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Making Good Decisions in Healthcare with Multi-Criteria Decision Analysis: The Use, Current Research and Future Development of MCDA

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  • Axel C. Mühlbacher

    (IGM Institut Gesundheitsökonomie und Medizinmanagement, Hochschule Neubrandenburg
    Gesellschaft für empirische Beratung GmbH (GEB)
    Duke Global Health Institute)

  • Anika Kaczynski

    (IGM Institut Gesundheitsökonomie und Medizinmanagement, Hochschule Neubrandenburg)

Abstract

Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.

Suggested Citation

  • Axel C. Mühlbacher & Anika Kaczynski, 2016. "Making Good Decisions in Healthcare with Multi-Criteria Decision Analysis: The Use, Current Research and Future Development of MCDA," Applied Health Economics and Health Policy, Springer, vol. 14(1), pages 29-40, February.
    • Handle: RePEc:spr:aphecp:v:14:y:2016:i:1:d:10.1007_s40258-015-0203-4
    DOI: 10.1007/s40258-015-0203-4
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    References listed on IDEAS

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    Cited by:

    1. Mónica D. Oliveira & Inês Mataloto & Panos Kanavos, 2019. "Multi-criteria decision analysis for health technology assessment: addressing methodological challenges to improve the state of the art," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(6), pages 891-918, August.
    2. Francesco Paolucci & Ken Redekop & Ayman Fouda & Gianluca Fiorentini, 2017. "Decision Making and Priority Setting: The Evolving Path Towards Universal Health Coverage," Applied Health Economics and Health Policy, Springer, vol. 15(6), pages 697-706, December.
    3. Martina Garau & Grace Hampson & Nancy Devlin & Nicola Amedeo Mazzanti & Antonio Profico, 2018. "Applying a Multicriteria Decision Analysis (MCDA) Approach to Elicit Stakeholders’ Preferences in Italy: The Case of Obinutuzumab for Rituximab-Refractory Indolent Non-Hodgkin Lymphoma (iNHL)," PharmacoEconomics - Open, Springer, vol. 2(2), pages 153-163, June.
    4. Wiebke Mohr & Anika Rädke & Adel Afi & Franka Mühlichen & Moritz Platen & Bernhard Michalowsky & Wolfgang Hoffmann, 2022. "Development of a Quantitative Instrument to Elicit Patient Preferences for Person-Centered Dementia Care Stage 1: A Formative Qualitative Study to Identify Patient Relevant Criteria for Experimental D," IJERPH, MDPI, vol. 19(13), pages 1-27, June.
    5. Bana e Costa, Carlos A. & Oliveira, Mónica D. & Vieira, Ana C.L. & Freitas, Liliana & Rodrigues, Teresa C. & Bana e Costa, João & Freitas, Ângela & Santana, Paula, 2023. "Collaborative development of composite indices from qualitative value judgements: The EURO-HEALTHY Population Health Index model," European Journal of Operational Research, Elsevier, vol. 305(1), pages 475-492.

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