A decision-theoretic framework for the application of cost-effectiveness analysis in regulatory processes


Cost-effectiveness analysis (CEA) represents the most important toolin the health economics literature to quantify and qualify the reasoningbehind the optimal decision process in terms of the allocation ofresources to a given health intervention. However, the practicalapplication of CEA in the regulatory process is often limited bysome critical barriers, and decisions in clinical practice are frequentlyinfluenced by factors that do not contribute to efficient resourceallocation, leading to inappropriate drug prescription and utilization.Moreover, most of the time there is uncertainty about the real cost-effectivenessprofile of an innovative intervention, with the consequence thatit is usually impossible to obtain an immediate and perfect substitutionof a product with another having a better cost-effectiveness ratio.The objective of this article is to propose a rational approach toCEA within regulatory processes, basing our analysis in a Bayesiandecision-theoretic framework and proposing an extension of the applicationof well known tools (such as the expected value of information) tosuch cases. The regulator can use these tools to identify the economicvalue of reducing the uncertainty surrounding the cost-effectivenessprofile of the several alternatives. This value can be compared withthe one that is generated by the actual market share of the differenttreatment options: one that is the most cost effective and othersin the same therapeutic category that, despite producing clinicalbenefits, are less cost effective.

Gianluca Baio
Gianluca Baio
Professor of Statistics and Health Economics