The application of multi-criteria decision analysis to inform in resource allocation

This is the authors' abstract. We don't add key points for this paper.

<ns3:p> <ns3:bold>Background:</ns3:bold> <ns3:bold/> There is a perception held by payers that orphan products are expensive. As a result, the current health technology assessment systems might be too restrictive for orphan drugs, therefore potentially denying patients access to life-saving medicines. While price is important, it should be considered in relation to a broader range of disease-related product attributes that are not necessarily considered by many health technology assessment agencies. To overcome these challenges, multi-criteria decision analysis has been proposed as an alternative to evaluate technologies. </ns3:p> <ns3:p> <ns3:bold>Methods:</ns3:bold> A targeted literature review was conducted to identify the most frequently cited attributes in multi-criteria decision analysis (MCDA) in rare diseases. From the leading attributes identified, we developed a multi-criteria decision analysis framework with which to aggregate the orphan drug values. We subsequently reviewed and plotted the relationship between single attributes and the average annual treatment costs for 8 drugs used in the treatment of rare endocrine diseases. The annual treatment costs were based on UK list prices for the average daily dose per patient. </ns3:p> <ns3:p> <ns3:bold>Results:</ns3:bold> The five most frequently mentioned attributes in the literature were as follows: Disease severity, Unmet need (or availability of therapeutic alternatives), Comparative effectiveness or efficacy, Quality of evidence and Safety & tolerability. Results from the multi-criteria decision analysis framework indicate a wide range of average annual per-patients costs for drugs intended for the same diseases, and likewise for diseases with a similar level of Disease severity. </ns3:p> <ns3:p> <ns3:bold>Conclusions:</ns3:bold> Multi-criteria decision analysis may offer a viable alternative to support discussion in reimbursement decisions for orphan drugs. The analyses can be used to inform investigations on the application of MCDAs in rare diseases. </ns3:p>