IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i5p4453-d1085581.html
   My bibliography  Save this article

Technical Efficiency Evaluation of Primary Health Care Institutions in Shenzhen, China, and Its Policy Implications under the COVID-19 Pandemic

Author

Listed:
  • Shujuan Chen

    (Shenzhen Health Development Research and Data Management Center, Shenzhen 518028, China
    Department of Architecture, University of Cambridge, Cambridge CB2 1PX, UK
    These authors contributed equally to this work.)

  • Yue Li

    (Shenzhen Health Development Research and Data Management Center, Shenzhen 518028, China
    Department of Architecture, University of Cambridge, Cambridge CB2 1PX, UK
    These authors contributed equally to this work.)

  • Yi Zheng

    (Shenzhen Health Development Research and Data Management Center, Shenzhen 518028, China)

  • Binglun Wu

    (Department of Structural Reform and Primary Health Care, Shenzhen Municipal Health Commission, Shenzhen 518031, China)

  • Ronita Bardhan

    (Department of Architecture, University of Cambridge, Cambridge CB2 1PX, UK)

  • Liqun Wu

    (Shenzhen Health Development Research and Data Management Center, Shenzhen 518028, China)

Abstract

(1) Background: Primary health care institutions (PHCI) play an important role in reducing health inequities and achieving universal health coverage. However, despite the increasing inputs of healthcare resources in China, the proportion of patient visits in PHCI keeps declining. In 2020, the advent of the COVID-19 pandemic further exerted a severe stress on the operation of PHCI due to administrative orders. This study aims to evaluate the efficiency change in PHCI and provide policy recommendations for the transformation of PHCI in the post-pandemic era. (2) Methods: Data envelope analysis (DEA) and the Malmquist index model were applied to estimate the technical efficiency of PHCI in Shenzhen, China, from 2016 to 2020. The Tobit regression model was then used to analyze the influencing factors of efficiency of PHCI. (3) Results: The results of our analysis reflect considerable low levels of technical efficiency, pure technical efficiency, and scale efficiency of PHCI in Shenzhen, China, in 2017 and 2020. Compared to years before the epidemic, the productivity of PHCI decreased by 24.6% in 2020, which reached the nadir, during the COVID-19 pandemic along with the considerable reduction of technological efficiency, despite the significant inputs of health personnel and volume of health services. The growth of technical efficiency of PHCI is significantly affected by the revenue from operation, percentage of doctors and nurses in health technicians, ratio of doctors and nurses, service population, proportion of children in the service population, and numbers of PHCI within one kilometer. (4) Conclusion: The technical efficiency significantly declines along with the COVID-19 outbreak in Shenzhen, China, with the deterioration of underlying technical efficiency change and technological efficiency change, regardless of the immense inputs of health resources. Transformation of PHCI such as adopting tele-health technologies to maximize primary care delivery is needed to optimize utilization of health resource inputs. This study brings insights to improve the performances of PHCI in China in response to the current epidemiologic transition and future epidemic outbreaks more effectively, and to promote the national strategy of Healthy China 2030.

