Appropriate Evidence Sources for Populating Decision Analytic Models within Health Technology Assessment (HTA)

Abstract

Background. An increasing number of evidence sources are relevant for populating decision analytic models. What is needed is detailed methodological advice on which type of data is to be used for what type of model parameter. Purpose. We aim to identify standards in health technology assessment manuals and economic (modeling) guidelines on appropriate evidence sources and on the role different types of data play within a model. Methods. Documents were identified via a call among members of the International Network of Agencies for Health Technology Assessment and by hand search. We included documents from Europe, the United States, Canada, Australia, and New Zealand as well as transnational guidelines written in English or German. We systematically summarized in a narrative manner information on appropriate evidence sources for model parameters, their advantages and limitations, data identification methods, and data quality issues. Results. A large variety of evidence sources for populating models are mentioned in the 28 documents included. They comprise research- and non–research-based sources. Valid and less appropriate sources are identified for informing different types of model parameters, such as clinical effect size, natural history of disease, resource use, unit costs, and health state utility values. Guidelines do not provide structured and detailed advice on this issue. Limitations. The article does not include information from guidelines in languages other than English or German, and the information is not tailored to specific modeling techniques. Conclusions. The usability of guidelines and manuals for modeling could be improved by addressing the issue of evidence sources in a more structured and comprehensive format.