Publication: Incorporating MCDA into HTA: Challenges and potential solutions, with a focus on lower income settings
Issued Date
2018-11-09
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ISSN
14787547
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2-s2.0-85056423370
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Mahidol University
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SCOPUS
Bibliographic Citation
Cost Effectiveness and Resource Allocation. Vol.16, (2018)
Suggested Citation
Kevin Marsh, Praveen Thokala, Sitaporn Youngkong, Kalipso Chalkidou Incorporating MCDA into HTA: Challenges and potential solutions, with a focus on lower income settings. Cost Effectiveness and Resource Allocation. Vol.16, (2018). doi:10.1186/s12962-018-0125-8 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/46190
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Title
Incorporating MCDA into HTA: Challenges and potential solutions, with a focus on lower income settings
Abstract
© 2018 The Author(s). Background: Multicriteria decision analysis (MCDA) has the potential to bring more structure and transparency to health technology assessment (HTA). The objective of this paper is to highlight key methodological and practical challenges facing the use of MCDA for HTA, with a particular focus on lower and middle-income countries (LMICs), and to highlight potential solutions to these challenges. Methodological challenges: Key lessons from existing applications of MCDA to HTA are summarized, including: that the socio-technical design of the MCDA reflect the local decision problem; the criteria set properties of additive models are understood and applied; and the alternative approaches for estimating opportunity cost, and the challenges with these approaches are understood. Practical challenges: Existing efforts to implement HTA in LMICs suggest a number of lessons that can help overcome the practical challenges facing the implementation of MCDA in LMICs, including: adapting inputs from other settings and from expert opinion; investing in technical capacity; embedding the MCDA in the decision-making process; and ensuring that the MCDA design reflects local cultural and social factors. Conclusion: MCDA has the potential to improve decision making in LMICs. For this potential to be achieved, it is important that the lessons from existing applications of MCDA are learned.