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Data envelopment analysis efficiency in the public sector using provider and customer opinion: An application to the Spanish health system

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  • Jesús A. Tapia

    (University of Valladolid)

  • Bonifacio Salvador

    (University of Valladolid)

Abstract

Measuring the relative efficiency of a finite fixed set of service-producing units (hospitals, state services, libraries, banks,...) is an important purpose of Data Envelopment Analysis (DEA). We illustrate an innovative way to measure this efficiency using stochastic indexes of the quality from these services. The indexes obtained from the opinion-satisfaction of the customers are estimators, from the statistical view point, of the quality of the service received (outputs); while, the quality of the offered service is estimated with opinion-satisfaction indexes of service providers (inputs). The estimation of these indicators is only possible by asking a customer and provider sample, in each service, through surveys. The technical efficiency score, obtained using the classic DEA models and estimated quality indicators, is an estimator of the unknown population efficiency that would be obtained if in each one of the services, interviews from all their customers and all their providers were available. With the object of achieving the best precision in the estimate, we propose results to determine the sample size of customers and providers needed so that with their answers can achieve a fixed accuracy in the estimation of the population efficiency of these service-producing units through the use of a novel one bootstrap confidence interval. Using this bootstrap methodology and quality opinion indexes obtained from two surveys, one of doctors and another of patients, we analyze the efficiency in the health care system of Spain.

Suggested Citation

  • Jesús A. Tapia & Bonifacio Salvador, 2022. "Data envelopment analysis efficiency in the public sector using provider and customer opinion: An application to the Spanish health system," Health Care Management Science, Springer, vol. 25(2), pages 333-346, June.
    • Handle: RePEc:kap:hcarem:v:25:y:2022:i:2:d:10.1007_s10729-021-09589-7
    DOI: 10.1007/s10729-021-09589-7
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    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, April.
    2. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    3. De Witte, Kristof & Geys, Benny, 2013. "Citizen coproduction and efficient public good provision: Theory and evidence from local public libraries," European Journal of Operational Research, Elsevier, vol. 224(3), pages 592-602.
    4. Cristian Barra & Roberto Zotti, 2016. "Measuring Efficiency in Higher Education: An Empirical Study Using a Bootstrapped Data Envelopment Analysis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(1), pages 11-33, February.
    5. Bernardino Benito & José Solana & María-Rocío Moreno, 2014. "Explaining efficiency in municipal services providers," Journal of Productivity Analysis, Springer, vol. 42(3), pages 225-239, December.
    6. Christopher Hammond, 2002. "Efficiency in the provision of public services: a data envelopment analysis of UK public library systems," Applied Economics, Taylor & Francis Journals, vol. 34(5), pages 649-657.
    7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    8. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    9. Shiva Zandkarimkhani & Hassan Mina & Mehdi Biuki & Kannan Govindan, 2020. "A chance constrained fuzzy goal programming approach for perishable pharmaceutical supply chain network design," Annals of Operations Research, Springer, vol. 295(1), pages 425-452, December.
    10. Jesús Alberto Tapia & Bonifacio Salvador & Jesús María Rodríguez, 2018. "Data envelopment analysis in satisfaction survey research: sample size problem," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(7), pages 1096-1104, July.
    11. Assaf, A., 2010. "Bootstrapped scale efficiency measures of UK airports," Journal of Air Transport Management, Elsevier, vol. 16(1), pages 42-44.
    12. W. Diewert, 2011. "Measuring productivity in the public sector: some conceptual problems," Journal of Productivity Analysis, Springer, vol. 36(2), pages 177-191, October.
    13. O. B. Olesen & N. C. Petersen, 1995. "Chance Constrained Efficiency Evaluation," Management Science, INFORMS, vol. 41(3), pages 442-457, March.
    14. Chowdhury, Hedayet & Zelenyuk, Valentin, 2016. "Performance of hospital services in Ontario: DEA with truncated regression approach," Omega, Elsevier, vol. 63(C), pages 111-122.
    15. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, January.
    16. David J. Mayston, 2017. "Data envelopment analysis, endogeneity and the quality frontier for public services," Annals of Operations Research, Springer, vol. 250(1), pages 185-203, March.
    17. Shwartz, Michael & Burgess, James F. & Zhu, Joe, 2016. "A DEA based composite measure of quality and its associated data uncertainty interval for health care provider profiling and pay-for-performance," European Journal of Operational Research, Elsevier, vol. 253(2), pages 489-502.
    18. Førsund, Finn R., 2017. "Measuring effectiveness of production in the public sector," Omega, Elsevier, vol. 73(C), pages 93-103.
    19. Korhonen, Pekka & Tainio, Risto & Wallenius, Jyrki, 2001. "Value efficiency analysis of academic research," European Journal of Operational Research, Elsevier, vol. 130(1), pages 121-132, April.
    20. Laura Botega & Mônica Viegas Andrade & Gilvan Ramalho Guedes, 2020. "Brazilian hospitals’ performance: an assessment of the unified health system (SUS)," Health Care Management Science, Springer, vol. 23(3), pages 443-452, September.
    21. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    22. Mehmet Ceyhan & James Benneyan, 2014. "Handling estimated proportions in public sector data envelopment analysis," Annals of Operations Research, Springer, vol. 221(1), pages 107-132, October.
    23. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    24. Ying Li & Yung-ho Chiu & Tai-Yu Lin & Yun Yuan Huang, 2019. "Market share and performance in Taiwanese banks: min/max SBM DEA," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 233-252, July.
    25. David Mayston, 2015. "Analysing the effectiveness of public service producers with endogenous resourcing," Journal of Productivity Analysis, Springer, vol. 44(1), pages 115-126, August.
    26. W W Cooper & H Deng & Z Huang & S X Li, 2002. "Chance constrained programming approaches to technical efficiencies and inefficiencies in stochastic data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(12), pages 1347-1356, December.
    27. Ruggiero, John, 1996. "On the measurement of technical efficiency in the public sector," European Journal of Operational Research, Elsevier, vol. 90(3), pages 553-565, May.
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