Relationship between the data collection approaches and the application of health economics models in practice: a case study approach

Introduction: There are a variety of data collection methods available for the purpose of populating health economic models. These can range in rigor from the most robust method such as full systematic reviews to less robust methods such as the use of expert opinion and stakeholder workshops. Often policy makers encourage the use of systematic reviews as a first line approach to generate the evidence base for decision models. However, systematic reviews are often limited by the lack of robust published data. In the face of this health economic modellers encounter three common options: (i) stay confined to the results of the systematic review, (ii) expand the systematic review (by altering search strategy or inclusion/exclusion criteria), or (iii) elicit expert opinion. Each of these methods can have significant implications for the final results of the health economics model and the applicability of the model in real world practice. It is important for those developing health economics models to understand the advantages and disadvantages of each data collection approaches along with an understanding of how these methods can be used together to ensure the final output of an economic analysis is of most use to policy makers. Objective: To examine the common issues encountered with data collection methods for health economics models. In addition, an understanding of how these concerns can be overcome using alternative data 3 collection methods. An examination of how the final combined approach to data collection is related to the applicability of the health economics models in practice. Methods: To examine two case studies of health economics models developed for public sector audiences: domestic violence prevention, and provision of play interventions for children. In each of these case studies the use of systematic reviews was used as the first approach to data collection. However, the systematic reviews were limited due to lack of robust data. Each case study provides an example of how various methods can be used to overcome the limitations of systematic reviews – (i) stay confined to the results of the systematic review, (ii) expand the systematic review, or (iii) elicit expert opinion. Each case study will be assessed to determine the relationship between the approach to data collection and the applicability of the final model. Results: The results of the case studies show that if models are constricted to only the use of the highest quality evidence they are at risk of being robust yet limited in use for policy makers. Alternatively, the use of less robust methods produce models which are of greater value to policy makers but face issues of data rigour. Therefore, when undertaking economic evaluation it is important to be flexible in the approach to data collection. Flexible approaches ensure the final outputs from the economic model are of most use to policy makers. As mixed methods approach to data collection can introduce bias it is important the approach to data collection is transparent to ensure users of the analysis are aware of any limitations.