Skip to main content

Advertisement

SpringerLink
Log in

Identifying the contribution to hospital performance among Chinese regions by an aggregate directional distance function

  • Published:
Health Care Management Science Aims and scope Submit manuscript

Abstract

In this paper, we examine efficiency and total factor productivity for hospitals operating in China between the years of 2009–2016. Given reforms in China focusing on the hospital sector, it has been demonstrated that efficiency and productivity are important in meeting the overall objective of meeting more accessibility to hospital care for the population. Measuring an aggregate directional distance function is in itself a non-parametric approach, we report on the decomposition of hospital performance and found that between 2009 and 2010, technical inefficiency (using resources inefficiently) dominated overall inefficiency but beyond 2011–2016, mix inefficiency (misallocation of resources) was higher. Furthermore, an additive total factor productivity (TFP) indicator is proposed to capture contributions of individual provincial (or group) hospital performance to the total productivity gain. We also report that mix inefficiency had growth throughout this time period indicating a catching up in the correct mix of inputs. This finding is worth following as hospital reform in China also focuses on utilizing the right labor and capital mix in producing efficient care.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. As a reminder, the Malmquist approach uses inputs and outputs from multiple time periods comparing what could be produced using year 1’s inputs and compares this to year 2’s output. The index is analogous to traditional indices such as Paasche and Laspeyre, but instead of using prices and commodities of goods purchased, the Malmqusit approach uses inputs and outputs. For a further review, see (Färe, et al.s [16]).

  2. We ignore the regions of Hong Kong, Macao and Taiwan in China due to data accessibility.

References

  1. Hu H, Qi Q, Yang C (2012) Analysis of hospital technical efficiency: effect of health insurance reform. China Econ Rev 23(4):865–877

    Article  Google Scholar 

  2. Blumenthal D, Hsiao W (2005) Privatization and its discontents – the evolving Chinese health care system. N Engl J Med 353(11):1165–1170

    Article  Google Scholar 

  3. Barber S, Borowitz M, Bekedam H, Ma J (2014) The hospital of the future in China: China’s reform of public hospitals and trends from industrialized countries. Health Policy Plan 29(3):367–378

    Article  Google Scholar 

  4. Liu G, Vortherms S, Hong X (2017) China’s health reform update. Annu Rev Public Health 38:431–448

    Article  Google Scholar 

  5. Zhang Y, Ma Q, Chen Y, Goa H (2017) Effects of public hospital reform on inpatient expenditures in rural China. Health Econ 26(4):421–430

    Article  Google Scholar 

  6. Liu X, Liu Y, Chen N (2000) The Chinese experience of hospital price regulation. Health Policy Plan 15(2):157–163

    Article  Google Scholar 

  7. Gerdtham U, Sogaard J, Andersson G, Jonsson B (1992) An econometric analysis of health care expenditure: a cross-section study of the OECD countries. J Health Econ 11(1):63–84

    Article  Google Scholar 

  8. Audibert M, Mathonnat J, Pelissier A, Huang H, Ma A (2013) Health insurance reform and efficiency of township hospitals in rural China: an analysis from survey data. China Econ Rev 27:326–338

    Article  Google Scholar 

  9. China sets up new system to optimize medical resources. National Health Commission of the Peoples Republic of China (2015) http://en.nhc.gov.cn/2015-09/16/c_46816.htm

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

    Article  Google Scholar 

  11. Daemmich A (2013) The pollical economy of healthcare reform in China: negotiating public and private. Springer Plus 2:448–463

    Article  Google Scholar 

  12. Li H, Dong S, Liu T (2014) Relative efficiency and productivity: a preliminary exploration of public hospitals in Beijing, China. BMJ Health Services Research 14:158–168

    Article  Google Scholar 

  13. Ng. Y (2011) The productive efficiency of Chinese hospitals. China Econ Rev 22:428–439

    Article  Google Scholar 

  14. Hu H, Qi Q, Yang C (2012) Evaluation of China’s regional hospital efficiency: DEA approach with undesirable output. J Oper Res Soc 63(6):715–725

    Article  Google Scholar 

  15. Wang M, Fang H, Tao H, Cheng Z (2017) Bootstrapping data envelopment analysis of efficiency, and productivity of county hospitals in eastern, central, and Western China after public hospital reform. J Huazhong University Sci Technol 37(5):681–692

