Trusting the Results of Model-Based Economic Analyses: Is there a Pragmatic Validation Solution?
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Models have become a nearly essential component of health technology assessment. This is because the efficacy and safety data available from clinical trials are insufficient to provide the required estimates of impact of new interventions over long periods of time and for other populations and subgroups. Despite more than five decades of use of these decision-analytic models, decision makers are still often presented with poorly validated models and thus trust in their results is impaired. Among the reasons for this vexing situation are the artificial nature of the models, impairing their validation against observable data, the complexity in their formulation and implementation, the lack of data against which to validate the model results, and the challenges of short timelines and insufficient resources. This article addresses this crucial problem of achieving models that produce results that can be trusted and the resulting requirements for validation and transparency, areas where our field is currently deficient. Based on their differing perspectives and experiences, the authors characterize the situation and outline the requirements for improvement and pragmatic solutions to the problem of inadequate validation.
The authors thank Isaac Coro Ramos, Pepijn Vemer, George A.K van Voorn, Maiwenn J. AI, Talitha L. Feenstra, and Chloé Herpin for their useful comments and suggestions.
SG drafted Sects. 2 and 3.1; MS drafted Sect. 3.2; JM drafted Sect. 3.3; and JJC reviewed these materials and integrated them into the paper. All authors participated in writing and editing Sects. 1, 2, and 4.
Compliance with Ethical Standards
No funding was received for the preparation of this article.
Conflict of interest
Salah Ghabri and Matt Stevenson have no conflicts of interest that are directly relevant to the contents of this article. Jörgen Möller and J. Jaime Caro are employed by Evidera, a company that provides consulting and other research services to pharmaceutical, device, government, and non-government organizations. The opinions expressed in this article are those of the authors and do not necessarily represent the views of their institutions.
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