Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

DEA-Like Efficiency Ranking of Regional Health Systems in Spain

  • 487 Accesses

  • 8 Citations

Abstract

The last decades have witnessed an increasing international concern in assessing how efficiently health care resources are used in producing health. At a country level, comparing the efficiency of regional health systems and ranking the regions accordingly promotes transparency policies and represents an important incentive for the design and implementation of specific programs aimed at improving the quality of health care services within the country. The use of data envelopment analysis (DEA) as a tool for efficiency analysis in the health sector is well-established, but its use with a ranking purpose is discouraged due to lack of discrimination and comparability issues. Using data from the competent health authority in Spain, the purpose of this study is to assess the efficiency of the regional health systems in Spain and identify those regions that are using their health care inputs more efficiently than others, given the observed level of health outcomes. To this aim, a DEA-based model that operates under a common weights basis is used in order to improve discrimination and establish a common scale for a proper comparison of the regional health systems in Spain that can be subsequently ranked by their efficiency score.

This is a preview of subscription content, log in to check access.

Fig. 1

References

  1. Adler, N., Friedman, L., & Sinuany-Stern, Z. (2002). Review of ranking methods in the data envelopment analysis context. European Journal of Operational Research, 140, 249–265.

  2. Afonso, A., & St. Aubyn, M. (2011). Assessing health efficiency across countries with a two-step and bootstrap analysis. Applied Economics Letters, 18, 1427–1430.

  3. Afonso, A., & St. Aubyn, M. (2005). Non-parametric approaches to education and health efficiency in OECD countries. Journal of Applied Economics, VIII, 227–246.

  4. Alexander, C. A., Busch, G., & Stringer, K. (2003). Implementing and interpreting a data envelopment analysis model to assess the efficiency of health systems in developing countries. IMA Journal of Management Mathematics, 14, 49–63.

  5. Angulo-Meza, L., & Lins, M. P. E. (2002). Review of methods for increasing discrimination in data envelopment analysis. Annals of Operations Research, 11, 225–242.

  6. Bhat, V. N. (2005). Institutional arrangements and efficiency of health care delivery systems. European Journal of Health Economics, 50, 215–222.

  7. Carrillo, M., & Jorge, J. M. (2016). A multiobjective DEA approach to ranking alternatives. Expert Systems with Applications, 50, 130–139.

  8. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.

  9. Chen, Y. W., Larbani, M., & Chang, Y. P. (2009). Multiobjective data envelopment analysis. Journal of the Operational Research Society, 60, 1556–1566.

  10. CIHI-Canadian Institute for Health Information. (2014). Measuring the level and determinants of health system efficiency in Canada. Technical Report. https://secure.cihi.ca/free_products/HSE_TechnicalReport_EN_web.pdf. Accessed January 18. 2016.

  11. Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. New York: Springer.

  12. de Cos, P. H., & Moral-Benito, E. (2014). Determinants of health-system efficiency: Evidence from OECD countries. International Journal of Health Care Finance and Economics, 14, 69–93.

  13. Deidda, M., Lupiáñez-Villanueva, F., Codagnone, C., & Maghiros, I. (2014). Using data envelopment analysis to analyse the efficiency of primary care units. Journal of Medical Systems, 38, 122.

  14. Despotis, D. K. (2002). Improving the discriminating power of DEA focus on globally efficient units. Journal of the Operational Research Society, 53, 314–323.

  15. Dyson, R. G., Allen, R., Camanho, A. S., Podinovski, V. V., Sarrico, C. S., & Shale, E. A. (2001). Pitfalls and protocols in DEA. European Journal of Operational Research, 132, 245–259.

  16. Emrouznejad, A., Parker, B. R., & Tavares, G. (2008). Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA. Socio-Economic Planning Sciences, 42, 151–157.

  17. European Commission. (2010). Joint report on health systems. European Economy, Occasional Papers 74. http://ec.europa.eu/economy_finance/publications/occasional_paper/2010/pdf/ocp74_en.pdf. Accessed September 28, 2015.

