Health Services and Outcomes Research Methodology

, Volume 19, Issue 4, pp 215–240 | Cite as

Evaluating efficiency of English acute foundation trusts under system reform: a two-stage DEA approach

  • Khanh Quoc ThaiEmail author
  • Masayoshi Noguchi


The English healthcare sector underwent extensive system reform over the period from 2010 to 2015, aimed principally at improving technical efficiency. This paper examines the effect of the reforms on foundation trusts in England with particular emphasis on technical efficiency. By employing data envelopment analysis (DEA) and a second-stage regression, we found evidence of an overall improvement in efficiency, notwithstanding some fluctuations. Specifically, we found that bed utilization had positive and statistically significant association with the efficiency of acute foundation trusts; suggesting that better management of patient flows and bed utilization might be expected to improve hospital efficiency. We also found evidence to suggest that efficiency might also be improved through better management of staff numbers, optimizing liquidity, and better utilization of assets such as buildings and information technology.


Efficiency Data envelopment analysis (DEA) Two-stage analysis English foundation trusts Hospital bed occupancy 



The authors would like to show our gratitude to Professor Paul Rouse, University of Auckland, New Zealand, and Dr. Joseph Drew, University of Technology Sydney, Australia and the two anonymous reviewers for their dedicated assistance and constructive comments that greatly improved the quality of the manuscript.


This study was funded by the advanced research programme (Kodo Kenkyuu) sponsored by Tokyo Metropolitan Government.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


