The European Journal of Health Economics

, Volume 14, Issue 6, pp 979–994 | Cite as

How efficient are Greek hospitals? A case study using a double bootstrap DEA approach

Original Paper


The purpose of this study was to measure Greek hospital performance using different input–output combinations, and to identify the factors that influence their efficiency thus providing policy makers with valuable input for the decision-making process. Using a unique dataset, we estimated the productive efficiency of each hospital through a bootstrapped data envelopment analysis (DEA) approach. In a second stage, we explored, using a bootstrapped truncated regression, the impact of environmental factors on hospitals’ technical and scale efficiency. Our results reveal that over 80 % of the examined hospitals appear to have a technical efficiency lower than 0.8, while the majority appear to be scale efficient. Moreover, efficiency performance differed with inclusion of medical examinations as an additional variable. On the other hand, bed occupancy ratio appeared to affect both technical and scale efficiency in a rather interesting way, while the adoption of advanced medical equipment and the type of hospital improves scale and technical efficiency, correspondingly. The findings of this study on Greek hospitals’ performance are not encouraging. Furthermore, our results raise questions regarding the number of hospitals that should operate, and which type of hospital is more efficient. Finally, the results indicate the role of medical equipment in performance, confirming its misallocation in healthcare expenditure.


Greek hospital efficiency Primary healthcare Bootstrapped DEA Truncated regression analysis 

