Criteria and Scoring Functions Used in Multi-criteria Decision Analysis and Value Frameworks for the Assessment of Rare Disease Therapies: A Systematic Literature Review

Background Traditionally, the economic value of health technologies is assessed with cost-effectiveness (CE) and budget impact (BI) analyses. However, the evaluation of rare disease therapies often considers novel value criteria. Multi-criteria decision analysis (MCDA) is a promising tool in the assessment of value criteria that typically cannot be captured with traditional approaches. Objectives The objective of this research was to investigate the criteria and scoring functions applied in value frameworks and MCDA tools relevant to the evaluation of rare disease therapies. The aim was to gain a better understanding of the domains and measurement of commonly referenced novel value criteria. Methods A systematic literature review was performed covering the period from 2013 to 2019. MCDA or value framework articles and structured review papers on orphan-drug-specific MCDA articles were reviewed. Information sources included MEDLINE, Embase, Scopus, and 26 other gray literature sources. A descriptive review of identified criteria and scoring functions was performed, with special focus on “novel” value criteria that are traditionally not considered in CE or BI analyses. Results In total, 15 relevant value frameworks and MCDA tools were identified. These studies included a large number (n = 56) of individual value criteria. The most commonly included novel criteria were unmet medical need, severity of disease, and reduction in uncertainty. The identified scoring functions (measurement methods) for novel criteria were highly heterogeneous and tailored. Standardized scoring functions were not observed. Additionally, the studies did not provide their rationale for choosing a specific scoring function for a criterion. Conclusions MCDA is a promising tool to include novel value criteria into the health technology assessment of therapies for rare diseases. To support the development of a transparent and justified evaluation process, scoring functions should be further investigated.