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Evaluation of China's regional hospital efficiency: DEA approach with undesirable output

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Journal of the Operational Research Society

Abstract

This paper investigates regional hospital efficiency in China. As hospital operations naturally increase along with an undesirable output of patient mortality, which may induce medical disputes and ligations, this study adopts data envelopment analysis to evaluate and compare the efficiency scores obtained with and without considering the undesirable output. On the basis of province-level panel data over 2002–2008 and considering the risk-adjusted undesirable output, empirical estimates indicate that hospital efficiency is moderate, but increases gradually from 0.6881 to 0.8159. Importantly, without considering the undesirable output, the average efficiency score is overestimated and the efficiency ranking across provinces changes considerably. An efficiency gap is found between coastal and non-coastal regions, but this gap’s drop is mainly contributed by the fast efficiency improvement of the western regions. However, the central regions continue to achieve a significantly lower efficiency score than the eastern and western regions. Moreover, the initiation of the New Rural Cooperative Medical System has overall enhanced hospital efficiency in China, especially for the non-coastal regions.

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Notes

  1. For the development of China's urban health insurance system, please see Liu (2002). Alternatively, Liu (2004) and Wang (2007) provide a comprehensive discussion on the evolution of the rural health insurance system. Akin et al (2005), Blomqvist (2009), and Dong (2009) also provide a detailed review on China’s health system reform.

  2. In 2007, basic social medical insurance coverage for the urban population and the New Rural Cooperative Medical System (NRCMS) coverage for the rural population is 65.00 and 73.79%, respectively (Dong, 2009).

  3. Some studies evaluate health production efficiency by using micro-level data of a small number of hospitals; please refer to Eggleston et al (2008) for a comprehensive survey.

  4. O’Neill et al (2008) provide a systematic review of 79 such studies published from 1984 to 2004 that represent 12 countries.

  5. Feng and Antony (2010) propose a new methodology that integrates the DEA method into the framework of Six Sigma to assess health service efficiency.

  6. Thanassoulis et al (1987) examine the nature of information obtained from DEA in comparative studies of the efficiency of decision-making units, and discuss the interpretation and practical usefulness of such information.

  7. Recent studies, such as Färe and Grosskopf (2004) and Seiford and Zhu (2005), have continued to argue with the matter of improving this approach, and it has been widely applied to evaluate efficiency with undesirable outputs, such as banks (Portela et al, 2004) and pollution (Forsund, 2009).

  8. There are at least five possibilities for dealing with undesirable outputs in the DEA framework (Seiford and Zhu, 2002).

  9. The difference with Seiford and Zhu’s (2002) BCC-DEA framework is that, in the final restriction equation, they pose an addition restriction, to ensure the convexity condition of a VRS model.

  10. While part of patient mortality in the hospital results from mistakes on the part of clinicians, mortality can still result even when there are no mistakes, that is, the technical quality of care is excellent. However, due to the lack of information, we cannot construct the variable of risk-adjustment mortality.

  11. There are many problems in the Chinese health-care system (Yip and Hsiao, 2008). However, we have no strong attempt and sufficient ability to deal with too many problems in this study. Both aforementioned points are limitations of this study.

  12. The measures of inputs and outputs are not the same in both studies, and thus we cannot compare the estimated efficiency scores directly.

  13. A more reliable argument regarding the impact of medical reform on hospital efficiency should be based on a longer time span for the pre-reform period.

  14. In China, hospitals can apply for ‘class’ certification. The classification system classifies hospitals into third-class (the highest class), second-class, and first-class according to criterions on number of beds, medical departments, personnel, and so on. For details, please see http://www.moh.gov.cn.

  15. Zheng and Zhang (2009) propose some possible interpretations.

  16. The Mid-China regions include: Hebei, Shanxi, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Hunan, and Hainan. The West China regions contain Neimenggu, Guangxi, Chongqing, Sichun, Guizhou, Yunan, Shangxi, Gansui, Qinghai, and Tibet.

  17. The main components of the strategy include development of infrastructure, enticement of foreign investment, increased efforts on ecological protection, promotion of education, and retention of talent flowing to richer provinces. For the details of this programme, please see http://www.westchina.gov.cn.

  18. In fact, the eastern region is a subsample of the coastal region that excludes Hebei, Guangxi, and Hainan.

  19. Indeed, there are many potential confounders that could cause one region to be more efficient than another, including labor costs, local diet, population health factors, environmental factors, other economic factors. These factors may induce the manager of a hospital or a group of hospitals to choose the hospital's location and further impact on hospital efficiency. This issue is worth further investigation.

References

  • Akin JS, Dow WH, Lance PM and Loh CP (2005). Changes in access to health care in China, 1989–1997. Health Pol Plann 20 (2): 80–89.

    Article  Google Scholar 

  • Banker RD, Charnes A and Cooper WW (1984). Models for estimating technical and scale inefficiencies in data envelopment analysis. Mngt Sci 30 (9): 1078–1092.

    Article  Google Scholar 

  • Blomqvist A (2009). Health system reform in China: What role for private insurance? China Econ Rev 20 (4): 605–612.

    Article  Google Scholar 

  • Chan KW and Wang M (2008). Remapping China's regional inequalities, 1990–2006: A new assessment of de facto and de jure population data. Eurasian Geogr Econ 49 (1): 22–55.

