Abstract
Purpose: The aim of this study is to compare the health system performances of OECD countries in the light of certain health and socio-economic indicators and to make country performance rankings with the MULTIMOORA method.
Methods: Firstly, health and socio-economic indicators were determined for the performance evaluation comparisons of the countries through literature review. The data of the indicators were obtained from reliable databases and analysed by MULTIMOORA method, which is one of the multi-criteria decision-making methods.
Results: According to the results of the analyses, the countries with the highest health system performance among 38 OECD countries are Japan, Sweden, Norway, Denmark and Germany, while the countries with the lowest performance are Latvia, Costa Rica, Turkey, Mexico and Colombia, respectively.
Conclusion: As a result, in countries with high health system performance, access, quality and comprehensiveness of health services are ensured. Per capita expenditures for the health system are quite high. In countries with low performance, the limited resources allocated to the health system cause the service coverage index to remain low. High out-of-pocket expenditures drive especially low-income groups away from health services. In this context, low-performing countries need to improve their health systems by learning from the health systems of high-performing countries and developing strategies to overcome existing deficiencies.
References
- 1. Bennett S and Peters DH. Assessing national health systems: why and how. Health Syst Reform. 2015;1(1):9-17.
- 2. Kumah E, Ankomah SE, Fusheini A, et al. Frameworks for health systems performance assessment: how comprehensive is Ghana’s holistic assessment tool? Glob Health Res Policy. 2020;5:1-12.
- 3. Street A and Smith P. How can we make valid and useful comparisons of different health care systems? Health Serv Res. 2021;56(3):1299.
- 4. Arsenault C, Gage A, Kim MK, et al. COVID-19 and resilience of healthcare systems in ten countries. Nat Med. 2022;28(6):1314-24.
- 5. Ibikunle JA, Oyerinola DS and Amos A. Food inflation and child health in Africa: evidence from countries with high misery index. Acta Econ. 2022;20(37):167-87. https://doi.org/10.7251/ace2237167a
- 6. Bamigbala OA and Ojetunde AO. Identifying factors contributing to under-five mortality in Nigeria. Tanzan J Sci. 2023;49(2):322-31. https://doi.org/10.4314/tjs.v49i2.4
- 7. Beyaztaş FY, Bütün C ve Yıldırım A. A baby found in a dumpster: case report. Cumhuriyet Med J. 2019. https://doi.org/10.7197/223.vi.566911
- 8. Tai N, Htut SHT and Swe T. Impact of health care delivery utilization on under-5 child mortality in Myanmar. Int J Health Econ Policy. 2019;4(3):82. https://doi.org/10.11648/j.hep.20190403.13
- 9. Owusu PA, Sarkodie SA and Pedersen PA. Relationship between mortality and health care expenditure: sustainable assessment of health care system. PLoS One. 2021;16(2):e0247413. https://doi.org/10.1371/journal.pone.0247413
- 10. Navarro-Jimenez E, Saturno-Hernández P, Jaramillo-Mejía M et. al. Amenable mortality in children under 5: an indicator for identifying inequalities in healthcare delivery: a review. Children. 2024;11(7):764. https://doi.org/10.3390/children11070764
- 11. Varela DV, Martins M, Furtado A, et al. Spatio-temporal evolution of mortality in Cape Verde: 1995–2018. PLoS Glob Public Health. 2023;3(3):e0000753. https://doi.org/10.1371/journal.pgph.0000753
- 12. OECD Data Explorer [Internet]. [cited 2024 Dec 12]. Available from: https://data-explorer.oecd.org/
- 13. World Bank Gender Data Portal [Internet]. [cited 2025 Dec 12]. Available from: https://genderdata.worldbank.org/en/indicator/
- 14. World Bank DataBank [Internet]. [cited 2025 Dec 12]. Available from: https://databank.worldbank.org/
- 15. WHO Indicator Metadata Registry [Internet]. [cited 2025 Dec 12]. Available from: https://data.who.int/indicators/i/3805B1E/9A706FD
- 16. Brauers WK and Zavadskas EK. The MOORA method and its application to privatization in a transition economy. Control Cybern. 2006;35(2):445-69.
