Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach

BMC Health Services Research

Research

Jiamian Xu¹  Wanmin Su²  Peixi Wang²  Qingfeng Du³  Yatian Hou⁴  Mengge Huang⁴ 

[1] General Practice Center, The Seventh Affiliated Hospital, Southern Medical University, 528244, Foshan, Guangdong, People’s Republic of China;General Practice Center, The Seventh Affiliated Hospital, Southern Medical University, 528244, Foshan, Guangdong, People’s Republic of China;School of Nursing and Health, Henan University, 475004, Kaifeng, Henan, People’s Republic of China;General Practice Center, The Seventh Affiliated Hospital, Southern Medical University, 528244, Foshan, Guangdong, People’s Republic of China;School of Traditional Chinese Medicine, Southern Medical University, 510515, Guangzhou, Guangdong, People’s Republic of China;School of Nursing and Health, Henan University, 475004, Kaifeng, Henan, People’s Republic of China;

关键词: Primary health care institutions;    Efficiency measurement;    Super-efficiency SBM DEA model;    Three-stage DEA model;    Global benchmarking technique;    External environment factors;    China;   

DOI  :  10.1186/s12913-023-09979-3

 received in 2023-04-09, accepted in 2023-08-28,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundPrimary health care (PHC) institutions are key to realizing the main functions of the health care system. Since the new health care reform in 2009, the Chinese government has invested heavily in PHC institutions and launched favorable initiatives to improve the efficiency of such institutions. This study is designed to gauge the efficiency of PHC institutions by using 2012–2020 panel data covering 31 provinces in China.MethodsThis study applied an improved three-stage data envelopment analysis (DEA) model to evaluate the efficiency of PHC institutions in China. Unlike the traditional three-stage DEA model, the input-oriented global super-efficiency slack-based measurement (SBM) DEA model is used to calculate the efficiency in the first and third stages of the improved three-stage DEA model, which not only allows the effects of environmental factors and random noise to be taken into account but also deal with the problem of slack, super-efficiency and the comparability of interperiod efficiency values throughout the efficiency measurement.ResultsThe results show that the efficiency of PHC institutions has been overestimated due to the impact of external environmental factors and random noise. From 2012 to 2020, the efficiency of PHC institutions displayed a downward trend. Moreover, there are significant differences in the efficiency of PHC institutions between regions, with the lowest efficiency being found in the northeast region. The efficiency of PHC institutions is significantly affected by residents’ annual average income, per capita GDP, population density, the percentage of the population aged 0–14, the percentage of the population aged 65 and older, the number of people with a college education and above per 100,000 residents, and the proportion of the urban population.ConclusionsSubstantial investment in PHC institutions has not led to the expected efficiency gains. Therefore, more effective measures should be taken to improve the efficiency of PHC institutions in China based on local conditions. This study provides a new analytical approach to calculating the efficiency of PHC institutions, and this approach can be applied to efficiency evaluation either in other fields or in other countries.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

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