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Hip fracture surgery efficiency in Israeli hospitals via a network data envelopment analysis

  • Simona Cohen-KadoshEmail author
  • Zilla Sinuany-Stern
Original Paper
  • 81 Downloads

Abstract

Data envelopment analysis (DEA) has been used previously for examining hospital efficiency, based on administrative data. Yet, previous DEA research devoted to quality assurance rarely considered medical processes or outcomes in efficiency studies. The goal of this study is to examine the relative efficiency of hip fracture surgery, based on clinical data reflecting medical process indicators and outcomes. To accomplish our goal, recent developments in DEA research were harnessed to model an output-oriented two-stage DEA network. The proposed DEA model has: two input variables reflecting the condition of the patient, fracture type and Charlson index; two intermediate variables reflecting clinical decisions, surgery within 48 h and usage of a drain for 1 day (rate); and two output variables reflecting the success of the surgery, survival rate after surgery and the rate of no infection. Using data from orthopedic wards in most of the acute Israeli hospitals (20 out of 22), no statistically significant correlation was found, either between the socio-economic index of patients who had hip fracture surgery and the relative efficiency scores produced by the two-stage network DEA model, or between efficiency and the geographical periphery status of the hospital. In addition to this, which points to a degree of social equality regarding hip fracture surgeries, we also compared the two-stage network model and related DEA models, providing several lemmas that represent the relationships between the various models mathematically.

Keywords

Efficiency Data envelopment analysis (DEA) Two-stage network DEA Socio-economic index (SEI) Geographical periphery status Hip fracture surgery Clinical quality assurance 

Notes

Acknowledgements

We thank the Quality Assurance Unit at Israel Ministry of Health for the data. We also thank the anonymous referees for their helpful comments which improve the paper.