- 17. Brauers WKM and Zavadskas EK. Project management by MULTIMOORA as an instrument for transition economies. Technol Econ Dev Econ. 2010;16(1):5-24.
- 18. Brauers WKM, Baležentis A and Baležentis T. Economic ranking of the European Union countries by MULTIMOORA optimization. Technol Econ Dev Econ. 2012;18:329-35. https://doi.org/10.3846/bm.2012.043
- 19. Özcan N and Ömürbek A. BİST’de işlem gören sigorta şirketlerinin MULTIMOORA yöntemiyle performans ölçümü. Int J Bus Econ Manag Perspect. 2016;1(2):65-75.
- 20. Klumpp M, Loske D and Bicciato S. COVID-19 health policy evaluation: integrating health and economic perspectives with a data envelopment analysis approach. Eur J Health Econ. 2022;23(8):1263-85. https://doi.org/10.1007/s10198-021-01425-7
- 21. Yüksel O. Comparison of healthcare system performances in OECD countries. Int J Health Serv Res Policy. 2021;6(2):251-61. https://doi.org/10.33457/ijhsrp.935170
- 22. Tchouaket É, Lamarche PA, Goulet L et. al. Health care system performance of 27 OECD countries. Int J Health Plann Manage. 2012;27(2):104-29. https://doi.org/10.1002/hpm.1110
- 23. Blümel M, Achstetter M, Hengel P, et.al. Piloting the first health system performance assessment for Germany: key results and learnings. Eur J Public Health. 2022;32(Suppl 3). https://doi.org/10.1093/eurpub/ckac129.245
- 24. Nilbert M, Thomsen LA, Jensen JW, et al. The power of empirical data; lessons from the clinical registry initiatives in Scandinavian cancer care. Acta Oncol. 2020;59(11):1343-56. https://doi.org/10.1080/0284186x.2020.1820573
- 25. Johansson AL, Larønningen S, Skovlund CW, et al. The impact of the COVID‐19 pandemic on cancer diagnosis based on pathology notifications: a comparison across the Nordic countries during 2020. Int J Cancer. 2022;151(3):381-95. https://doi.org/10.1002/ijc.34029
- 26. Gavurová B, Kočišová K and Sopko J. Health system efficiency in OECD countries: dynamic network DEA approach. Health Econ Rev. 2021;11(1). https://doi.org/10.1186/s13561-021-00337-9
- 27. Rotar A, Botje D, Klazinga N, et al. The involvement of medical doctors in hospital governance and implications for quality management: a quick scan in 19 and an in depth study in 7 OECD countries. BMC Health Serv Res. 2016;16(Suppl 2). https://doi.org/10.1186/s12913-016-1396-4
- 28. Scheffler RM and Arnold D. Projecting shortages and surpluses of doctors and nurses in the OECD: what looms ahead. Health Econ Policy Law. 2018;14(2):274-90. https://doi.org/10.1017/s174413311700055x
- 29. Anwar A, Hyder S, Nor NM, et.al. Government health expenditures and health outcome nexus: a study on OECD countries. Front Public Health. 2023;11. https://doi.org/10.3389/fpubh.2023.1123759
- 30. Bilsel M and Davutyan N. Hospital efficiency with risk adjusted mortality as undesirable output: the Turkish case. Ann Oper Res. 2011;221(1):73-88. https://doi.org/10.1007/s10479-011-0951-y
Details
| Primary Language | English |
|---|---|
| Subjects | Health Policy, Health Services and Systems (Other) |
| Journal Section | Research Articles |
| Authors | |
| Early Pub Date | June 18, 2025 |
| Publication Date | |
| Submission Date | January 13, 2025 |
| Acceptance Date | April 10, 2025 |
| Published in Issue | Year 2025Volume: 16 Issue: Erken Çevrimiçi Yayınlar |