  18. FADSP-Federación de Asociaciones para la Defensa de la Sanidad Pública. (2015). XII Informe Los Servicios Sanitarios de las CCAA. http://www.fadsp.org/index.php/observatorio-ccaa. Accessed January 25, 2016.

  19. Figueras, J., McKee, M., Lessof, S., Duran A., & Menabde, N. (2008). Health systems, health and wealth: Assessing the case for investing in health systems. Background document for the WHO European Ministerial Conference on Health Systems, Health and Wealth, Tallin, June 2008. http://www.euro.who.int/__data/assets/pdf_file/0017/91430/E93699.pdf. Accessed November 26, 2015.

  20. García, S., Abadía, M. B., Durán, A., Hernández-Quevedo, C., & Bernal, E. (2010). Spain: Health system review. Health Systems in Transition, 12(4), 1–295.

  21. Hadad, S., Hadad, Y., & Simon-Tuval, T. (2013). Determinants of healthcare system’s efficiency in OECD countries. European Journal of Health Economics, 14, 253–265.

  22. Hollingsworth, B. (2003). Non-parametric and parametric applications measuring efficiency in health care. Health Care Management Science, 6, 203–218.

  23. Hollingsworth, B. (2008). The measurement of efficiency and productivity of health care delivery. Health Economics, 17, 1107–1128.

  24. Jacobs, R., Smith, P. C., & Street, A. (2006). Measuring efficiency in health care: Analytic techniques and health policy. UK: Cambridge University Press.

  25. Joumard, I., André, C., & Nicq, C. (2010). Health care systems: Efficiency and institutions. Economics Department Working Papers No. 769. OECD Publishing. doi:10.1787/18151973

  26. Joumard, I., André, C., Nicq, C., & Chatal, O. (2008). Health status determinants: Lifestyle, environment, health care resources and efficiency. OECD Economics Department Working Papers No. 627, OECD Publishing. doi:10.1787/240858500130

  27. Kao, C., & Hung, H. (2005). Data envelopment analysis with common weights: The compromise solution approach. Journal of the Operational Research Society, 56, 1196–1203.

  28. Kathunia, V., & Sankar, D. (2005). Inter-state disparities in health outcomes in rural India: An analysis using a stochastic production frontier approach. Development Policy Review, 23(2), 145–163.

  29. Liu, F. H. F., & Peng, H. H. (2008). Ranking of units on the DEA frontier with common weights. Computers and Operations Research, 35, 1624–1637.

  30. Mariano, E. B., Sobreiro, V. A., & Rebelatto, D. A. N. (2015). Human development and data envelopment analysis: A structured literature review. Omega, 54, 33–49.

  31. Martić, M., & Savić, G. (2001). An application of DEA for comparative analysis and ranking of regions in Serbia with regards to social-economic development. European Journal of Operational Research, 132, 343–356.

  32. MSSSI: Ministerio de Sanidad, Servicios Sociales e Igualdad. (2014). Indicadores Clave del Sistema Nacional de Salud (INCLASNS. Versión 2). http://inclasns.msssi.es/doc/Metodologia_INCLASNS_V2.pdf. Accessed September 28, 2015.

  33. Navarro, C., Karlsdotter, K., Martín, J. J., Puerto, M., & Herrero, L. (2011). Medida de la eficiencia de los hospitales del Servicio Andaluz de Salud mediante técnicas no frontera. Indicadores sintéticos de eficiencia. Málaga: XVIII Encuentro de Economía Pública.

  34. Nebot, M., & Fernández, E. (2009). Evaluación del impacto de la Ley de medidas sanitarias frente al tabaquismo. Grupo de Trabajo sobre Tabaquismo de la Sociedad Española de Epidemiología. Ministerio de Sanidad y Política Social. Barcelona. http://www.seepidemiologia.es/monografia.pdf. Accessed January 18, 2016.

