Improving the Accuracy and Comparability of Model-Based Economic Evaluations of Health Technologies for Reimbursement Decisions

Hossein Haji Ali Afzali, Jonathan Karnon and Tracy Merlin

Medical Decision Making, 2013, vol. 33, issue 3, 325-332

Abstract: Increasingly, decision analytic models are used within economic evaluations of health technologies (e.g., pharmaceuticals) submitted to national reimbursement bodies in countries like Australia and UK, where such models play a fundamental role in informing public funding decisions. Concerns regarding the accuracy of model outputs and hence the credibility of national reimbursement decisions are frequently raised. We propose a framework for developing reference models for specific diseases to inform economic evaluations of health technologies and their appraisal. The structure of a reference model reflects the natural history of the condition under study and defines the clinical events to be represented, the relationships between the events, and the effect of patient characteristics on the probability and timing of events. We contend that the use of reference models will improve the accuracy and comparability of public funding decisions. This can lead to the more efficient allocation of public funds.

Keywords: model uncertainty; sensitivity analysis; reference model (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:33:y:2013:i:3:p:325-332

DOI: 10.1177/0272989X12458160

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