JEL Classification

C14 D24 I12 I18 


  1. 1.
    World Health Organization (WHO): National Health Accounts. Geneva (2010)Google Scholar
  2. 2.
    Greek Ministry of Health and Social Solidarity Report. Athens (2011)Google Scholar
  3. 3.
    Athanassopoulos, A.D., Gounaris, C., Sissouras, A.: A descriptive assessment of the cost and production efficiency of the general hospitals in Greece. Health Care Manag. Sci. 2, 97–106 (1999)PubMedCrossRefGoogle Scholar
  4. 4.
    Athanassopoulos, D., Gounaris, C.: Assessing the technical allocative efficiency of hospital operation in Greece and its resource allocation implication. Eur. J. Oper. Res. 133, 416–431 (2001)CrossRefGoogle Scholar
  5. 5.
    Giokas, D.I.: Greek hospitals: how well their resources are used Omega. Int. J. Manag. Sci. 29(1), 73–83 (2001)Google Scholar
  6. 6.
    Polyzos, N.M.: Striving towards efficiency in the Greek hospitals by reviewing case mix classifications. Health Policy 61(3), 305–328 (2002)PubMedCrossRefGoogle Scholar
  7. 7.
    Niakas, D., Theodorou, M., Liaropoulos, L.: Can privatising selected services benefit the public healthcare system? The Greek case. Appl. Health Econ. 4(3), 153–157 (2005)CrossRefGoogle Scholar
  8. 8.
    Kontodimopoulos, N., Nanos, P., Niakas, D.: Balancing efficiency of health services and equity of access in remote areas in Greece. Health Policy 76(1), 49–57 (2006)PubMedCrossRefGoogle Scholar
  9. 9.
    Aletras, V., Kontodimopoulos, N., Zagouldoudis, A., Niakas, D.: The short-term effect on technical and scale efficiency of establishing regional health systems and general management in Greek NHS hospitals. Health Policy 83(2), 236–245 (2007)PubMedCrossRefGoogle Scholar
  10. 10.
    Katharaki, M.: Approaching the management of hospital units with an operation research technique: the case of 32 Greek obstetric and gynaecology public units. Health Policy 85(1), 19–31 (2008)PubMedCrossRefGoogle Scholar
  11. 11.
    Flokou, A., Kontodimopoulos, N., Niakas, D.: Employing post-DEA Cross-evaluation and cluster analysis in a sample of Greek NHS Hospitals. J. Med. Syst. 35(5), 1–14 (2011)CrossRefGoogle Scholar
  12. 12.
    Dimas, G., Goula, A., Soulis, S.: Productive performance and its components in Greek public hospitals. Oper. Res. 12(1), 15–27 (2012)Google Scholar
  13. 13.
    Tsekouras, K., Papathanassopoulos, F., Kounetas, K., Pappous, G.: Does the adoption of new technology boost productive efficiency in the public sector? the case of ICUs system. Int. J. Prod. Econ. 128(1), 427–433 (2010)CrossRefGoogle Scholar
  14. 14.
    Androutsou, L., Geitona, M., Yfantopoulos, J.: Measuring efficiency and productivity across hospitals in the Regional Health Authority of Thessaly, in Greece. J. Health Manag. 13(2), 121–140 (2011)CrossRefGoogle Scholar
  15. 15.
    Hollingsworth, B., Dawson, P.J., Maniadakis, N.: Efficiency measurement of health care: a review of non-parametric methods and applications. Health Care Manag. Sci. 2(3), 161–172 (1999)PubMedCrossRefGoogle Scholar
  16. 16.
    Hollingsworth, B.: Non-parametric and parametric applications measuring efficiency in health care. Health Care Manag. Sci. 6(4), 203–218 (2003)PubMedCrossRefGoogle Scholar
  17. 17.
    Hollingsworth, B.: The measurement of efficiency and productivity of health care delivery. Health Econ. 17(10), 1107–1128 (2008)PubMedCrossRefGoogle Scholar
  18. 18.
    O’Neil, L., Rauner, M., Heidenberger, K., Kraus, M.: A cross-national comparison and taxonomy of DEA-based hospital efficiency studies. Soc. Econ. Plan. Sci. 42(3), 158–189 (2008)CrossRefGoogle Scholar
  19. 19.
    Fried, H.O., Lovell, C.A.K., Schmidt, S.C.: Efficiency and productivity. In: Fried, H.O., Lovell, C.A.K., Schmidt, S.C. (eds.) The measurement of productive efficiency and productivity growth, pp. 3–91. Oxford University Press, New York (2008)CrossRefGoogle Scholar
  20. 20.
    Chirikos, T.N., Sear, A.M.: Measuring hospital efficiency: a comparison of two approaches. Health Serv Res 34(6), 1389–1408 (2000)PubMedGoogle Scholar
  21. 21.
    Coelli, T.J., Prasada, D.S.R., Battese, G.E.: An Introduction to efficiency and productivity analysis. Kluwer, Boston (2005)Google Scholar
  22. 22.
    Simar, L., Wilson, P.W.: Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models. Manag. Sci. 44, 49–61 (1998)CrossRefGoogle Scholar
  23. 23.
    Simar, L., Wilson, P.W.: Estimating and bootstrapping Malmquist indices. Eur. J. Oper. Res. 115, 459–471 (1999)CrossRefGoogle Scholar
  24. 24.