  35. OECD. (2014). Health at a glance: Europe 2014. Paris: OECD Publishing. doi:10.1787/23056088.

  36. O’Neill, L., Rauner, M., Heidenberger, K., & Kraus, M. (2008). A cross-national comparison and taxonomy of DEA-based hospital efficiency studies. Socio-Economic Planning Sciences, 42, 158–189.

  37. Or, Z. (2000). Determinants of health outcomes in industrialised countries: A pooled, cross-country, time-series analysis. OECD Economic Studies,. doi:10.1787/16097491.

  38. Parrish, R. G. (2010). Measuring population health outcomes. Preventing Chronic Disease, 7(4), A71. http://www.cdc.gov/pcd/issues/2010/jul/10_0005.htm. Accessed September 23, 2015.

  39. Pelone, F., Kringos, D. S., Romaniello, A., Archibugi, M., Salsiri, C., & Ricciardi, W. (2015). Primary care efficiency measurement using data envelopment analysis: A systematic review. Journal of Medical Systems, 39, 156.

  40. Pinillos, M., & Antoñanzas, F. (2002). La Atención Primaria de Salud: descentralización y eficiencia. Gaceta Sanitaria, 16(5), 401–407.

  41. Qi, X. G., & Guo, B. (2014). Determining common weights in data envelopment analysis with Shannon’s Entropy. Entropy, 16, 6394–6414.

  42. Retzlaff-Roberts, D., Chang, C. F., & Rubin, R. M. (2004). Technical efficiency in the use of health care resources: A comparison of OECD countries. Health Policy, 69, 55–72.

  43. Rodríguez-López, F., & Sánchez-Macías, J. I. (2004). Especialización y eficiencia en el sistema hospitalario español. Cuadernos Económicos ICE, 67, 27–47.

  44. Roll, Y., Cook, W. D., & Golany, B. (1991). Controlling factor weights in data envelopment analysis. IIE Transactions, 23(1), 2–9.

  45. Roll, Y., & Golany, B. (1993). Alternate methods of treating factor weights in DEA. OMEGA, 21(1), 99–109.

  46. Samut, P. K., & Cafri, R. (2015). Analysis of the efficiency determinants of health systems in OECD countries by DEA and panel tobit. Social Indicators Research,. doi:10.1007/s11205-015-1094-3.

  47. Sinuany-Stern, Z., & Friedman, L. (1998). DEA and the discriminant analysis of ratios for ranking units. European Journal of the Operational Research, 111, 470–478.

  48. Spinks, J., & Hollingsworth, B. (2009). Cross-country comparisons of technical efficiency of health production: A demonstration of pitfalls. Applied Economics, 42, 417–427.

  49. Wang, Y. M., & Chin, K. S. (2010). A neutral DEA model for cross-efficiency evaluation and its extension. Expert Systems with Applications, 37, 3666–3675.

  50. Wang, Y. M., Luo, Y., & Lan, Y. (2011). Common weights for fully ranking decision making units by regression analysis. Expert Systems with Applications, 38, 9122–9128.

  51. WHO-World Health Organization. (2000). The world health report 2000. Health systems: Improving performance. Geneva: World Health Organization.

  52. Wong, Y. H. B., & Beasley, J. E. (1990). Restricting weight flexibility in data envelopment analysis. Journal of the Operational Research Society, 41, 829–835.

  53. Zeleny, M. (1982). Multiple criteria decision making. New York: McGraw Hill.

  54. Zohrehbandian, M., Makui, A., & Alinezhad, A. (2010). A compromise solution approach for finding common weights in DEA: An improvement to Kao and Hung’s approach. Journal of the Operational Research Society, 61, 604–610.

Download references

Acknowledgments

The authors are sincerely grateful to two anonymous referees whose suggestions have substantially improved the final version of this paper.

Author information

Correspondence to Marianela Carrillo.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Carrillo, M., Jorge, J.M. DEA-Like Efficiency Ranking of Regional Health Systems in Spain. Soc Indic Res 133, 1133–1149 (2017). https://doi.org/10.1007/s11205-016-1398-y

Download citation

Keywords

  • Data envelopment analysis
  • Health system efficiency
  • Common weights
  • Ranking