Real world designs in economic evaluation. Bridging the gap between clinical research and policy-making

Abstract

This paper identifies the information that economic evaluation should provide to adequately inform policy-makers. First, policy-makers need cost-effectiveness information that is both internally and externally valid. The latter aspect is often ignored and refers to the relevance of the results of economic trials to the specific decision-making context of the policy-maker. Second, policy-makers, like purchasers of care, may want assessments of the overall budget and health impacts of adopting an intervention in a disease or treatment area. This requires more of an aggregate analysis than the current approaches to economic evaluation (which are typically individual-orientated). There are 3 main conceptual approaches to economic evaluation: the use of randomised controlled trials (RCTs), observational studies and modelling. The RCT can be considered as the gold standard in economic evaluation because of its high internal validity, but results should be interpreted with caution because of its low external validity. There a number of options to enhance external validity; of these, additional modelling and observational data seem to be the most promising. To address issues at the system level, disease modelling or public health modelling is suggested. A 3-step approach, comprising successive assessment of internal validity, external validity (real world relevance) and net impact at the system level, can enhance the informative value of economic analyses. For example, this approach has been used to assess the informative value to decision-makers of an RCT in benign prostatic hyperplasia. The analysis emphasised the feasibility and importance of additional modelling beyond the results from an RCT-based economic analysis and provided important information of relevance for policy-making. Because of the need to increase the real world relevance of pharmacoeconomic analyses, there is potentially a large role for modelling in economic evaluation; however, in order to enhance its credibility, more attention should be paid to validity aspects.