Net Health Benefits : A New Framework for the Analysis of Uncertainty in Cost-Effectiveness Analysis

Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.

To address controversies in the applications of cost-effectiveness analysis, we investigate the principles underlying the technique and discuss the implications for the evaluation of medical interventions. Using a standard von Neumann-Morgenstern utility framework, we show how a cost-effectiveness criterion can be derived to guide resource allocation decisions, and how it varies with age, gender, income level, and risk aversion. Although cost-effectiveness analysis can be a useful and powerful tool for resource allocation decisions, a uniform cost-effectiveness criterion that is applied to a heterogeneous population level is unlikely to yield Pareto-optimal resource allocations.