    Google Scholar 

  16. Färe R, Grosskopf S, Lindgren B, Roos P (1992) Productivity changes in Swedish pharmacies 1980-1989: a non-parametric Malmquist approach. J Prod Anal 3(1–2):85–101

    Article  Google Scholar 

  17. Cheng Z, Tao H, Lin H, Lin X, Zhang R (2015) Technical efficiency and productivity of Chinese county hospitals: an exploratory study in Henan Province. BMJ Open Access 5:e007267. https://doi.org/10.1136/BMJOpen-2014-007267

    Article  Google Scholar 

  18. Chu K, Zhang N, Chen Z (2015) The efficiency and its determinants for China’s medical care system: some policy implications for Northeast China. Sustainability 7(10):14092–14111

    Article  Google Scholar 

  19. Yang, J., Zeng W. (2014). The tradeoff between efficiency and quality in the hospital production: some evidence from Shenzhen, China. China Econ Rev 31 166–184

    Article  Google Scholar 

  20. Boussemart, J-P., Ferrier, G., Leleu, H., Shen, Z. (2018) An expanded decomposition of the Luenberger productivity indicator with an application to the Chinese healthcare sector. IESEG working paper

  21. Hackman ST (2008) Production economics: integrating the microeconomic and engineering perspectives. Springer, Berlin

    Google Scholar 

  22. Li SK (1995) Relations between convexity and homogeneity in multi-output technologies. J Math Econ 24:311–318

    Article  Google Scholar 

  23. Ferrier G, Leleu H, Valdmanis V (2010) The impact of CON regulation on hospital efficiency. Health Care Management Sci 83(1):84–100

    Article  Google Scholar 

  24. Chambers R, Chung Y, Färe R (1996) Benefit and distance functions. J Econ Theory 70(2):407–419

    Article  Google Scholar 

  25. Boussemart JP, Leleu H, Shen Z (2015) Environmental growth convergence among Chinese regions. China Econ Rev 34:1–18

    Article  Google Scholar 

  26. Briec W, Kerstens K (2004) A Luenberger-Hicks-Moorsteen productivity indicator: its relation to the Hicks-Moorsteen productivity index and the Luenberger productivity indicator. Economic Theory 23:925–939

    Article  Google Scholar 

  27. Kerstens K, Shen Z, Van de Woestyne I (2018) Comparing Luenberger and Luenberger-Hicks-Moorsteen productivity indicators: how well is total factor productivity approximated? Int J Prod Econ 195:311–318

    Article  Google Scholar 

  28. National Bureau of Statistics of China (2017) http://www.stats.gov.cn/english/Statisticaldata/AnnualData/

  29. Ma J, Lu M, Quan H (2008) From a national, centrally planned health system to a systems based on the market: lessons from China. Health Aff 27(4):937–948

    Article  Google Scholar 

  30. Shi J, Liu M, Zhang Q, Lu M, Quan H (2008) Male and female adult population health status in China: a cross-sectional national survey. BMC Public Health 8:277–286

    Article  Google Scholar 

  31. Gong P, Liang S, Carlton E, Jiang Q, Wu J, Wang L, Remais J (2012) Urbanisation and health in China. Lancet 379:843–851

    Article  Google Scholar 

  32. Yu H (2015) Universal health insurance coverage for 1.3 billion people: what accounts for China’s success? Health Policy 119:1145–1152

    Article  Google Scholar 

Download references

Funding

There was no external funding received for this study.

Author information

Authors and Affiliations

  1. Anhui University of Finance & Economics, 962 CaoShan RD, Bengbu, 233030, China

    Zhiyang Shen

  2. China Eximbank, 30 FuXingMenNei RD, Beijing, 100031, China

    Zhiyang Shen

  3. Western Michigan University, Grand Rapids, MI, 49503, USA

    Vivian Valdmanis

Authors
  1. Zhiyang Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vivian Valdmanis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vivian Valdmanis.

Ethics declarations

Conflict of interest

There is no conflict of interest between the authors and other agencies or persons.

Ethical approval

This article does not contain any studies with human participants or animals performed.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shen, Z., Valdmanis, V. Identifying the contribution to hospital performance among Chinese regions by an aggregate directional distance function. Health Care Manag Sci 23, 142–152 (2020). https://doi.org/10.1007/s10729-019-09482-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10729-019-09482-4

Keywords

JEL classification

Search

Navigation