    Simar, L., Wilson, P.W.: A general methodology for bootstrapping in nonparametric frontier models. J. Appl. Stat. 27, 779–802 (2000)CrossRefGoogle Scholar
  25. 25.
    Simar, L., Wilson, P.W.: Estimation and inference in two-stage, semi-parametric models of production processes. J. Econ. 136, 31–64 (2007)Google Scholar
  26. 26.
    Charnes, A., Cooper, W.W., Rhodes, E.: Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2, 429–444 (1978)CrossRefGoogle Scholar
  27. 27.
    Banker, R.D., Charnes, A., Cooper, W.W.: Some models for estimating technical and scale inefficiencies in Data Envelopment Analysis. Manag. Sci. 30, 1078–1092 (1984)CrossRefGoogle Scholar
  28. 28.
    Efron, B.: Bootstrap methods: another Look at the Jackknife. Ann. Stat. 7(1), 1–26 (1979)CrossRefGoogle Scholar
  29. 29.
    Efron, B.: The Jackknife, Bootstrap, and Other Resampling Plans. Siam monograph No. 38, CBMS-NSF. Philadelphia (1982)Google Scholar
  30. 30.
    Efron, B., Tibshirani, R.J.: An introduction to the bootstrap. Chapman & Hall, New York (1993)Google Scholar
  31. 31.
    Simar, L.: Estimating efficiencies from frontier models with panel data: a comparison of parametric, non-parametric and semi-parametric methods with bootstrapping. J. Prod. Anal. 3(1–2), 171–203 (1992)CrossRefGoogle Scholar
  32. 32.
    Assaf, A.: Bootstrapped scale efficiency measures of UK airports. J. Air Transp. Manag. 16, 42–44 (2010)CrossRefGoogle Scholar
  33. 33.
    Butler, J.R.G.: Hospital cost analysis. Kluwer, Boston (1995)CrossRefGoogle Scholar
  34. 34.
    Mutter, R., Valdmanis, V., Rosko, M.: High versus lower quality hospitals: a comparison of environmental characteristics and technical efficiency. Health Serv. Outcome Res. Meth 10(3–4), 134–153 (2010)CrossRefGoogle Scholar
  35. 35.
    Ozcan, Y.A., Lins, M.E., Lobo, M.S.C., da Silva, A.C.M., Fiszman, R., Pereira, B.B.: Evaluating the performance of Brazilian university hospitals. Ann. Oper. Res. 178(1), 247–261 (2010)CrossRefGoogle Scholar
  36. 36.
    Esroy, K., Kavuncubasi, S., Ozcan, A.Y., Harris, M.J.: Technical efficiencies of Turkish hospitals: DEA approach. J. Med. Syst. 21(2), 67–74 (1997)CrossRefGoogle Scholar
  37. 37.
    Kirigia, J.M., Emrouznejad, A., Cassoma, B., Asbu, E.Z., Barry, S.A.: Performance assessment method for hospitals: the case of municipal hospitals in Angola. J. Med. Syst. 32(6), 509–519 (2008)PubMedCrossRefGoogle Scholar
  38. 38.
    Sahin, I., Ozcan, Y.A., Ozgen, H.: Assessment of hospital efficiency under health transformation program in Turkey Cent. Eur. J. Oper. Res. 19(1), 19–37 (2011)CrossRefGoogle Scholar
  39. 39.
    Ozcan, Y.A., Luke, R.D.: A national study of the efficiency of hospitals in urban markets. Health Serv. Res. 27(6), 719–739 (1993)PubMedGoogle Scholar
  40. 40.
    Watcharasriroj, B., Tang, J.C.S.: The effects of size and information technology on hospital efficiency. J. High Tech. Manag. Res. 15(1), 1–16 (2004)CrossRefGoogle Scholar
  41. 41.
    Kuntz, L., Scholtes, S., Vera, A.: Incorporating efficiency in hospital-capacity planning in Germany. Eur. J. Health. Econ. 8, 213–223 (2007)PubMedCrossRefGoogle Scholar
  42. 42.
    Ludwig, M., Van Merode, F., Groot, W.: Principal agent relationships and the efficiency of hospitals. Eur. J. Health Econ. 11(3), 291–304 (2010)PubMedCrossRefGoogle Scholar
  43. 43.
    Zuckerman, S., Hadley, J., Iczzoni, L.: Measuring hospital efficiency with frontier cost functions. J. Health Econ. 13, 255–280 (1994)PubMedCrossRefGoogle Scholar
  44. 44.
    Puenpatom, R.A., Rosenman, R.: Efficiency of Thai provincial public hospitals during the introduction of universal health coverage using capitation. Health Care Manag. Sci. 11, 319–338 (2008)PubMedCrossRefGoogle Scholar
  45. 45.
    Argote, L., Ingram, P.: Knowledge transfer: a basis for competitive advantage in firms. Organ. Behav. Hum. Dec 82(1), 150–169 (2000)CrossRefGoogle Scholar
  46. 46.
    Brown, H.S., Pagan, J.A.: Managed care and the scale efficiency of US Hospitals. Int. J. Health Care Fi. 6, 278–289 (2006)CrossRefGoogle Scholar
  47. 47.
    Jovanovic, B., Nyarko, Y.: Learning by doing and the choice of technology. Econometrica 64, 43–60 (1996)CrossRefGoogle Scholar
  48. 48.
    Silverman, B.W.: Density estimation for statistics and data analysis. In: Monographs on Statistics and Applied Probability. Chapman and Hall, London (1986)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of EconomicsUniversity of PatrasPatrasGreece
  2. 2.Biomedical Engineering Unit, Department of Medical PhysicsUniversity of PatrasPatrasGreece

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