). The incremental cost-effectiveness ratio that represents the additional cost per unit of outcome gained by a new strategy has served as the most widely accepted methodology in the CEA. In this article, we call for expanded perspectives and reporting standards reflecting a more comprehensive analysis that can elucidate different aspects of available data. Specifically, we propose that mean- and median-based incremental cost-effectiveness ratios and average cost-effectiveness ratios be reported together, along with relevant summary and inferential statistics, as complementary measures for informed decision making.