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Analysis on Efficiency and Productivity Changes of Regional Public Hospitals in Korea with Data Envelopment Analysis/Window and Global Malmquist Indices Models

Data Envelopment Analysis/Window 모형과 Global Malmquist 생산성지수 모형을 이용한 지방의료원의 효율성과 생산성 변화 분석

  • Received : 2012.11.06
  • Accepted : 2013.02.19
  • Published : 2013.03.31

Abstract

This study empirically analyze efficiency and productivity changes of public hospitals of Korea using data envelopment analysis/Window model and global Malmquist indices model. We use the ten-year data from 2001 to 2010 of 30 regional public hospitals listed database from the Association of Korean Regional Public Hospitals. The main focuses are to reveal whether the technical inefficiency are improved as time goes by, and efficiency and productivity are affected by environmental factors. The results can be summarized as follows. First, the efficiencies of public hospitals rise in trend as time passes. Second, regional public hospitals show the different average efficiencies according to their regional type, hospital type, operational type, medicaid type, and demand and supply conditions by Mann-Whitney U-tests. Third, technical efficiency changes mainly contribute to 4.4% annual average growth rate of productivity of regional public hospitals during that period. Our findings have some policy implications. It is confirmed that there exist some environmental inefficiencies, and those inefficiencies can not be overcome through just improving the inner management system. Thus, policy and institutional changes are necessary for regional public hospitals to improve efficiency and productivity overall.

