Abstract
This study measures the quality-adjusted hospital efficiency and productivity index of a production unit. We propose a non-radial output-oriented directional distance function approach to analyze Taiwan’s hospital productivity, which embeds the quality of care and environment variables simultaneously. There are two major advantages of this model. First, it considers all the radial and non-radial slacks that the model can identify, and hence is able to provide a more accurate performance measure and improve the discriminating power of the analysis. Second, it allows us to identify the source of the inefficiency. Our results show that the productivity indices of most of Taiwan’s hospitals got worse during the 2002–2004 period, during which both technology and efficiency performance deteriorated, but divergence appeared among different types of hospitals. We confirmed the need to incorporate quality factors while measuring a hospital’s efficiency and productivity. Nevertheless, there is no evidence to support the idea that healthcare quality is undermined by the cost-saving efforts by the care providers after the implantation of a global budget system.
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Arocena P, García-Prado A (2007) Accounting for quality in the measurement of hospital performance: evidence from Costa Rica. Health Econ 16: 667–685
Ashton CM, Wray NP (1996) A conceptual framework for the study of early readmission as an indicator of quality of care. Soc Sci Med 43(11): 1533–1541
Barros CP, Menezes A, Vieira JAC, Peypoch N, Solonandrasana B (2007) An analysis of hospital efficiency and productivity growth using the Luenberger productivity indicator. IZA Discussion Paper No. 2689
Boardman AE, Vining AR (1989) Ownership and performance in competitive environments: a comparison of the performance of private, mixed, and state-owned enterprises. J Law Econ 32(1): 1–33
Bureau of National Health Insurance (2004) National Health Insurance annual statistical report. Bureau of National Health Insurance, Taipei, Taiwan, pp 94–99
Chen SN (2006) Productivity changes in Taiwanese hospitals and the national health insurance. Serv Ind J 26(4): 459–477
Chung YH, Färe R, Grosskopf S (1997) Productivity and undesirable outputs: a directional distance function approach. J Environ Manag 51: 229–240
Cooper WW, Huang Z, Li SX, Parker BR, Pastor JT (2007a) Efficiency aggregation with enhanced Russell measures in data envelopment analysis. Socio-Econ Plan Sci 41: 1–21
Cooper WW, Seiford LM, Tone K (2007b) Some models and measures for evaluating performances with DEA: past accomplishments and future prospects. J Product Anal 28: 151–163
Deyo RA, Cherkin DC, Ciol MA (1992) Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 45: 613–619
Dismuke CE, Sena V (2001) Is there a trade-off between quality and productivity? The case of diagnostic technologies in Portugal. Ann Oper Res 107: 101–116
Donabedian A (1980) The definition of quality and approaches to its assessment. Health Administration Press, Ann Arbor
Dredge R (2004) Hospital global budgeting. HNP discussion paper. Available from: http://siteresources.worldbank.org/HEALTHNUTRITIONANDPOPULATION/Resources/281627-1095698140167/DredgeHspGlblBdgtFinal.pdf, Accessed May 2008
Epstein AM, Bogen J, Dreyer P, Thorpe KE (1991) Trends in length of stay and rates of readmission in Massachusetts: implications for monitoring quality of care. Inquiry 28: 19–28
Färe R, Lovell CAK (1978) Measuring the technical efficiency of production. J Econ Theory 19(1): 150–162
Färe R, Grosskopf S (2000) Network DEA. Socio-Econ Plan Sci 34: 35–49
Färe R, Grosskopf S (2004) Modeling undesirable factors in efficiency evaluation: comment. Eur J Oper Res 157: 242–245
Färe R, Grosskopf S (2010) Directional distance functions and slacks-based measures of efficiency. Eur J Oper Res 200(1): 320–322
