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A study on the efficiency of pediatric healthcare services and its influencing factors in China ——estimation of a three-stage DEA model based on provincial-level data

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  • Liu, Hongda
  • Wu, Wangqiang
  • Yao, Pinbo

Abstract

The rapid development of socio-economic has challenged pediatric health services in the new era. Assessing the efficiency of pediatric health services in China and utilizing them will facilitate the continued and stable development of pediatric health services in the face of these challenges. Based on a Three-stage DEA model of generalized modified panel, this paper uses panel data from 31 provinces and cities in China from 2008 to 2019 to estimate efficiency of pediatric health services and analyze the influential factors influencing the efficiency of pediatric services. The research establishes a multi-dimensional evaluation model of input-output-environment-impact. Fully consider the transformation of input elements such as pediatric beds, technical experts, pediatric finance, and pediatric policies in technical, professional, and economic environments. And with the help of long-term and short-term service effects of pediatrics, pediatric income, pediatric infrastructure, social satisfaction and other factors to output. Objectively summarize the real service effect of pediatrics. The model corrects for the interference of technical and non-administrative factors and obtains the most realistic pediatric performance based on changing social dynamics. The study found: (1) while the efficiency of pediatric healthcare services in China's provincial areas has been increasing year by year, there are specific geographical differences, and further improvements and rational allocation of healthcare resources are needed. Among them, the southern developed regions are 16.25% higher than the average efficiency of the northern regions. The annual floating span is 9.54%. Geography is a key factor that dominates the efficiency gap.(2) There is significant redundancy and disparity in the resources invested in pediatric services, and optimization of the economic, technological, and professional environment will continue to eliminate the impact of redundancy and drive the growth of pediatric service efficiency.The redundant scale of various input elements accounted for 31.81%. It shows that nearly 30% of the input resources have not been fully utilized. Among them, the redundancy of beds is relatively small in China, only 21.77%. It shows that the construction of pediatric beds in China is relatively effective, but the pediatric redundancy in developed areas is only 3.24%, and the adjustment of input resources across regions is the key to the optimization of pediatric services. (3) Increase in the health care price index will have a negative effect on the efficiency of pediatric services. In contrast, an increase in urbanization levels, education levels, and birth rates will drive the optimization of pediatric service efficiency.

Suggested Citation

  • Liu, Hongda & Wu, Wangqiang & Yao, Pinbo, 2022. "A study on the efficiency of pediatric healthcare services and its influencing factors in China ——estimation of a three-stage DEA model based on provincial-level data," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
  • Handle: RePEc:eee:soceps:v:84:y:2022:i:c:s0038012122001008
    DOI: 10.1016/j.seps.2022.101315
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    References listed on IDEAS

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    1. Ferreira, Diogo Cunha & Nunes, Alexandre Morais & Marques, Rui Cunha, 2018. "Doctors, nurses, and the optimal scale size in the Portuguese public hospitals," Health Policy, Elsevier, vol. 122(10), pages 1093-1100.
    2. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    3. Li, Lan-bing & Liu, Bing-lian & Liu, Wei-lin & Chiu, Yung-Ho, 2017. "Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 24-33.
    4. Paul Woolley & Ron Bird, 2003. "Economic implications of passive investing," Journal of Asset Management, Palgrave Macmillan, vol. 3(4), pages 303-312, March.
    5. Ferreira, D.C. & Marques, R.C. & Nunes, A.M., 2018. "Economies of scope in the health sector: The case of Portuguese hospitals," European Journal of Operational Research, Elsevier, vol. 266(2), pages 716-735.
    6. Hongda Liu & Pinbo Yao & Xiaoxia Wang & Jialiang Huang & Liying Yu, 2021. "Research on the Peer Behavior of Local Government Green Governance Based on SECI Expansion Model," Land, MDPI, vol. 10(5), pages 1-26, May.
    7. Ferreira, Diogo Cunha & Marques, Rui Cunha & Nunes, Alexandre Morais & Figueira, José Rui, 2021. "Customers satisfaction in pediatric inpatient services: A multiple criteria satisfaction analysis," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    8. Fenn, Paul & Vencappa, Dev & Diacon, Stephen & Klumpes, Paul & O'Brien, Chris, 2008. "Market structure and the efficiency of European insurance companies: A stochastic frontier analysis," Journal of Banking & Finance, Elsevier, vol. 32(1), pages 86-100, January.
    9. Sonila Tomini & Wim Groot & Milena Pavlova, 2012. "Paying informally in the Albanian health care sector: a two-tiered stochastic frontier model," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(6), pages 777-788, December.
    10. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    11. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    2. zhang, Ling & Niu, Guangli, 2023. "Role of financial performance and natural resources development on economic recovery: Empirical evidence from an Asian perspective," Resources Policy, Elsevier, vol. 85(PA).

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