References

  1. Aka-Zohar A et al (2015) The national quality indicators program in hospitals in Israel. https://www.health.gov.il/PublicationsFiles/Quality_National_Prog_2013-14(in Hebrew). Accessed 6 Sept 2017
  2. Alper D, Sinuany-Stern Z, Shinar D (2015) Evaluating the efficiency of local municipalities in providing traffic safety using the data envelopment analysis. Accid Anal Prev 78:39–50CrossRefGoogle Scholar
  3. Averbuch E, Avni S (2013) Coping with health inequalities. Management, Strategic and Economic Planning Division. Israel Ministry of Health. www.health.gov.il/PublicationsFiles/inequality-2013.pdf(in Hebrew). Accessed 20 July 2018
  4. Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 30:1078–1092CrossRefGoogle Scholar
  5. Ben-David D (2011) Report on the country state: society, economics and policy. Taub Research Center of Social policy in Israel. www.taubcenter.org.il(in Hebrew). Accessed 6 Sept 2017
  6. Ben-David N (2013) Opening the “black box”: efficiency of police stations using a multi-stage network DEA model. Master thesis, Industrial Engineering and Management, Ben Gurion University (in Hebrew) Google Scholar
  7. Bhattacharyya T, Freiberg AA, Mehta P, Katz JN, Ferris T (2009) Measuring the report card: the validity of pay-for-performance metrics in orthopedic surgery. Health Aff 28(2):526–532CrossRefGoogle Scholar
  8. Burk L et al (2013) Characterizing geographical units and their clustering according to the socio-economic level of their population in 2008. Central Bureau of Statistics of Israel publication no. 1530. www.cbs.gov.il(in Hebrew). Accessed 6 Sept 2017
  9. Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444CrossRefGoogle Scholar
  10. Chen Y, Cook WD, Li N, Zhu J (2009) Additive efficiency decomposition in two-stage DEA. Eur J Oper Res 196(3):1170–1176CrossRefGoogle Scholar
  11. Chen Y, Cook WD, Zhu J (2010) Deriving the DEA frontier for two-stage processes. Eur J Oper Res 202(1):138–142CrossRefGoogle Scholar
  12. Chernichovsky D, Regev E (2013) Trends in Israel’s health care system policy. Paper no. 2013.14. In: Ben-David D (ed) Report on the country state: society, economics and policy. Taub Research Center of Social policy in Israel. www.taubcenter.org.il. Accessed 20 July 2018
  13. Chernichovsky D, Friedman L, Sinuany-Stern Z, Hadad Y (2009) Hospitals efficiency in Israel via data envelopment analysis. Econ Q 56(2):119–142 (in Hebrew) Google Scholar
  14. Chilingerian JA, Sherman HD (2011) Health-care applications: from hospitals to physicians, from productive efficiency to quality frontiers. In: Cooper WW, Seiford LM, Zhu J (eds) Handbook on data envelopment analysis. Springer, New York, pp 445–493CrossRefGoogle Scholar
  15. Cohen-Kadosh S (2016) The relative efficiency of orthopedic wards in Israel: the case of fracture of femoral neck and the effect socio-economic status using data envelopment analysis. Master thesis, Industrial Engineering and Management, Ben Gurion University (in Hebrew) Google Scholar
  16. Cook WD, Zhu J, Bi G, Yang F (2010) Network DEA: additive efficiency decomposition. Eur J Oper Res 207(2):1122–1129CrossRefGoogle Scholar
  17. Färe R, Grosskopf S (1996) Productivity and intermediate products: a frontier approach. Econ Lett 50(1):65–70.  https://doi.org/10.1016/0165-1765(95)00729-6 CrossRefGoogle Scholar
  18. Färe R, Grosskopf S (2000) Network DEA. Socio Econ Plann Sci 34(1):35–49.  https://doi.org/10.1016/S0038-0121(99)00012-9 CrossRefGoogle Scholar
  19. Färe R, Grosskopf S, Ross P (1998) Malmquist productivity indexes: a survey of theory and practice. In: Färe R, Grosskopf S, Russell RR (eds) Index numbers: essays in honour of Sten Malmquist. Kluwer Academic Publishers, NorwellCrossRefGoogle Scholar
  20. Haleem S, Lutchman L, Mayahi R, Grice JE, Parker MJ (2008) Mortality following hip fracture: trends and geographical variations over the last 40 years. Inj Int J Care Inj 39(10):1157–1163CrossRefGoogle Scholar
  21. Hollingsworth B, Peacock SJ (2008) Efficiency measurement in health and health care delivery. Taylor and Francis, New-YorkCrossRefGoogle Scholar
  22. Hu F, Jiang C, Shen J, Tang P, Wang Y (2012) Preoperative predictors for mortality following hip fracture surgery: a systematic review and meta-analysis. Inj Int J Care Inj 43(2012):676–685CrossRefGoogle Scholar
  23. Kao C (2009) Efficiency decomposition in network data envelopment analysis: a relational model. Eur J Oper Res 192(3):949–962CrossRefGoogle Scholar
  24. Kao C (2014) Network data envelopment analysis: a review. Eur J Oper Res 239(1):1–16CrossRefGoogle Scholar