Färe R, Grosskopf S, Lovell CAK (1985) The measurement of efficiency of production. Kluwer, Boston
Färe R, Grosskopf S, Roos P (1995) Productivity and quality changes in Swedish pharmacies. Int Prod Econ 39: 137–147
Feldman R, Lobo F (1997) Global budgets and excess demand for hospital care. Health Econ 6: 187–196
Fried HO, Schmidt SS, Yaisawarng S (1999) Incorporating the operating environment into a nonparametric measure of technical efficiency. J Product Anal 12: 249–267
Fukuyama H, Weber WL (2009) A directional slacks-based measure of technical inefficiency. Socio-Econ Plan Sci 43(4): 274–287
Hinds S, Sanchez N, Schap D (2005) Public enterprise: retrospective review and prospective theory. In: Backhaus JG, Wagner RE (eds) Handbook of public finance. Springer, Berlin, pp 277–300
Ho V, Hamilton BH (2000) Hospital mergers and acquisitions: does market consolidation harm patients?. J Health Econ 19: 767–791
Hofmarcher MM, Paterson I, Riedel M (2002) Measuring hospital efficiency in Austria—a DEA approach. Health Care Manag Sci 5: 7–14
Hollingsworth B (2003) Non-parametric and parametric applications measuring efficiency in health care. Health Care Manag Sci 6: 203–218
Hollingsworth B (2008) The measurement of efficiency and productivity of health care delivery. Health Econ 17: 1107–1128
Hollingsworth B, Street A (2006) The market for efficiency analysis of health care organizations. Health Econ 15: 1055–1059
Kontodimopoulos N, Nanos P, Niakas D (2006) Balancing efficiency of health services and equity of access in remote areas in Greece. Health Policy 76: 49–57
Linna M (1998) Measuring hospital cost efficiency with panel data models. Health Econ 7: 415–427
Luenberger DG (1992) Benefit function and duality. J Math Econ 21: 461–481
Maniadakis N, Hollingsworth B, Thanassoulis E (1999) The impact of the internal market on the hospital efficiency, productivity and service quality. Health Care Manag Sci 2: 75–85
O’Neill L, Rauner M, Heidenberger K, Kraus M (2007) A cross-national comparison and taxonomy of DEA-based hospital efficiency studies. Socio-Econ Plan Sci 42(3): 158–189
Ozcan YA (2008) Health care benchmarking and performance evaluation an assessment using data envelopment analysis (DEA). Springer, Newton. ISBN: 978-0-387-75447-5
Pastor JT, Ruiz JL, Sirvent I (1999) An enhanced DEA Russell graph efficiency measure. Eur J Oper Res 115: 596–607
Sommersguter-Reichmann M (2000) The impact of the Austrian hospital financing reform on hospital productivity: empirical evidence on efficiency and technology changes using a non-parametric input-based Malmquist approach. Health Care Manag Sci 3(4): 309–321
Sueyoshi T, Goto M (2012) Data envelopment analysis for environmental assessment: comparison between public and private ownership in petroleum industry. Eur J Oper Res 216: 668–678
Thanassoulis E, Boussofiane A, Dyson RG (1995) Exploring output quality targets in the provision of perinatal care in England using data envelopment analysis. Eur J Oper Res 80: 588–607
Tone K (2001) A slack based measure of efficiency in data envelopment analysis. Eur J Oper Res 130: 498–509
Wang YH, Lee WF (2004) Technical efficiency of district hospitals in Taiwan: nonparametric data envelopment analysis. Taipei Econ Inq 40: 61–95
Zhou P, Poh KL, Ang BW (2007) A non-radial DEA approach to measuring environmental performance. Eur J Oper Res 178: 1–9
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Wu, CH., Chang, CC., Chen, PC. et al. Efficiency and productivity change in Taiwan’s hospitals: a non-radial quality-adjusted measurement. Cent Eur J Oper Res 21, 431–453 (2013). https://doi.org/10.1007/s10100-012-0238-7
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DOI: https://doi.org/10.1007/s10100-012-0238-7
Keywords
- Data envelopment analysis
- Directional distance function
- Russell measure
- Slacks-based measures
- Malmquist-Luenberger index
- Hospitals