BACKGROUND: Policymakers, who are constantly discussing growing health expenditures, should know whether the health system is efficient. We can provide them with such information through international health system efficiency evaluations. The main objectives of this study are: (a) to evaluate the efficiency of health systems in 28 developed countries by multiple-criteria decision analysis (MCDA) and data envelopment analysis (DEA) and (b) to identify reasonable benchmark countries for the Czech Republic, for which we collect information on the relative importance of health system inputs and outputs. METHODS: We used MCDA and DEA to evaluate the efficiency of the health systems of 28 developed countries. The models included four health system inputs (health expenditure as a relative share of GDP, the number of physicians, nurses, and hospital beds) and three health system outputs (life expectancy at birth, healthy life expectancy, and infant mortality rate). The sample covers 27 OECD countries and Russia, which is also included in the OECD database. To determine the input and output weights, we used a questionnaire sent to health policy experts in the Czech Republic. RESULTS: We obtained subjective information on the relative importance of the health system inputs and outputs from 27 Czech health policy experts. We evaluated health system efficiency using four MCDA and two DEA models. According to the MCDA models, Turkey, Poland, and Israel were found to have efficient health systems. The Czech Republic ranked 16th, 19th, 15th, and 17th. The benchmark countries for the Czech Republic's health system were Israel, Estonia, Luxembourg, Italy, the UK, Spain, Slovenia, and Canada. The DEA model with the constant returns to scale identified four technically efficient health systems: Turkey, the UK, Canada, and Sweden. The Czech Republic was found to be one of the worst-performing health systems. The DEA model with the variable returns to scale identified 15 technically efficient health systems. We found that efficiency results are quite robust. With two exceptions, the Spearman rank correlations between each pair of models were statistically significant at the 0.05 level. CONCLUSIONS: During the model formulation, we investigated the pitfalls of efficiency measurement in health care and used several practical solutions. We consider MCDA and DEA, above all, as exploratory methods, not methods providing definitive answers.

Faculty of Finance and Accounting Prague University of Economics and Business 4 Winston Churchill Sq Prague Czech Republic

Faculty of Informatics and Statistics Prague University of Economics and Business 4 Winston Churchill Sq Prague Czech Republic

Zobrazit více v PubMed

OECD. Health at a glance 2023: OECD indicators. Paris: OECD Publishing; 2023. 10.1787/7a7afb35-en.

Schneider EC, Shah A, Doty MM, et al. Reflecting poorly: health care in the US compared to other high-income countries. Commonwealth Fund. 2021. 10.26099/01dv-h208.

Nolte E, Wait S, McKee M. Investing in health: benchmarking health systems. London: The Nuffield Trust; 2006.

Papanicolas I, Smith PC. Health systems performance comparison: an agenda for policy, information and research. New York: Open University Press; 2013. ISBN 9780335247264.

WHO. The World Health Report 2000: Health systems: improving performance. Geneva, WHO; 2000.

Dlouhý M. Non-homogeneity in the efficiency evaluation of health systems. BMC Health Serv Res. 2023;23:1237. 10.1186/s12913-023-10246-8. 10.1186/s12913-023-10246-8 PubMed DOI PMC

European Commission. Directorate-General for Health and Food Safety. Tools and methodologies to assess the efficiency of health care services in Europe: an overview of current approaches and opportunities for improvement. Report by the Expert Group on Health System Performance Assessment. Luxembourg: Publications Office of the European Union. 2019. 10.2875/346480.

OECD. Health at a glance: Europe 2022: state of Health in the EU cycle. Paris: OECD Publishing; 2022.

Papanicolas I, Rajan D, Karanikolos M, Soucat A, Figueras J. Health system performance assessment: a framework for policy analysis. World Health Organization; 2022. PubMed

Tchouaket ÉN, Lamarche PA, Goulet L, Contandriopoulos AP. Health care system performance of 27 OECD countries. Int J Health Plan Manag. 2012;27:104–29. 10.1002/hpm.1110.10.1002/hpm.1110 PubMed DOI

Tandon A, Murray CJ, Lauer JA, Evans DB. Measuring overall health system performance for 191 countries. Geneva: World Health Organization; 2000.

Health Consumer Powerhouse. Euro Health Consumer Index 2018. Health Consumer Powerhouse Ltd.; 2019.

Romaniuk P, Kaczmarek K, Syrkiewicz-Świtała M, Holecki T, Szromek AR. Health systems and their assessment: a methodological proposal of the synthetic outcome measure. Front Public Health. 2018;6:126. 10.3389/fpubh.2018.00126. 10.3389/fpubh.2018.00126 PubMed DOI PMC

Yiğit A. Performance analysis of OECD countries based on health outcomes and expenditure indicators. J Int Health Sci Manage. 2019;5(9):114–23.

