ArticleBMC health services research2023
Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach.
Article in BMC health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Primary health care as the main guarantor of a healthy population in the country and a global challenge in the world: a systematic review.F1000Research · 2024Pooled it
- Operational efficiency in public infectious disease hospitals across 31 provinces in China: a three-phase data envelopment analysis.BMJ open · 2026Article
- Training needs and service capacity gaps among primary healthcare workers in Henan Province, China: a large cross-sectional study.BMC primary care · 2026Article
- The impact of digital economy on primary healthcare institution efficiency: evidence from China based on spatial effect analysis.BMC primary care · 2026Article
- Efficiency assessment and demand forecasting in China's primary healthcare system: a comprehensive SBM-DDF-GML analysis.Frontiers in public health · 2026Article
- A study on the efficiency and spatial correlation of health resource allocation in Chinese hospitals.PloS one · 2026Article
- The efficiency of secondary-level hospitals in hard-to-reach and non-hard-to-reach areas in Bangladesh: a data envelopment analysis approach.BMC health services research · 2025Article
- How to improve the construction efficiency of key medical disciplines: a three-stage DEA.Cost effectiveness and resource allocation : C/E · 2025Article
- Measuring the effect of deprivation on primary health care performance using data envelopment analysis and Malmquist Indices.Health care management science · 2025Article
- Patient perceived service quality profiles of primary health care associated with usual source of care: a latent profile analysis.Frontiers in medicine · 2025Article
- Based on regional heterogeneity: measurement of hospital service efficiency and analysis of spatial effects.Frontiers in public health · 2025Article
- Efficiency analysis of primary health care resources: DEA and Tobit regression evidence from village clinics in Jiangsu Province.Frontiers in public health · 2025Article
- The effect of patient participation on trust in primary health care physicians among patients with chronic diseases: the mediating role of perceived value.Frontiers in public health · 2025Article
- Evaluating the operational efficiency of the compact urban medical group in Qiqihar based on the three-stage DEA and Malmquist index model.Frontiers in public health · 2025Article
- Comprehensive evaluation of primary health care service capacity in China based on TOPSIS and RSR methods.Frontiers in public health · 2025Article
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- Resource allocation efficiency in 68 county-level traditional Chinese medicine hospitals in China: a data envelopment analysis.BMJ open · 2024Article
- Modelling efficiency in primary healthcare using the DEA methodology: an empirical analysis in a healthcare district.BMC health services research · 2024Article
- Efficiency evaluation and promoter identification of primary health care system in China: an enhanced DEA-Tobit approach.BMC health services research · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
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Abstract
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.