AUTHOR=Jiang Wei , Yang Boyi , Dai Xiaoli , Li Shanshan TITLE=Efficiency analysis of primary health care resources: DEA and Tobit regression evidence from village clinics in Jiangsu Province JOURNAL=Frontiers in Public Health VOLUME=Volume 13 - 2025 YEAR=2025 URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1515532 DOI=10.3389/fpubh.2025.1515532 ISSN=2296-2565 ABSTRACT=BackgroundVillage clinics are essential for delivering primary health care in rural China, yet their resource allocation efficiency remains a concern. Many clinics face challenges such as low technical efficiency, imbalanced resource distribution, and insufficient technological progress, which may hinder the delivery of quality healthcare services.MethodsThis study evaluates the resource allocation efficiency of village clinics across 13 cities in Jiangsu Province, China, using Data Envelopment Analysis. The Malmquist Productivity Index was applied to assess efficiency changes over time, and Tobit regression was employed to identify influencing factors.ResultsThe overall efficiency of village clinic resource allocation in Jiangsu Province is suboptimal. In 2022, the average technical efficiency was 0.869, with seven cities classified as inefficient. Among them, three exhibited decreasing returns to scale, while four demonstrated increasing returns to scale. Reducing the number of village clinics and health technicians while increasing medical revenue could improve efficiency. From 2015 to 2022, the average Malmquist Productivity Index was 0.96, with a significant decline of 11.6% in 2021–2022, primarily due to a 6.8% decrease in technological change. Random-effects Tobit regression revealed that population density positively correlates with technical efficiency (coefficient = 0.0014, p < 0.05), whereas per capita disposable income, healthcare fiscal expenditure, and urbanization rate showed no statistically significant effects.ConclusionThe resource allocation efficiency of village clinics in Jiangsu Province is insufficient, with technological change being a key driver of efficiency fluctuations. Population density plays a significant role in efficiency variation. To enhance efficiency, optimizing resource allocation strategies and promoting technological advancements are essential for strengthening rural primary health care.