Cost-effectiveness profiles with an expanding treatment population

Abstract

In trying to identify the therapeutic impact of a drug, clinical trials eliminate potentially confounding factors such as comorbidities, poor compliance and treatment errors in diagnosis, dosing, and drug interactions. Elimination of these variables means that attempts to use clinical data as the basis for predicting relative cost-effectiveness are fraught with difficulties. In this article a theoretical framework is proposed, which, for a single drug intervention, examines the relationship between assumed patterns of clinical effectiveness, costs of drug delivery, and the proportion of the prospective patient population being treated. Cost-effectiveness profiles are generated to represent both usual-treatment situations and situations where interventions to reduce misdiagnoses, adverse events, and noncompliance attempt to push clinical effectiveness to a maximum (given the existence of comorbidities). Without data describing effectiveness and cost profiles, and unless strict assumptions are made as to effectiveness and cost functions, profiles of cost-effectiveness cannot be predicted.