Representing uncertainty: the role of cost‐effectiveness acceptability curves

TLDR

Decision‑making in health care is performed under uncertainty about intervention effectiveness and costs, and the cost‑effectiveness acceptability curve (CEAC) has been proposed as a superior alternative to confidence‑interval estimation for incremental cost‑effectiveness ratios, yet it remains underused in economic evaluation. The authors examine the relationship between CEACs and health‑care decision‑making, introduce the cost‑effectiveness frontier concept, and clarify how these tools can be applied when evaluating multiple interventions. They analyze the link between CEACs and decision‑making, propose the frontier concept, and explain its application to multi‑intervention scenarios. The authors expect that these insights will encourage broader adoption of CEACs and related decision‑analysis techniques.

Abstract

Decision-making in health care is inevitably undertaken in a context of uncertainty concerning the effectiveness and costs of health care interventions and programmes. One method that has been suggested to represent this uncertainty is the cost-effectiveness acceptability curve. This technique, which directly addresses the decision-making problem, has advantages over confidence interval estimation for incremental cost-effectiveness ratios. However, despite these advantages, cost-effectiveness acceptability curves have yet to be widely adopted within the field of economic evaluation of health care technologies. In this paper we consider the relationship between cost-effectiveness acceptability curves and decision-making in health care, suggest the introduction of a new concept more relevant to decision-making, that of the cost-effectiveness frontier, and clarify the use of these techniques when considering decisions involving multiple interventions. We hope that as a result we can encourage the greater use of these techniques.