    Article  Google Scholar 

  • Charnes A, Cooper WW and Rhodes E (1978). Measuring the efficiency of decision-making units. Eur J Opl Res 2 (6): 429–444.

    Article  Google Scholar 

  • Clement JP, Valdmanis VG, Bazzoli GJ, Zhao M and Chukmaitov A (2008). Is more better? An analysis of hospital outcomes and efficiency with a DEA model of output congestion. Health Care Mngt Sci 11 (1): 66–77.

    Article  Google Scholar 

  • Dong K (2009). Medical insurance system evolution in China. China Econ Rev 20 (4): 591–597.

    Article  Google Scholar 

  • Eggleston K, Li L, Meng Q, Lindelow M and Wagstaff A (2008). Health service delivery in China: A literature review. Health Econ 17 (2): 149–165.

    Article  Google Scholar 

  • Färe R and Grosskopf S (2004). Modeling undesirable factors in efficiency evaluation: Comment. Eur J Opl Res 157 (1): 242–245.

    Article  Google Scholar 

  • Feng Q and Antony J (2010). Integrating DEA into six sigma methodology for measuring health service efficiency. J Opl Res Soc 61 (7): 1112–1121.

    Article  Google Scholar 

  • Ferrier GD, Rosko MD and Valdmanis VG (2006). Analysis of uncompensated hospital care using a DEA model of output congestion. Health Care Mngt Sci 9 (2): 181–188.

    Article  Google Scholar 

  • Forsund FR (2009). Good modelling of bad outputs: Pollution and multiple-output production. Int Rev Environ Resource Econ 3 (1): 1–38.

    Article  Google Scholar 

  • Hollingsworth B (2008). The measurement of efficiency and productivity of health care delivery. Health Econ 17 (10): 1107–1128.

    Article  Google Scholar 

  • Hollingsworth B and Wildman J (2003). The efficiency of health production: Re-estimating the WHO panel data using parametric and non-parametric approaches to provide additional information. Health Econ 12 (6): 493–504.

    Article  Google Scholar 

  • Kanbur R and Zhang X (2005). Fifty years of regional inequality in China: a journey through central planning, reform, and openness. Rev Dev Econ 9 (1): 87–106.

    Article  Google Scholar 

  • Liu Y (2002). Reforming China's urban health insurance system. Health Pol 60 (2): 133–150.

    Article  Google Scholar 

  • Liu Y (2004). Development of the rural health insurance system in China. Health Pol Plann 19 (3): 159–165.

    Article  Google Scholar 

  • McKay NL and Deily ME (2005). Comparing high- and low-performing hospitals using risk-adjusted excess mortality and cost inefficiency. Health Care Serv Mngt 30 (4): 347–360.

    Google Scholar 

  • Nayar P and Ozcan YA (2008). Data envelopment analysis comparison of hospital efficiency and quality. J Med Syst 32 (3): 193–199.

    Article  Google Scholar 

  • O'Neill L, Rauner M, Heidenberger K and Kraus M (2008). A cross-national comparison and taxonomy of DEA-based hospital efficiency studies. Socio-Econ Plann Sci 42 (3): 158–189.

    Article  Google Scholar 

  • Portela MCAS, Thanassoulis E and Simpson G (2004). Negative data in DEA: A directional distance approach applied to bank branches. J Opl Res Soc 55 (10): 1111–1121.

    Article  Google Scholar 

  • Puig-Junoy J (1998). Technical efficiency in the clinical management of critically ill patients. Health Econ 7 (3): 263–277.

    Article  Google Scholar 

  • Retzlaff-Roberts D, Chang CF and Rubin RM (2004). Technical efficiency in the use of health care resources: a comparison of OECD countries. Health Pol 69 (1): 55–72.

    Article  Google Scholar 

  • Seiford LM and Zhu J (2002). Modeling undesirable factors in efficiency evaluation. Eur J Opl Res 142 (1): 16–20.

    Article  Google Scholar 

  • Seiford LM and Zhu J (2005). A Response to comments on modeling undesirable factors in efficiency evaluation. Eur J Opl Res 161 (2): 579–581.

    Article  Google Scholar 

  • Thanassoulis E, Dyson RG and Foster MJ (1987). Relative efficiency assessments using data envelopment analysis: an application to data on rates departments. J Opl Res Soc 38 (5): 397–411.

    Article  Google Scholar 

  • Wang YZ (2007). Development of the new rural cooperative medical system in China. China World Econ 15 (1): 66–77.

    Article  Google Scholar 

  • Yip W and Hsiao WC (2008). The Chinese health system at a crossroads. Health Aff 27 (2): 460–468.

    Article  Google Scholar 

  • Zhang N, Hu A and Zheng J (2007). Using data envelopment analysis approach to estimate the health production efficiencies in China. Front Econ China 2 (1): 1–27.

    Article  Google Scholar 

  • Zheng W and Zhang C (2009). Efficiency evaluation of China's new rural cooperative medical system using DEA method. Mimeo.

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Acknowledgements

The paper is drawn from parts of Hsin-Hui Hu’s Dalian Medical University PhD dissertation. The authors would like to thank two anonymous referees for their insightful comments and suggestions on an earlier version of this paper. The usual disclaimer applies.

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Correspondence to C-H Yang.

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Hu, HH., Qi, Q. & Yang, CH. Evaluation of China's regional hospital efficiency: DEA approach with undesirable output. J Oper Res Soc 63, 715–725 (2012). https://doi.org/10.1057/jors.2011.77

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