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. 2023 Sep 15;23(1):995.
doi: 10.1186/s12913-023-09979-3.

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

Wanmin Su  1   2 , Yatian Hou  2 , Mengge Huang  2 , Jiamian Xu  1 , Qingfeng Du  3   4 , Peixi Wang  5   6
Affiliations

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

Wanmin Su et al. BMC Health Serv Res. .

Abstract

Background: Primary 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.

Methods: This 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.

Results: The 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.

Conclusions: Substantial 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.

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

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The methodological framework of the improved three-stage DEA model
Fig. 2
Fig. 2
The trend in the efficiency of PHC institutions in stage 1 from 2012 to 2020
Fig. 3
Fig. 3
The trend in the efficiency of PHC institutions in stage 3 from 2012 to 2020
Fig. 4
Fig. 4
The average TE values of PHC institutions in China from 2012 to 2020
Fig. 5
Fig. 5
Four groups of regions in China
Fig. 6
Fig. 6
Three types of efficiency of PHC institutions in the four regions
Fig. 7
Fig. 7
The trend in the efficiency of PHC institutions in the four regions from 2012 to 2020
Fig. 8
Fig. 8
Categorization of the PTE and SE of 31 provinces. a and b denote the efficiency scores in stage 1 and stage 3, respectively
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References

    1. Yan C, Liao H, Ma Y, Wang J. The impact of health care reform since 2009 on the efficiency of primary health services: a provincial panel data study in China. Front Public Health. 2021;9:735654. doi: 10.3389/fpubh.2021.735654. - DOI - PMC - PubMed
    1. The World Bank and World Health Organization. Healthy China: Deepening Health Reform in China. Building High-Quality and Value-Based Service Delivery. Peking: China Finance and Economy Media Group; 2018. p. 39.
    1. Planning, Development, and Information Technology Division: Statistical bulletin on the development of health care in China in 2021. 2022. http://www.nhc.gov.cn/guihuaxxs/s3586s/202207/51b55216c2154332a660157abf... Accessed 3 Mar 2023.
    1. National Health Commission of the People's Republic of China. China Health Care Statistics Yearbook. Peking: Peking Union Medical College Press; 2021. p. 217–33.
    1. Li X, Krumholz HM, Yip W, Cheng KK, De Maeseneer J, Meng Q, et al. Quality of primary health care in China: challenges and recommendations. Lancet. 2020;395:1802–1812. doi: 10.1016/S0140-6736(20)30122-7. - DOI - PMC - PubMed

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