Considerations for enhancing the credibility of health economic models: a review

Abstract: Health economic evaluations address resource allocation problems and have been widely used in health technology assessment for adopting new interventions. Numerous countries and international societies have developed economic evaluation guidelines. There is consensus among the guidelines on several key principles including the type of analysis [cost-utility analysis (CUA) preferred], time horizon of the analysis (long enough required), health outcome [the quality-adjusted life-year (QALY) preferred], and sensitivity analysis (various analyses recommended). Long-term CUAs which aim to capture all intended effects and unintended side effects of interventions, ideally over the lifetime horizon, are generally recommended. However, strict application of these recommendations could introduce greater uncertainty in economic evaluation results. We examine various guidelines to distill the commonalities and suggest more nuanced approaches for improving the presentation of the credibility of economic model results (i.e., the likelihood of cost-effectiveness results being trusted). We propose several considerations for enhancing the credibility of economic evaluation conclusions. First, when it is challenging to make a reliable projection of long-term outcomes, health economists may limit the time horizon to a shorter time supported by the available data. Second, the economic evaluation can be conducted using natural units of health when high-quality utility data are not available. Third, health economists need to understand whether the available data can support complex disease models so they can choose a proper level of model complexity. Fourth, health economists need to specify factors that are associated with health benefits, and to control remaining factors (e.g., background mortality and baseline characteristics). Fifth, instead of focusing on selecting fitted parameters from real-world data, economic evaluations should use the best quality clinical evidence for their key model inputs. In conclusion, economic evaluations should aim to produce the most credible cost-effectiveness estimates by adhering to rigorous methodological standards and by adapting recommendations to suit the specific context. Health economists should clearly identify and report potential biases, assumptions, the quality of evidence informing key model parameters, and sources of uncertainty to ensure the credibility of the cost-effectiveness results and their use in decision and policy making.