  1. Aigner, D., Lovell, C.A.K., Schmidt, P.: Formulation and estimation of stochastic frontier production function models. J. Econometrics 6, 21–37 (1977)CrossRefGoogle Scholar
  2. Applyby, J., Baird, B., Thompson, J., Jabbal, J.: The NHS under the coalition government. Part two: NHS performance. (2015). Accessed 28 May 2018
  3. Aragon Aragon, M.J., Castelli, A., Gaughan, J.: Hospital trusts productivity in the English NHS: uncovering possible drivers of productivity variations. PLoS ONE 12(8), 1–14 (2017)CrossRefGoogle Scholar
  4. Bain, C.A.: Myths of ideal hospitals occupancy. Med. J. Aust. 192(1), 42–43 (2010)PubMedCrossRefGoogle Scholar
  5. Baker, B.C.: NHS indicators: England, October 2017. (2017). Accessed 27 June 2018
  6. Banker, R.D., Charnes, A., Cooper, W.W.: Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage. Sci. 30(9), 1078–1092 (1984)CrossRefGoogle Scholar
  7. Banker, R.D., Natarajan, R.: Evaluating contextual variables affecting productivity using data envelopment analysis. Oper. Res. 56(1), 48–58 (2008)CrossRefGoogle Scholar
  8. Barnum, D.T., Walton, S.M., Shields, K.L., Schumock, G.T.: Measuring hospital efficiency with data envelopment analysis: nonsubstitutable vs. substitutable inputs and outputs. J. Med. Syst. 35(6), 1393–1401 (2011)PubMedCrossRefGoogle Scholar
  9. Berta, P., Callea, G., Martini, G., Vittadini, G.: The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: a population-based investigation. Econ. Model. 27(4), 812–821 (2010)CrossRefGoogle Scholar
  10. Cantor, V.J.M., Poh, K.L.: Integrated analysis of healthcare efficiency: a systematic review. J. Med. Syst. 42(8), 1–23 (2018)Google Scholar
  11. Castelli, A., Street, A., Verzulli, R., Ward, P.: Examining variations in hospital productivity in the English NHS. Eur. J. Health Econ. 16(3), 243–254 (2015)PubMedCrossRefGoogle Scholar
  12. Charnes, A., Cooper, W., Lewin, A., Seiford, L.: Data Envelopment Analysis: Theory, Methodology, and Application. Springer, New York (1994)CrossRefGoogle Scholar
  13. Charnes, A., Cooper, W.W., Rhodes, E.: Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2, 429–444 (1978)CrossRefGoogle Scholar
  14. Chilingerian, J., Sherman, H.D.: Health-care applications: from hospitals to physicians, from productive efficiency to quality frontiers. In: Cooper, W., Seiford, L.M., Zhu, J. (eds.) Handbook on Data Envelopment Analysis, pp. 445–493. Springer, Boston, MA (2011)CrossRefGoogle Scholar
  15. Chou, T.-H., Ozcan, Y.A., White, K.R.: Technical and scale efficiencies of Catholic hospitals: does a system value of stewardship matter? In: Tànfani, E., Testi, A. (eds.) Advanced Decision Making Methods Applied to Health Care, pp. 83–102. Springer-Verlag Italia, Milan (2012)CrossRefGoogle Scholar
  16. Clover, B.: Monitor directors say FTs “opportunistic” in acquiring community services. (2011). Accessed 21 June 2018
  17. Coelli, T.J., Rao, D.S.P., O’Donnell, C.J., Battese, G.E.: An introduction to efficiency and productivity analysis. Springer, Berlin (2005)Google Scholar
  18. Crawford, R., Stoye, G.: Challenges for health spending. (2015). Accessed 4 March 2018
  19. Cylus, J., Richardson, E., Findley, L., Longley, M., O’Neill, C., Steel, D.: United Kingdom: health system review. Health Syst. Transit. 17(5), 1–125 (2015)PubMedGoogle Scholar
  20. Czypionka, T., Kraus, M., Mayer, S., Röhrling, G.: Efficiency, ownership, and financing of hospitals: the case of Austria. Health Care Manag. Sci. 17(4), 331–347 (2013)PubMedCrossRefGoogle Scholar
  21. Department of Health: The operating framework 2011/12. (2010). Accessed 21 June 2018
  22. Department of Health: A simple guide to payment by results. (2012a). Accessed 27 June 2018
  23. Department of Health: Overview of the health and social care act fact sheet. (2012b). Accessed 3 April 2018
  24. Ding, D.X.: The effect of experience, ownership and focus on productive efficiency: a longitudinal study of U.S. hospitals. J. Oper. Manag. 32(1–2), 1–14 (2014)CrossRefGoogle Scholar
  25. Dong, G.N.: Earning management in US hospitals. J. Health Hum. Serv. Adm. 39(1), 41–71 (2016)PubMedGoogle Scholar
  26. Dyson, R.G., Allen, R., Camanho, A.S., Podinovski, V.V., Sarrico, C.S., Shale, E.A.: Pitfalls and protocols in DEA. Eur. J. Oper. Res. 132(2), 245–259 (2001)CrossRefGoogle Scholar
  27. Edwards, A.N.: Perspectives NHS buildings: obstacle or opportunity ? (2011). Accessed 10 Aug 2018
  28. Emrouznejad, A., Yang, G.L.: A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Econ. Plan. Sci. 61, 4–8 (2018)CrossRefGoogle Scholar
  29. Ferrari, A.: Market oriented reforms of health services: a non-parametric analysis. Serv. Ind. J. 26(1), 1–13 (2006)CrossRefGoogle Scholar
  30. Ferreira, D.C., Marques, R.C., Nunes, A.M.: Economies of scope in the health sector: the case of Portuguese hospitals. Eur. J. Oper. Res. 266(2), 716–735 (2018)CrossRefGoogle Scholar
