How to use multi-criteria decision analysis methods for reimbursement decision-making in healthcare: a step-by-step guide

Abstract

In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.

Keywords::

• decision-making
• healthcare
• methods
• multi-criteria decision analysis
• reimbursement

Acknowledgements

The authors are grateful to L Dias and H Blythman for helpful comments on an earlier version of the current manuscript.

Disclaimer

The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of Mitacs and Pfizer Canada Inc.

Financial & competing interests disclosure

This work was supported by a grant from Mitacs accelerate with partner Pfizer Canada Inc. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Key issues

• Multi-criteria decision analysis (MCDA) has been purported as a valuable alternative to the traditional decision-making framework used in Health Technology Assessment. It has proven its usefulness in other fields such as operations research, management and environment.

• Current research and applications focus on a specific family of MCDA method, namely value-based measurement models.

• Contrary to common beliefs, MCDA is both a process and set of methods that can be applied to a variety of healthcare problems and decision-making levels.

• Future research should be devoted to investigating the relevance of the remaining MCDA models, and to selecting the appropriate models for supporting healthcare reimbursement decisions.

• The selection of the appropriate MCDA methods to support healthcare decision-making should take into account the type of problems to address and the decision-making level. It is critical that the criteria selected exhibit the following features ‘value relevance’, ‘understandability’, ‘measurability’, ‘non-redundancy’, ‘independence’ and ‘comprehensiveness’. Failing to fulfill these requirements would lead to non-optimal results. The background and training of the stakeholders involved in the decision-making process might also influence that choice.