Pereira MA, Machete IF, Ferreira DC, Marques RC. Using multi-criteria decision analysis to rank European health systems: the Beveridgian Financing Case. Soc Econ Plan Sci. 2020;72:100913. 10.1016/j.seps.2020.100913.10.1016/j.seps.2020.100913 DOI

Retzlaff-Roberts D, Chang CF, Rubin RM. Technical efficiency in the use of health care resources: a comparison of OECD countries. Health Pol. 2004;69(1):55–72. 10.1016/j.healthpol.2003.12.002.10.1016/j.healthpol.2003.12.002 PubMed DOI

Spinks J, Hollingsworth C. Cross-country comparisons of technical efficiency of health production: a demonstration of pitfalls. Appl Econ. 2009;41(4):417–27. 10.1080/00036840701604354.10.1080/00036840701604354 DOI

Asandului L, Roman M, Fatulescu P. The efficiency of healthcare systems in Europe: a data envelopment analysis approach. Proc Econ Finance. 2014;31(10):261–8. 10.1016/S2212-5671(14)00301-3.10.1016/S2212-5671(14)00301-3 DOI

Cetin VR, Bahce S. Measuring the efficiency of health systems of OECD countries by data envelopment analysis. Appl Econ. 2016;48(37):3497–507. 10.1080/00036846.2016.1139682.10.1080/00036846.2016.1139682 DOI

Behr A, Theune K. Health system efficiency: a fragmented picture based on OECD Data. PharmacoEcon Open. 2017;1:203–21. 10.1007/s41669-017-0010-y. 10.1007/s41669-017-0010-y PubMed DOI PMC

Cylus J, Papanicolas I, Smith PC. Using data envelopment analysis to address the challenges of comparing health system efficiency. Global Pol. 2017;8:60–8. 10.1111/1758-5899.12212.10.1111/1758-5899.12212 DOI

Ahmed S, Hasan MZ, MacLennan M, et al. Measuring the efficiency of health systems in Asia: a data envelopment analysis. BMJ Open. 2019;9:e022155. 10.1136/bmjopen-2018-022155. 10.1136/bmjopen-2018-022155 PubMed DOI PMC

Gavurova B, Kocisova K, Sopko J. Health system efficiency in OECD countries: dynamic network DEA approach. Health Econ Rev. 2021;11:40. 10.1186/s13561-021-00337-9. 10.1186/s13561-021-00337-9 PubMed DOI PMC

Pereira MA, Dinis DC, Ferreira DC, Figueira JR, Marques RC. A network data envelopment analysis to estimate nations’ efficiency in the fight against SARS-CoV-2. Expert Syst Appl. 2022;210:118362. 10.1016/j.eswa.2022.118362. 10.1016/j.eswa.2022.118362 PubMed DOI PMC

Lupu D, Tiganasu R. COVID-19 and the efficiency of health systems in Europe. Health Econ Rev. 2022;12:14. 10.1186/s13561-022-00358-y. 10.1186/s13561-022-00358-y PubMed DOI PMC

Ersoy Y, Aktaş A. Health system efficiency of oecd countries with data envelopment analysis. Problemy Zarządzania (Management Issues). 2022;20(4):90–109. 10.7172/1644-9584.98.4.

Selamzade F, Ersoy Y, Ozdemir Y, Celik MY. Health Efficiency Measurement of OECD Countries against the COVID-19 pandemic by using DEA and MCDM methods. Arab J Sci Eng. 2023;48:15695–712. 10.1007/s13369-023-08114-y.10.1007/s13369-023-08114-y DOI

GBD 2015 Healthcare Access and Quality Collaborators. Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990–2015: a novel analysis from the Global Burden of Disease Study 2015. Lancet. 2017;390(10091):231–66. 10.1016/S0140-6736(17)30818-8. PubMed PMC

Pereira MA, Camanho AS. The ‘Healthcare Access and Quality Index’ revisited: a fuzzy data envelopment analysis approach. Expert Syst Appl. 2024;245:123057. 10.1016/j.eswa.2023.123057.10.1016/j.eswa.2023.123057 DOI

Mbau R, Musiega A, Nyawira L, Tsofa B, Mulwa A, Molyneux S, Maina I, Jemutai J, Normand C, Hanson K, Barasa E. Analysing the efficiency of health systems: a systematic review of the literature. Appl Health Econ Health Pol. 2023;21(2):205–24. 10.1007/s40258-022-00785-2.10.1007/s40258-022-00785-2 PubMed DOI PMC

