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Prediction and Decomposition of Efficiency Differences in Chinese Provincial Community Health Services

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  • Qian Liu

    (Department of Social Medicine and Health Administration, School of Public Health, Tianjin Medical University, Tianjin 300070, China)

  • Bo Li

    (International College of Business and Technology, Tianjin University of Technology, Tianjin 300384, China
    School of Business and Economics, Thompson Rivers University, Kamloops, BC V2C 0C8, Canada)

  • Muhammad Mohiuddin

    (School of Business and Economics, Thompson Rivers University, Kamloops, BC V2C 0C8, Canada)

Abstract

The objective of this paper is to analyze the provincial efficiency of the Chinese community health care service and its differences. This study allows us to predict the provincial differences in the efficiency of the Chinese community health care service from 2017 to 2026. This study analyzes the contributions of inter-regional and intra-regional differences in the total efficiency difference. We use the Super-SBM (Slacks-based Model) data envelopment analysis (DEA) model, Grey Model GM (1,1) for grey prediction, and the group-based Theil index decomposition method to study Chinese provincial panel data from 2008 to 2016. Results show that a fluctuating trend existed in the average provincial efficiency of community health services from 2008 to 2016. The community health services in a considerable number of provincial areas were inefficient. This study also reveals that there existed apparent inter-provincial differences in efficiency in Chinese community health services. The inter-provincial differences of the efficiency of Chinese community health services revealed by the Theil index declined at a relatively slow pace. With regard to the provincial efficiency difference of the Chinese community health service, the intra-regional efficiency difference is the most important structural reason for the overall efficiency difference, which explains the overall difference to a large extent. The inter-regional efficiency difference among the eastern, central, and western regions becomes the secondary structural reason, which should not be ignored. In conclusion, focus should be put on restructuring the investments into medical resources for community health service in each Chinese province. More attentions should be put into narrowing the inter-regional efficiency differences of the Chinese provincial community health service. The strategies targeted at reducing the inter-regional efficiency differences should not be ignored, so as to facilitate the improvement of overall efficiency of the Chinese community health service.

Suggested Citation

  • Qian Liu & Bo Li & Muhammad Mohiuddin, 2018. "Prediction and Decomposition of Efficiency Differences in Chinese Provincial Community Health Services," IJERPH, MDPI, vol. 15(10), pages 1-14, October.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:10:p:2265-:d:175940
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    as
    1. Halkos, George E. & Tzeremes, Nickolaos G., 2011. "A conditional nonparametric analysis for measuring the efficiency of regional public healthcare delivery: An application to Greek prefectures," Health Policy, Elsevier, vol. 103(1), pages 73-82.
    2. Thomas Czypionka & Markus Kraus & Susanne Mayer & Gerald Röhrling, 2014. "Efficiency, ownership, and financing of hospitals: The case of Austria," Health Care Management Science, Springer, vol. 17(4), pages 331-347, December.
    3. Robert Stefko & Beata Gavurova & Kristina Kocisova, 2018. "Healthcare efficiency assessment using DEA analysis in the Slovak Republic," Health Economics Review, Springer, vol. 8(1), pages 1-12, December.
    4. O'Neill, Liam & Rauner, Marion & Heidenberger, Kurt & Kraus, Markus, 2008. "A cross-national comparison and taxonomy of DEA-based hospital efficiency studies," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 158-189, September.
    5. John S. Liu & Louis Y. Y. Lu & Wen-Min Lu, 2016. "Research Fronts and Prevailing Applications in Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 543-574, Springer.
    6. Gustafsson, Bjorn & Shi, Li, 2002. "Income inequality within and across counties in rural China 1988 and 1995," Journal of Development Economics, Elsevier, vol. 69(1), pages 179-204, October.
    7. Bruce Hollingsworth, 2008. "The measurement of efficiency and productivity of health care delivery," Health Economics, John Wiley & Sons, Ltd., vol. 17(10), pages 1107-1128, October.
    8. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    9. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    10. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    11. Kontodimopoulos, Nick & Nanos, Panagiotis & Niakas, Dimitris, 2006. "Balancing efficiency of health services and equity of access in remote areas in Greece," Health Policy, Elsevier, vol. 76(1), pages 49-57, March.
    12. Jean Spinks & Bruce Hollingsworth, 2009. "Cross-country comparisons of technical efficiency of health production: a demonstration of pitfalls," Applied Economics, Taylor & Francis Journals, vol. 41(4), pages 417-427.
    13. Cristian Nedelea, I. & Matthew Fannin, J., 2013. "Analyzing cost efficiency of Critical Access Hospitals," Journal of Policy Modeling, Elsevier, vol. 35(1), pages 183-195.
    14. Kazley, Abby Swanson & Ozcan, Yasar A., 2009. "Electronic medical record use and efficiency: A DEA and windows analysis of hospitals," Socio-Economic Planning Sciences, Elsevier, vol. 43(3), pages 209-216, September.
    15. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    16. Alcantara, Vicent & Duro, Juan Antonio, 2004. "Inequality of energy intensities across OECD countries: a note," Energy Policy, Elsevier, vol. 32(11), pages 1257-1260, July.
    17. Necmi Avkiran & Kaoru Tone & Miki Tsutsui, 2008. "Bridging radial and non-radial measures of efficiency in DEA," Annals of Operations Research, Springer, vol. 164(1), pages 127-138, November.
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