  25. Kao C, Hwang SN (2008) Efficiency decomposition in two-stage data envelopment analysis: an application to non-life insurance companies in Taiwan. Eur J Oper Res 185(1):418–429CrossRefGoogle Scholar
  26. Kawaguchi H, Tone K, Tsutsui M (2014) Estimation of the efficiency of Japanese hospitals using a dynamic and network data envelopment analysis model. Health Care Manag Sci 17(2):101–112CrossRefGoogle Scholar
  27. Keene GS, Parker MJ, Pryor GA (1993) Mortality and morbidity after hip fractures. BMJ 307:1248–1250CrossRefGoogle Scholar
  28. Le Manach Y, Collins G, Bhandari M, Bessissow A, Boddaert J, Khiami F, Chaudhry H, De Beer J, Riou B, Landais P, Winemaker M, Boudemaghe T, Devereaux PJ (2015) Outcomes after hip fracture surgery compared with elective total hip replacement. JAMA 314(11):1159CrossRefGoogle Scholar
  29. Lewis HF, Sexton TR (2004) Network DEA: efficiency analysis of organizations with complex internal structure. Comput Oper Res 31(9):1365–1410CrossRefGoogle Scholar
  30. Lu WM, Wang WK, Hung SW, Lu ET (2012) The effects of corporate governance on airline performance: Production and marketing efficiency perspectives. Transp Res Part E Logist Transp Rev 48(2):529–544CrossRefGoogle Scholar
  31. Ministry of Health Israel (1994) National Health Insurance (NHI) law https://www.knesset.gov.il/review/data/heb/law/kns13_nationalhealth.pdf(in Hebrew)
  32. Moja L, Piatti A, Pecoraro V, Ricci C, Virgili G, Salanti G, Banfi G (2012) Timing matters in hip fracture surgery: patients operated within 48 hours have better outcomes. A Meta-Analysis and Meta-Regression of over 190,000 Patients. https://moh-it.pure.elsevier.com/en/publications/timing-matters-in-hip-fracture-surgery-patients-operated-within-4. Accessed 20 July 2018‏
  33. Moran CG, Wenn RT, Sikand M, Taylor AM (2005) Early mortality after hip fracture: Is delay before surgery important? J Bone Joint Surg Am 87(3):483–489Google Scholar
  34. Mutter RL, Rosko MD, Greene WH, Wilson PW (2011) Translating frontiers into practice: taking the next steps toward improving hospital efficiency. Med Care Res Rev 68:3S–19SCrossRefGoogle Scholar
  35. Nijmeijer WS, Folbert EC, Vermeer M, Slaets JP, Hegeman JH (2016) Prediction of early mortality following hip fracture surgery in frail elderly: the almelo hip fracture score (AHFS). Inj Int J Care Inj 47:2138–2143CrossRefGoogle Scholar
  36. O’Neill L, Rauner M, Heidenberger K, Kraus M (2008) A cross-national comparison and taxonomy of DEA-based hospital efficiency studies. Soc Econ Plan Sci 42(3):158–189CrossRefGoogle Scholar
  37. Parker M (2010) Intracapsular fractures of the femoral neck. J Bones Joint Surg. http://www.boneandjoint.org.uk/content/intracapsular-fractures-femoral-neck. Accessed 6 Sept 2017
  38. Rauner MS, Behrens DA, Wild C (2005) Preface. Quantitative decision support for health services. Cent Eur J Oper Res 13(4):319–323Google Scholar
  39. Rauner MS, Schaffhauser-Linzatti MM, Bauerstter J (2015) Decision support system for social occupational injury insurance institutions: cost analysis and targeted resource allocation. Cent Eur J Oper Res 23(1):1–29CrossRefGoogle Scholar
  40. Sahin I, Ozcan Y, Ozgen H (2011) Assessment of hospital efficiency under health transformation program in Turkey. Cent Eur J Oper Res 9(1):19–37CrossRefGoogle Scholar
  41. Seiford LM, Zhu J (2002) Modeling undesirable factors in efficiency evaluation. Eur J Oper Res 142(1):16–20CrossRefGoogle Scholar
  42. Shemesh A et al (2011) Gaps in health and a social periphery. Ministry of Health Israel. http://www.health.gov.il/publicationsfiles/pearim2011.pdf. Accessed 6 Sept 2017
  43. Simões P, Marques R (2011) Performance and congestion analysis of the Portuguese hospital services. Cent Eur J Oper Res 19:39–63CrossRefGoogle Scholar
  44. Sinuany-Stern Z, Friedman L (1998) Rank scaling in the DEA context. Stud Reg Urban Plan 6:135–144Google Scholar
  45. Sinuany-Stern Z, Cohen-Kadosh S, Friedman L (2015) The relationship between the efficiency of orthopedic wards and the socio-economic status of their patients. Cent Eur J Oper Res 24(4):853–876CrossRefGoogle Scholar
  46. Sircar P, Godkar D, Mahgerefteh S, Chambers K, Niranjan S, Cucco R (2007) Morbidity and mortality among patients with hip fractures surgically repaired within and after 48 hours. Am J Ther 14(6):508–513CrossRefGoogle Scholar
  47. Tone K, Tsutsui M (2009) Network DEA: a slacks-based measure approach. Eur J Oper Res 197(1):243–252CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Industrial Engineering and ManagementBen-Gurion University of the NegevBeer-ShevaIsrael

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