Suggested Citation

  • Shujuan Chen & Yue Li & Yi Zheng & Binglun Wu & Ronita Bardhan & Liqun Wu, 2023. "Technical Efficiency Evaluation of Primary Health Care Institutions in Shenzhen, China, and Its Policy Implications under the COVID-19 Pandemic," IJERPH, MDPI, vol. 20(5), pages 1-21, March.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:4453-:d:1085581
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/5/4453/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/5/4453/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kuosmanen, Timo & Matin, Reza Kazemi, 2009. "Theory of integer-valued data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 192(2), pages 658-667, January.
    2. 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.
    3. Yasar A. Ozcan, 2008. "Health Care Benchmarking and Performance Evaluation," International Series in Operations Research and Management Science, Springer, number 978-0-387-75448-2, April.
    4. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    5. Rize Jing & Tingting Xu & Xiaozhen Lai & Elham Mahmoudi & Hai Fang, 2019. "Technical Efficiency of Public and Private Hospitals in Beijing, China: A Comparative Study," IJERPH, MDPI, vol. 17(1), pages 1-18, December.
    6. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    7. Xiaoyan Zhang & Xin Chen & Chen Chen & Yuxuan Wang & Kenyiti Shindo & Xiaojin Zhang, 2022. "The influence mechanism of psychological contract on primary medical staff's turnover intention in the context of COVID‐19 pandemic in China," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(5), pages 2936-2948, September.
    8. Zhou, Zhongliang & Zhao, Yaxin & Shen, Chi & Lai, Sha & Nawaz, Rashed & Gao, Jianmin, 2021. "Evaluating the effect of hierarchical medical system on health seeking behavior: A difference-in-differences analysis in China," Social Science & Medicine, Elsevier, vol. 268(C).
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. Ismet Sahin & Yasar Ozcan & Hacer Ozgen, 2011. "Assessment of hospital efficiency under health transformation program in Turkey," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(1), pages 19-37, March.
    4. Suhyeon Han & Shinyoung Park & Sejin An & Wonjun Choi & Mina Lee, 2023. "Research on Analyzing the Efficiency of R&D Projects for Climate Change Response Using DEA–Malmquist," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    5. Simona Alfiero & Laura Broccardo & Massimo Cane & Alfredo Esposito, 2018. "High Performance Through Innovation Process Management in SMEs. Evidence from the Italian wine sector," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(3), pages 87-110.
    6. Jens J. Krüger, 2020. "Long‐run productivity trends: A global update with a global index," Review of Development Economics, Wiley Blackwell, vol. 24(4), pages 1393-1412, November.
    7. Pontus Mattsson & Jonas Månsson & Christian Andersson & Fredrik Bonander, 2018. "A bootstrapped Malmquist index applied to Swedish district courts," European Journal of Law and Economics, Springer, vol. 46(1), pages 109-139, August.
    8. Alexander Cotte Poveda, 2012. "Estimating Effectiveness of the Control of Violence and Socioeconomic Development in Colombia: An Application of Dynamic Data Envelopment Analysis and Data Panel Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 105(3), pages 343-366, February.
    9. Don U.A. Galagedera & Piyadasa Edirisuriya, 2004. "Performance of Indian commercial banks (1995-2002): an application of data envelopment analysis and Malmquist productivity index," Finance 0408006, University Library of Munich, Germany.
    10. Ali Kabasakal & Aziz Kutlar & Murat Sarikaya, 2015. "Efficiency determinations of the worldwide railway companies via DEA and contributions of the outputs to the efficiency and TFP by panel regression," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(1), pages 69-88, March.
    11. Alessandra Cepparulo & Gilles Mourre, 2020. "How and How Much? The Growth-Friendliness of Public Spending through the Lens," European Economy - Discussion Papers 132, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    12. Chen, Xiang & Grifell-Tatjé, Emili & Fu, Tsu-Tan, 2023. "A profit difference decomposition model for measuring group performance: an application to Chinese and Taiwanese commercial banks," Omega, Elsevier, vol. 120(C).
    13. Muliaman Hadad & Maximilian Hall & Karligash Kenjegalieva & Wimboh Santoso & Richard Simper, 2011. "Banking efficiency and stock market performance: an analysis of listed Indonesian banks," Review of Quantitative Finance and Accounting, Springer, vol. 37(1), pages 1-20, July.
    14. Finn Førsund, 2013. "Weight restrictions in DEA: misplaced emphasis?," Journal of Productivity Analysis, Springer, vol. 40(3), pages 271-283, December.
    15. Miguel SARMIENTOO & Andrés CEPEDA & Hernando MUTIS & Juan F. PÉREZ, 2013. "Nueva Evidencia sobre la Eficiencia de la Banca," Archivos de Economía 10705, Departamento Nacional de Planeación.
    16. Houyem Zrelli & Abdullah H. Alsharif & Iskander Tlili, 2020. "Malmquist Indexes of Productivity Change in Tunisian Manufacturing Industries," Sustainability, MDPI, vol. 12(4), pages 1-20, February.
    17. Pastor, Jesus T. & Lovell, C.A. Knox & Aparicio, Juan, 2020. "Defining a new graph inefficiency measure for the proportional directional distance function and introducing a new Malmquist productivity index," European Journal of Operational Research, Elsevier, vol. 281(1), pages 222-230.
    18. Tumaniants, Karen A. (Туманянц, Карэн) & Sesina, Julia E. (Сесина, Юлия), 2017. "Social Expenditures of Russian Regions in Terms of “Input-Output” [Расходы На Социальную Политику Российских Регионов В Координатах «Затраты — Результат»]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 128-149, October.
    19. Wang, Lan-Hsun & Liao, Shu-Yi & Huang, Mao-Lung, 2022. "The growth effects of knowledge-based technological change on Taiwan’s industry: A comparison of R&D and education level," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 525-545.
    20. Necmi Avkiran & Alan McCrystal, 2014. "Intertemporal analysis of organizational productivity in residential aged care networks: scenario analyses for setting policy targets," Health Care Management Science, Springer, vol. 17(2), pages 113-125, June.

    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:20:y:2023:i:5:p:4453-:d:1085581. 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.