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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
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    References listed on IDEAS

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    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, March.
    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).
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