  31. Fixler, T., Paradi, J.C., Yang, X.: A data envelopment analysis approach for measuring the efficiency of Canadian acute care hospitals. Health Serv. Manag. Res. 27(3–4), 57–69 (2014)CrossRefGoogle Scholar
  32. Førsund, F.R.: Economic interpretations of DEA. Socio-Econ. Plan. Sci. 61(1), 9–15 (2018)CrossRefGoogle Scholar
  33. Gebicki, M., Mooney, E., Chen, S.J., Mazur, L.M.: Evaluation of hospital medication inventory policies. Health Care Manag. Sci. 17(3), 215–229 (2014)PubMedCrossRefGoogle Scholar
  34. Giancotti, M., Guglielmo, A., Mauro, M.: Efficiency and optimal size of hospitals: results of a systematic search. PLoS ONE 12(3), 1–40 (2017)CrossRefGoogle Scholar
  35. HM Treasury: Public expenditure statistical analyses (PESA). (2017). Accessed 30 March 2018
  36. Hoff, A.: Second stage DEA: comparison of approaches for modelling the DEA score. Eur. J. Oper. Res. 181(1), 425–435 (2007)CrossRefGoogle Scholar
  37. Hollingsworth, B.: The measurement of efficiency and productivity of health care delivery. Health Econ. 17(10), 1107–1128 (2008)PubMedCrossRefGoogle Scholar
  38. Hollingsworth, B., Parkin, D.: Efficiency and productivity change in the English National Health Service: can data envelopment analysis provide a robust and useful measure? J. Health Serv. Res. Policy 8(4), 230–236 (2003)PubMedCrossRefGoogle Scholar
  39. Jacobs, R.: Alternative methods to examine hospital efficiency: data envelopment analysis and stochastic frontier analysis. Health Care Manag. Sci. 4(2), 103–115 (2001)PubMedCrossRefGoogle Scholar
  40. Jacobs, R., Smith, P., Street, A.: Measuring Efficiency in Health Care: Analytic Techniques and Health Policy. Cambridge University Press, Cambridge (2006)CrossRefGoogle Scholar
  41. Jindal, R.P., Gauri, D.K., Singh, G., Nicholson, S.: Factors influencing hospital readmission penalties: are they really under hospitals’ control ? Decis. Support Syst. 110, 58–70 (2018)CrossRefGoogle Scholar
  42. Jones, R.: Bed occupancy in acute and mental health hospitals. Health Serv. J. 111(5752), 28–31 (2001)PubMedGoogle Scholar
  43. Jones, R.: Hospital bed occupancy demystified. Br. J. Healthc. Manag. 17(6), 242–248 (2011)CrossRefGoogle Scholar
  44. Kaya Samut, P., Cafrı, R.: Analysis of the efficiency determinants of health systems in OECD countries by DEA and panel tobit. Soc. Indic. Res. 129(1), 113–132 (2016)CrossRefGoogle Scholar
  45. Keegan, A.D.: Hospital bed occupancy: more than queuing for a bed. Med. J. Aust. 193(5), 291–293 (2010)PubMedCrossRefGoogle Scholar
  46. Kelly, E., Soye, G., Vera-hernadez, M.: Public hospital spending in England: evidence from National Health Service administrative records. Fiscal Stud. 37(3), 433–459 (2016)CrossRefGoogle Scholar
  47. Kirigia, J.M., Asbu, E.Z.: Technical and scale efficiency of public community hospitals in Eritrea: an exploratory study. Health Econ. Rev. 3(1), 1–16 (2013)CrossRefGoogle Scholar
  48. Kohl, S., Schoenfelder, J., Fügener, A., Brunner, J.O.: The use of data envelopment analysis (DEA) in healthcare with a focus on hospitals. Health Care Manag. Sci. (2018). CrossRefPubMedGoogle Scholar
  49. Kounetas, K., Papathanassopoulos, F.: How efficient are Greek hospitals? A case study using a double bootstrap DEA approach. Eur. J. Health Econ. 14(6), 979–994 (2013)PubMedCrossRefGoogle Scholar
  50. Lanfond, S.: Funding overview: current NHS spending in England. The Health Foundation. (2015). Accessed 4 Apr 2018
  51. Lewis, R., Edwards, N.: Improving length of stay: what can hospitals do ? (2015). Accessed 20 June 2018
  52. Licchetta, M., Stelmach, M.: Fiscal sustainability analytical paper: fiscal sustainability and public spending on health. (2016). Accessed 17 March 2018
  53. Lord Carter of Coles: Operational productivity and performance in English NHS acute hospitals. (2016). Accessed 11 June 2018
  54. Lovell, C.A.K., Walters, L.C., Wood, L.L.: Stratified models of education production using modified DEA and regression analysis. In: Charnes, A., Cooper, W., Lewin, A., Seiford, L. (eds.) Data Envelopment Analysis: Theory, Methodology, and Application, pp. 329–351. Springer, New York (1994)CrossRefGoogle Scholar
  55. Maniadakis, N., Thanassoulis, E.: Assessing productivity changes in UK hospitals reflecting technology and input prices. Appl. Econ. 32(12), 1575–1589 (2000)CrossRefGoogle Scholar
  56. Marshall, L., Charlesworth, A., Hurst, J.: The NHS payment system: evolving policy and emerging evidence Research report. (2014). Accessed 27 June 2018
  57. Matranga, D., Bono, F., Casuccio, A., Firenze, A., Marsala, L., Giaimo, R.: Evaluating the effect of organization and context on technical efficiency: a second-stage DEA analysis of Italian hospitals. Epidemiol. Biostat. Public Health 11(1), 1–11 (2014)Google Scholar
  58. Mccallion, G., Glass, J.C., Jackson, R., Kerr, C.A., Mckillop, D.G.: Investigating productivity change and hospital size: a nonparametric frontier approach. Appl. Econ. 32(2), 161–174 (2000)CrossRefGoogle Scholar
