In recent years, considerable attention has been devoted to the development of statistical methods for the analysis of uncertainty in cost-effectiveness (CE) analysis, with a focus on situations in which the analyst has patient-level data on the costs and health effects of alternative interventions. To date, discussions have focused almost exclusively on addressing the practical challenges involved in estimating confidence intervals for CE ratios. However, the general approach of using confidence intervals to convey information about uncertainty around CE ratio estimates suffers from theoretical limitations that render it inappropriate in many situations. The authors present an alternative framework for analyzing uncertainty in the economic evaluation of health interventions (the "net health benefits" approach) that is more broadly applicable and that avoids some problems of prior methods. This approach offers several practical and theoretical advantages over the analysis of CE ratios, is straightforward to apply, and highlights some important principles in the theoretical underpinnings of CE analysis.