Varabyova Y, Müller JM. The efficiency of health care production in OECD countries: a systematic review and meta-analysis of cross-country comparisons. Health Pol. 2016;120(3):252–63. 10.1016/j.healthpol.2015.12.005.10.1016/j.healthpol.2015.12.005 PubMed DOI

Olesen OB, Petersen NV, Podinovski VV. Efficiency analysis with ratio measures. Eur J Oper Res. 2015;245(2):446–62. 10.1016/j.ejor.2015.03.013.10.1016/j.ejor.2015.03.013 DOI

Belton V, Stewart TJ. DEA and MCDA: competing or complementary approaches? In: Meskens N, Roubens M, editors. Advances in decision analysis. Mathematical Modelling: theory and applications. Volume 4. Dordrecht: Springer; 1999. 10.1007/978-94-017-0647-6_6.

Cooper WW, Seiford LM, Zhu J. Handbook on Data Envelopment Analysis. Kluwer Academic; 2004.

Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. Eur J Oper Res. 1978;2(6):429–44. 10.1016/0377-2217(78)90138-8.10.1016/0377-2217(78)90138-8 DOI

Banker RD, Charnes A, Cooper WW. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci. 1984;30(9):1078–92. 10.1287/mnsc.30.9.1078.10.1287/mnsc.30.9.1078 DOI

Deprins D, Simar L, Tulkens H. Measuring labor efficiency in post offices. In: Marchand M, Petieau P, Tulkens H, editors. The performance of public enterprises: concepts and measurement. Amsterdam: North Holland; 1984.

Hollingsworth B. Non-parametric and parametric applications measuring efficiency in health care. Health Care Manag Sci. 2003;6(4):203–18. 10.1023/A:1026255523228. 10.1023/A:1026255523228 PubMed DOI

Havlík P, Dlouhý M. Relative weights of indicators in health system efficiency evaluation. In: Proceedings of the 15th International Scientific Conference Public Economics and Administration 2023. Ostrava: VŠB-Technical University of Ostrava; 2023, pp. 156–161. 10.31490/9788024846989.

Mas-Colell A, Whinston MD, Green JR. Microeconomic theory. New York: Oxford University Press; 1995.

Nicholson W. Microeconomic theory: basic principles and extensions. 8th ed. Thomson Learning; 2002.

WHO. Constitution of the World Health Organization. New York: WHO; 1946.

Barr N. The Economics of the Welfare State. 2nd ed. Oxford: Oxford University Press; 1993.

Dyson RG, Allen R, Camanho AS, Podinovski VV, Sarrico CS, Shale EA. Pitfalls and protocols in DEA. Eur J Oper Res. 2001;132(2):245–59. 10.1016/s0377-2217(00)00149-1.10.1016/s0377-2217(00)00149-1 DOI

Canadian Council on Social Determinants of Health. A review of frameworks on the determinants of health. Ottawa, ON: Canadian Council on Social Determinants of Health; 2015.

McGovern L. Health Policy brief: the relative contribution of multiple determinants to health outcomes. Health Aff. 2014. 10.1377/hpb20140821.404487.10.1377/hpb20140821.404487 DOI

Wilkinson R, Marmot M, World Health Organization. Regional Office for Europe. Social determinants of health: the solid facts. 2nd ed. World Health Organization. Regional Office for Europe; 2003.

Nolte E, McKee M. Measuring the health of nations: analysis of mortality amenable to health care. BMJ. 2003;327(7424):1129. 10.1136/bmj.327.7424.1129. 10.1136/bmj.327.7424.1129 PubMed DOI PMC

GBD 2019 Healthcare Access and Quality Collaborators. Assessing performance of the Healthcare Access and Quality Index, overall and by select age groups, for 204 countries and territories, 1990–2019: a systematic analysis from the global burden of Disease Study 2019. Lancet Glob Health. 2022;10(12):e1715–43. 10.1016/S2214-109X(22)00429-6. 10.1016/S2214-109X(22)00429-6 PubMed DOI PMC

Golany B, Roll Y. An application procedure for DEA. Omega. 1989;17(3):237–50. 10.1016/0305-0483(89)90029-7.10.1016/0305-0483(89)90029-7 DOI

Emrouznejad A, Thanassoulis E. A mathematical model for dynamic efficiency using data envelopment analysis. Appl Math Comput. 2005;160(2):363–78. 10.1016/j.amc.2003.09.026.10.1016/j.amc.2003.09.026 DOI