IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i10p2265-d175940.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/10/2265/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/10/2265/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lin, Boqiang & Xie, Yongjing, 2023. "Does digital transformation improve the operational efficiency of Chinese power enterprises?," Utilities Policy, Elsevier, vol. 82(C).
    2. Yu-Feng Zhao & Ming-Huan Shou & Zheng-Xin Wang, 2020. "Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models," IJERPH, MDPI, vol. 17(12), pages 1-20, June.
    3. Fang Wu & Mingyao Gu & Chenming Zhu & Yingna Qu, 2023. "Temporal-Spatial Evolution and Trend Prediction of the Supply Efficiency of Primary Medical Health Service—An Empirical Study Based on Central and Western Regions of China," IJERPH, MDPI, vol. 20(3), pages 1-23, January.
    4. Kaili Zhong & Lv Chen & Sixiang Cheng & Hongjun Chen & Fei Long, 2020. "The Efficiency of Primary Health Care Institutions in the Counties of Hunan Province, China: Data from 2009 to 2017," IJERPH, MDPI, vol. 17(5), pages 1-15, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Berger, Michael & Sommersguter-Reichmann, Margit & Czypionka, Thomas, 2020. "Determinants of soft budget constraints: how public debt affects hospital performance in Austria," LSE Research Online Documents on Economics 116865, London School of Economics and Political Science, LSE Library.
    2. Berger, Michael & Sommersguter-Reichmann, Margit & Czypionka, Thomas, 2020. "Determinants of soft budget constraints: How public debt affects hospital performance in Austria," Social Science & Medicine, Elsevier, vol. 249(C).
    3. Sommersguter-Reichmann, Margit & Stepan, Adolf, 2015. "The interplay between regulation and efficiency: Evidence from the Austrian hospital inpatient sector," Socio-Economic Planning Sciences, Elsevier, vol. 52(C), pages 10-21.
    4. Yusi Cheng & Xuejie Bai & Yung‐Ho Chiu, 2023. "Performance evaluation for health‐care sectors using a dynamic network data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 2237-2253, June.
    5. Yi-Chung Hsu, 2014. "Efficiency in government health spending: a super slacks-based model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 111-126, January.
    6. George Fragkiadakis & Michael Doumpos & Constantin Zopounidis & Christophe Germain, 2016. "Operational and economic efficiency analysis of public hospitals in Greece," Post-Print hal-01414677, HAL.
    7. Sepideh Abolghasem & Mehdi Toloo & Santiago Amézquita, 2019. "Cross-efficiency evaluation in the presence of flexible measures with an application to healthcare systems," Health Care Management Science, Springer, vol. 22(3), pages 512-533, September.
    8. George Fragkiadakis & Michael Doumpos & Constantin Zopounidis & Christophe Germain, 2016. "Operational and economic efficiency analysis of public hospitals in Greece," Annals of Operations Research, Springer, vol. 247(2), pages 787-806, December.
    9. Dinesh R. Pai & Fatma Pakdil & Nasibeh Azadeh-Fard, 2024. "Applications of data envelopment analysis in acute care hospitals: a systematic literature review, 1984–2022," Health Care Management Science, Springer, vol. 27(2), pages 284-312, June.
    10. Aleksandar Medarević & Dejana Vuković, 2021. "Efficiency and Productivity of Public Hospitals in Serbia Using DEA-Malmquist Model and Tobit Regression Model, 2015–2019," IJERPH, MDPI, vol. 18(23), pages 1-22, November.
    11. Chowdhury, Hedayet & Zelenyuk, Valentin, 2016. "Performance of hospital services in Ontario: DEA with truncated regression approach," Omega, Elsevier, vol. 63(C), pages 111-122.
    12. Fang Wu & Mingyao Gu & Chenming Zhu & Yingna Qu, 2023. "Temporal-Spatial Evolution and Trend Prediction of the Supply Efficiency of Primary Medical Health Service—An Empirical Study Based on Central and Western Regions of China," IJERPH, MDPI, vol. 20(3), pages 1-23, January.
    13. Svetlana V. Ratner & Artem M. Shaposhnikov & Andrey V. Lychev, 2023. "Network DEA and Its Applications (2017–2022): A Systematic Literature Review," Mathematics, MDPI, vol. 11(9), pages 1-24, May.
    14. Zhao, Y. & Triantis, K. & Murray-Tuite, P. & Edara, P., 2011. "Performance measurement of a transportation network with a downtown space reservation system: A network-DEA approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1140-1159.
    15. Ioannis E. Tsolas, 2020. "Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    16. Shiu-Wan Hung & Chao-Liang Chang & Shu Ming Liu, 2019. "Innovation System Assessment Model for Sustainability Planning in Taiwan," Sustainability, MDPI, vol. 11(24), pages 1-24, December.
    17. Kostas Kounetas & Fotis Papathanassopoulos, 2013. "How efficient are Greek hospitals? A case study using a double bootstrap DEA approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(6), pages 979-994, December.
    18. Hainan Guo & Yang Zhao & Tie Niu & Kwok-Leung Tsui, 2017. "Hong Kong Hospital Authority resource efficiency evaluation: Via a novel DEA-Malmquist model and Tobit regression model," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-24, September.
    19. Wen-Min Lu & Qian Long Kweh & Kai-Chu Yang, 2022. "Multiplicative efficiency aggregation to evaluate Taiwanese local auditing institutions performance," Annals of Operations Research, Springer, vol. 315(2), pages 1243-1262, August.
    20. Lorena Androutsou & Michail Kokkinos & Dimitra Latsou & Mary Geitona, 2022. "Assessing the Efficiency and Productivity of the Hospital Clinics on the Island of Rhodes during the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(23), pages 1-12, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:15:y:2018:i:10:p:2265-:d:175940. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.