  59. McDonald, J.: Using least squares and Tobit in second stage DEA efficiency analyses. Eur. J. Oper. Res. 197(2), 792–798 (2009)CrossRefGoogle Scholar
  60. Monitor: 2015/16 National tariff payment system: a consultation notice. (2015a). Accessed 27 June 2018
  61. Monitor: For action—tariff arrangements for your 2015/16 NHS activity. (2015b). Accessed 27 June 2018
  62. Monitor: NHS foundation trust accounts. (2017). Accessed 27 Dec 2017
  63. Morris, J.: The growing problem of treatment waiting times. (2018). Accessed 20 June 2018
  64. National NHS Staff Survey Co-ordination Centre: NHS staff survey. (2018). Accessed 8 Mar 2018
  65. Nedelea, I.C., Fannin, J.M.: Technical efficiency of critical access hospitals: an application of the two-stage approach with double bootstrap. Health Care Manag. Sci. 16(1), 27–36 (2013)PubMedCrossRefGoogle Scholar
  66. NHS Choice: The NHS in England. (2016). Accessed 18 June 2018
  67. NHS England: Five years forward review. (2014). Accessed 31 July 2018
  68. NHS England: Bed availability and overnight occupancy. (2017a). Accessed 20 Dec 2017
  69. NHS England: Referral to treatment (RTT) waiting times statistics for consultant-led elective care: 2016–17 Annual Report. NHS England. (2017b). Accessed 20 June 2018
  70. NHS Improvement: National schedule of reference costs. (2017a). Accessed 3 Jan 2018
  71. NHS Improvement: NHS foundation trusts: consolidated accounts 2016/17. (2017b). Accessed 18 July 2018
  72. NICE: Chapter 39 Bed occupancy. (2017). Accessed 15 Apr 2018
  73. Nuffieldtrust: Length of stay case study. (2014). Accessed 27 June 2018
  74. O’Neill, L., Rauner, M., Heidenberger, K., Kraus, M.: A cross-national comparison and taxonomy of DEA-based hospital efficiency studies. Socio-Econ. Plan. Sci. 42(3), 158–189 (2008)CrossRefGoogle Scholar
  75. OECD/EU: Health at a glance: Europe 2016—State of Health in the EU Cycle. (2016). Accessed 11 June 2018
  76. OECD: OECD Health Statistics 2017. (2017). Accessed 20 June 2018
  77. Ozcan, Y.A.: Health Care Benchmarking and Performance Evaluation: An Assessment Using Data Envelopment Analysis (DEA). Springer, NewYork (2014)Google Scholar
  78. Powell, M., Dawson, J., Topakas, A., Durose, J., Fewtrell, C.: Staff satisfaction and organisational performance: evidence from a longitudinal secondary analysis of the NHS staff survey and outcome data. Health Serv. Deliv. Res. 2(50), 1–306 (2014)CrossRefGoogle Scholar
  79. Powell, M., Mannion, R.: “Groundhog Day”: the Coalition government’s quality and safety reforms. In: Exworthy, M., Mannion, R., Powell, M. (eds.) Dismantling the NHS? Evaluating the impact of health reforms, pp. 323–342. Policy Press, Bristol (2016)CrossRefGoogle Scholar
  80. Powell, T.: (2016) The structure of the NHS in England. (2016). Accessed 6 Dec 2017
  81. Roberts, A., Marshall, L., Charlesworth, A.: A decade of austerity? (2012). Accessed 4 Apr 2018
  82. Robertson, R., Wenzel, L., Thompson, J., Charles, A.: Understanding NHS financial pressures—how are they affecting patient care? (2017). Accessed 4 Dec 2017
  83. Şamiloğlu, F., Akgün, Aİ.: The relationship between working capital management and profitability: evidence from Turkey. Bus. Econ. Res. J. 7(2), 1–14 (2016)CrossRefGoogle Scholar
  84. Simar, L., Wilson, P.W.: Estimation and inference in two-stage, semi-parametric models of production processes. J. Econom. 136(1), 31–64 (2007)CrossRefGoogle Scholar
  85. Simar, L., Wilson, P.W.: Two-stage DEA: caveat emptor. J. Prod. Anal. 36(2), 205–218 (2011)CrossRefGoogle Scholar
  86. Sorenson, C., Drummond, M., Khan, B.B.: Medical technology as a key driver of rising health expenditure: disentangling the relationship. ClinicoEcon. Outcomes Res. 5(1), 223–234 (2013)PubMedPubMedCentralCrossRefGoogle Scholar
  87. The King’s Fund: How the NHS is funded. (2017). Accessed 18 June 2018
  88. Umobong, A.: Assessing the impact of liquidity and profitability ratios on growth of profits in pharmaceutical firms in Nigeria. Eur. J. Account. Audit. Finance Res. 3(10), 97–114 (2015)Google Scholar
  89. Valdmanis, V., Rosko, M., Mancuso, P., Tavakoli, M., Farrar, S.: Measuring performance change in Scottish hospitals: a Malmquist and times-series approach. Health Serv. Outcomes Res. Methods 17(2), 113–126 (2016)CrossRefGoogle Scholar
  90. Varabyova, Y., Schreyögg, J.: International comparisons of the technical efficiency of the hospital sector: panel data analysis of OECD countries using parametric and non-parametric approaches. Health Policy 112(1–2), 70–79 (2013)PubMedCrossRefGoogle Scholar
  91. Verzulli, R., Jacobs, R., Goddard, M.: Autonomy and performance in the public sector: the experience of English NHS hospitals. Eur. J. Health Econ. 19(4), 607–626 (2018)PubMedCrossRefGoogle Scholar
  92. Wachter, R., Slee, A., Brailer, D.: Making IT work: harnessing the power of health information technology to improve care in England. (2016). Accessed 5 Mar 2018

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Tokyo Metropolitan UniversityTokyoJapan

Personalised recommendations