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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 as...

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Autores principales: Zelei, Tamás, Mendola, Nicholas D., Elezbawy, Baher, Németh, Bertalan, Campbell, Jonathan D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8611126/
https://www.ncbi.nlm.nih.gov/pubmed/34003484
http://dx.doi.org/10.1007/s41669-021-00271-w
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author Zelei, Tamás
Mendola, Nicholas D.
Elezbawy, Baher
Németh, Bertalan
Campbell, Jonathan D.
author_facet Zelei, Tamás
Mendola, Nicholas D.
Elezbawy, Baher
Németh, Bertalan
Campbell, Jonathan D.
author_sort Zelei, Tamás
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41669-021-00271-w.
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spelling pubmed-86111262021-12-10 Criteria and Scoring Functions Used in Multi-criteria Decision Analysis and Value Frameworks for the Assessment of Rare Disease Therapies: A Systematic Literature Review Zelei, Tamás Mendola, Nicholas D. Elezbawy, Baher Németh, Bertalan Campbell, Jonathan D. Pharmacoecon Open Systematic 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41669-021-00271-w. Springer International Publishing 2021-05-18 /pmc/articles/PMC8611126/ /pubmed/34003484 http://dx.doi.org/10.1007/s41669-021-00271-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Systematic Review
Zelei, Tamás
Mendola, Nicholas D.
Elezbawy, Baher
Németh, Bertalan
Campbell, Jonathan D.
Criteria and Scoring Functions Used in Multi-criteria Decision Analysis and Value Frameworks for the Assessment of Rare Disease Therapies: A Systematic Literature Review
title Criteria and Scoring Functions Used in Multi-criteria Decision Analysis and Value Frameworks for the Assessment of Rare Disease Therapies: A Systematic Literature Review
title_full Criteria and Scoring Functions Used in Multi-criteria Decision Analysis and Value Frameworks for the Assessment of Rare Disease Therapies: A Systematic Literature Review
title_fullStr Criteria and Scoring Functions Used in Multi-criteria Decision Analysis and Value Frameworks for the Assessment of Rare Disease Therapies: A Systematic Literature Review
title_full_unstemmed Criteria and Scoring Functions Used in Multi-criteria Decision Analysis and Value Frameworks for the Assessment of Rare Disease Therapies: A Systematic Literature Review
title_short Criteria and Scoring Functions Used in Multi-criteria Decision Analysis and Value Frameworks for the Assessment of Rare Disease Therapies: A Systematic Literature Review
title_sort criteria and scoring functions used in multi-criteria decision analysis and value frameworks for the assessment of rare disease therapies: a systematic literature review
topic Systematic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8611126/
https://www.ncbi.nlm.nih.gov/pubmed/34003484
http://dx.doi.org/10.1007/s41669-021-00271-w
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