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Multi-criteria decision analysis for supporting the selection of medical devices under uncertainty

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  • Ivlev, Ilya
  • Vacek, Jakub
  • Kneppo, Peter

Abstract

Innovative approaches to the assessment and management of medical technologies use a combination of health technology assessment (HTA) and operations research methods, specifically multiple-criteria decision analysis (MCDA). The purpose of this article is to develop methodological support and provide a theoretical justification for decision support in the selection of medical devices under conditions of uncertainty, using MRI systems as an example. The goal of the method application has been formulated as follows: determine a ranked list of MRI systems for contributory health organisations administered by regional authorities (regional hospitals) in the Czech Republic. An analytic hierarchy process (AHP) and the Delphi method were used to identify experts’ preferences and for consensus building. The expert group was selected based on eight complex-valued criteria, and each expert was given a weighting factor. A set of 13 MRI systems and the 14 key default specifications that play the most important roles when hospitals select MRIs for purchase were defined. Strong conformity (W ≥ 0.6, p < 0.05) within the experts' judgments was revealed. A prediction regarding alternatives, weights and changes in priority vectors over the following 8 years has been provided. The developed approach is useful in decision support when selecting medical devices under conditions of uncertainty by hospitals.

Suggested Citation

  • Ivlev, Ilya & Vacek, Jakub & Kneppo, Peter, 2015. "Multi-criteria decision analysis for supporting the selection of medical devices under uncertainty," European Journal of Operational Research, Elsevier, vol. 247(1), pages 216-228.
    • Handle: RePEc:eee:ejores:v:247:y:2015:i:1:p:216-228
    DOI: 10.1016/j.ejor.2015.05.075
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    2. 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.
    3. Ni, Lei & Chen, Yu-wang & de Brujin, Oscar, 2021. "Towards understanding socially influenced vaccination decision making: An integrated model of multiple criteria belief modelling and social network analysis," European Journal of Operational Research, Elsevier, vol. 293(1), pages 276-289.
    4. Sergio Domínguez & María Carmen Carnero, 2020. "Fuzzy Multicriteria Modelling of Decision Making in the Renewal of Healthcare Technologies," Mathematics, MDPI, vol. 8(6), pages 1-46, June.
    5. Abbas, Ali E. & Hupman, Andrea C., 2023. "Scale dependence in weight and rate multicriteria decision methods," European Journal of Operational Research, Elsevier, vol. 309(1), pages 225-235.
    6. Gawlik, Remigiusz, 2016. "Encompassing the Work-Life Balance into Early Career Decision-Making of Future Employees Through the Analytic Hierarchy Process," MPRA Paper 80260, University Library of Munich, Germany.
    7. Vieira, Ana C.L. & Oliveira, Mónica D. & Bana e Costa, Carlos A., 2020. "Enhancing knowledge construction processes within multicriteria decision analysis: The Collaborative Value Modelling framework," Omega, Elsevier, vol. 94(C).
    8. Zhu, Bin & Xu, Zeshui & Zhang, Ren & Hong, Mei, 2016. "Hesitant analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 250(2), pages 602-614.
    9. María Carmen Carnero & Andrés Gómez, 2019. "Optimization of Decision Making in the Supply of Medicinal Gases Used in Health Care," Sustainability, MDPI, vol. 11(10), pages 1-31, May.
    10. Arantes, Amílcar & Alhais, Andreia Frias & Ferreira, Luis Miguel D.F., 2022. "Application of a purchasing portfolio model to define medicine purchasing strategies: An empirical study," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

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