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Using multi-criteria decision analysis to rank European health systems: The Beveridgian financing case

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  • Pereira, Miguel Alves
  • Machete, Inês Freire
  • Ferreira, Diogo Cunha
  • Marques, Rui Cunha

Abstract

Health is one of the most fundamental human rights. In that sense, the creation of health systems attempted to provide the population with organisations, institutions, and resources to meet their needs. However, health inequalities are prevalent in all countries. Thus, evaluating health systems is vital to understand this issue. Accordingly, the aim of this work is to develop a multi-criteria decision analysis (MCDA) approach to innovatively rank nine of the European health systems with Beveridgian financing that would help determine the shortcomings of the Portuguese National Health Service and discern the operating “best practices”, in a close interaction with the Portuguese Ministry of Health. First, the panel of decision-making actors was guided through the design of a cognitive map to promote their learning process and help them identify eleven fundamental points of view. Second, their operationalisation was facilitated by selecting acceptable descriptors of performance. Finally, an MCDA approach was proposed to evaluate the chosen health systems using an additive model, which included a sensitivity and a robustness analysis. In the end, the model was perceived by the panel as being trustworthy and reliable. This framework can be used for further MCDA modelling in similar applications based on participatory procedures.

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  • Pereira, Miguel Alves & Machete, Inês Freire & Ferreira, Diogo Cunha & Marques, Rui Cunha, 2020. "Using multi-criteria decision analysis to rank European health systems: The Beveridgian financing case," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
  • Handle: RePEc:eee:soceps:v:72:y:2020:i:c:s0038012120301336
    DOI: 10.1016/j.seps.2020.100913
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    4. Elorza, María Eugenia & Moscoso, Nebel Silvana & Blanco, Anibal Manuel, 2022. "Assessing performance in health care: A mathematical programming approach for the re-design of primary health care networks," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    5. Sven Peters & Mendy Tönsfeuerborn & Rüdiger von Nitzsch, 2024. "Integrating Uncertainties in a Multi-Criteria Decision Analysis with the Entscheidungsnavi," Mathematics, MDPI, vol. 12(11), pages 1-28, June.
    6. Paulo Caldas & Miguel Varela, 2023. "The Portuguese Public Hospitals Performance Evolution before and during the SARS-CoV-2 Pandemic (2017–2022)," Sustainability, MDPI, vol. 15(15), pages 1-31, July.
    7. Vidoli, Francesco & Auteri, Monica, 2022. "Health-care demand and supply at municipal level: A spatial disaggregation approach," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    8. Popkova, Elena G. & Sergi, Bruno S., 2022. "Digital public health: Automation based on new datasets and the Internet of Things," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    9. Jaros{l}aw Wk{a}tr'obski & Aleksandra Bk{a}czkiewicz & Iga Rudawska, 2023. "A Strong Sustainability Paradigm Based Analytical Hierarchy Process (SSP-AHP) Method to Evaluate Sustainable Healthcare Systems," Papers 2306.00718, arXiv.org.
    10. Pereira, André Alves & Pereira, Miguel Alves, 2023. "Energy storage strategy analysis based on the Choquet multi-criteria preference aggregation model: The Portuguese case," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    11. Pereira, Miguel Alves & Camanho, Ana Santos & Figueira, José Rui & Marques, Rui Cunha, 2021. "Incorporating preference information in a range directional composite indicator: The case of Portuguese public hospitals," European Journal of Operational Research, Elsevier, vol. 294(2), pages 633-650.
    12. Pereira, Miguel Alves & Marques, Rui Cunha, 2022. "Is sunshine regulation the new prescription to brighten up public hospitals in Portugal?," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
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    15. Pereira, Javier & Contreras, Pedro & Morais, Danielle C. & Arroyo-López, Pilar, 2022. "Multi-criteria ordered clustering of countries in the Global Health Security Index," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

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