Keywords

References

  1. Ahn TS, Park JS. Productivity evaluation and comparison of Korean provincial hospitals. Korean J Hosp Manag 1997;2(1):22-47.
  2. Asmild M, Tam F. Estimating global frontier shifts and global Malmquist indices. J Prod Anal 2007;27:137-148. https://doi.org/10.1007/s11123-006-0028-0
  3. Avkiran, NK, Rowlands T. How to better identify the true managerial performance: state of the art using DEA. Omega 2008;36(2):317-324. https://doi.org/10.1016/j.omega.2006.01.002
  4. Banker RD, Charnes A, Cooper WW. Some models for the estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 1984;30(9):1078-1092. https://doi.org/10.1287/mnsc.30.9.1078
  5. Banker RD, Conrad RF, Strauss RP. A comparative application of data envelopment analysis and translog methods: an illustrative study of hospital production. Manag Sci 1986;32(1):30-44. https://doi.org/10.1287/mnsc.32.1.30
  6. Caves DW, Christensen LR, Diewert WE. The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica 1982;50(6):1393-1414. https://doi.org/10.2307/1913388
  7. Chang YJ, Yang DH. Analysis on global Malmquist productivity index change of regional public hospitals. Korean J Health Econ Policy 2011;17(4):89-107.
  8. Charnes A, Cooper WW. Preface to topics in data envelopment analysis. Ann Oper Res 1985;2:59-94.
  9. Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. European J Oper Res 1978;2(6):429-444. https://doi.org/10.1016/0377-2217(78)90138-8
  10. Charnes A, Cooper WW, Rhodes E. Evaluating program and managerial efficiency: an application of data envelopment analysis to program follow through. Manag Sci 1981;27(6):668-697. https://doi.org/10.1287/mnsc.27.6.668
  11. Chilingerian JA. Evaluating physician efficiency in hospitals: a multivariate analysis of best practices. European J Oper Res 1995;80(3):548-574. https://doi.org/10.1016/0377-2217(94)00137-2
  12. Fare R. Grosskopf S, Norris M, Zhang Z. Productivity growth, technical progress, and efficiency change in industrialized countries. Am Econ Rev 1994;84(1):66-83.
  13. Fried HO, Schmidt SS, Yaisawarng S. Incorporating the operating environment into a nonparametric measure of technical efficiency. J Product Anal 1999;12(3):249-267. https://doi.org/10.1023/A:1007800306752
  14. Grosskopf S, Valdmanis V. Measuring hospital performance: a non-parametric approach. J Health Econ 1987;6(2):89-107. https://doi.org/10.1016/0167-6296(87)90001-4
  15. Kim CB. Analysis on static, dynamic efficiency of service industry related to transportation. J Ind Econ Bus 2009;22(4):1715-1728.
  16. Kim JK, Jeon JW. Static and dynamic analysis of efficiency of Korean regional public hospitals. J Hosp Manag 2010;15(1):28-48.
  17. Kim YH, Cho WH, An DH, Park SW, Chung WJ. Medical care environment and the productivity change in Korean tertiary hospitals. Korean J Hosp Manag 2005;10(4):51-74.
  18. Kim YT. An exploration on changes in productivity index of local public medical centers by management system. J Ind Econ Bus 2010;23(3):1159-1184.
  19. Korea Association of Regional Public Hospitals. The Korea Association of Regional Public Hospitals database 2001-2010. Seoul: The Korea Association of Regional Public Hospitals; 2011.
  20. Korea Health Industry Development Institute. A study on plan for promoting the public service and efficiency of public hospitals as district base hospitals. Cheongwon: Korea Health Industry Development Institute; 2006.
  21. Lee MH. The effect of IT investment and dynamic efficiency test in manufacturing industries. J Econ Theory Econom 2009;20(4):27-49.
  22. Linna M, Hakkinen U, Magnussen J. Comparing hospital cost efficiency between Norway and Finland. Health Policy 2006;77(3):268-278. https://doi.org/10.1016/j.healthpol.2005.07.019
  23. Liu J, Tone K. A multistage method to measure efficiency and its application to Japanese banking industry. Socio-Econ Plan Sci 2008;42(2):75-91. https://doi.org/10.1016/j.seps.2006.06.008
  24. Nayar P, Ozcan YA. Data envelopment analysis comparison of hospital efficiency and quality. J Med Syst 2008;32:193-199. https://doi.org/10.1007/s10916-007-9122-8
  25. Oh D, Lee J. A metafrontier approach for measuring Malmquist productivity index. Empir Econ 2010;38:47-64. https://doi.org/10.1007/s00181-009-0255-0
  26. Oh DW, Lee JH, Min IS, Analysis on efficiency and productivity of Korean Regional Public Hospital between before and after the separation of dispensary from medical practice: using parametric and non-parametric statistical approaches. Korean J Health Econ Policy 2007;13(1):173-198.
  27. Park CJ. Measuring production efficiency using data envelopment analysis: the case of public corporation medical centers. Korean J Health Policy Adm 1996;6(2):91-114.
  28. Park GS, Kim YT, Chung HS. Assessing hospital efficiency and profit dynamics using DEA and DEA Window analysis. Korean Manag Rev 2005; 34(1):267-287.
  29. Pastor JT, Lovell CA. A global Malmquist productivity index. Econ Lett 2005; 88(2):266-271. https://doi.org/10.1016/j.econlet.2005.02.013
  30. Seo JN, Kim DH. Analyzing the dynamic productive efficiency of large purse seine fishery in Korea. J Fish Bus Adm 2012;43(1):11-18. https://doi.org/10.12939/FBA.2012.43.1.011
  31. Sherman HD. Hospital efficiency measurement and evaluation: empirical test of a new technique. Med Care 1984;22(10):922-938. https://doi.org/10.1097/00005650-198410000-00005
  32. Shin CG. An analysis on the efficiency and productivity changes of the national university hospitals in the Republic of Korea. Korean Soc Sec Stud 2006;22(4):49-78.
  33. Thoraneenitiyan N, Avikiran NK. Measuring the impact of restructuring and country-specific factors on the efficiency of post-crisis East Asian banking systems: intergrating DEA with SFA. Socio-Econ Plan Sci 2009;43(4): 240-252. https://doi.org/10.1016/j.seps.2008.12.002
  34. Tulken H, Eeckaut PV. Non-parametric efficiency, progress and regress measures for panel data: methodological aspects. European J Oper Res 1995; 80(3):474-499. https://doi.org/10.1016/0377-2217(94)00132-V
  35. Yoo T, Yim J, Zi H. Measuring efficiency and productivity of the Korean public hospitals. J Korean Oper Res Manag Sci 2004;29(3):79-98.
  36. Yoon KJ. Using DEA to measure the efficiency of local health centers. Korean Policy Stud Rev 1996;5(1):80-109.