Work

Efficiency analysis of primary health care resources: DEA and Tobit regression evidence from village clinics in Jiangsu Province

Year: 2025

Type: article

Abstract: Background Village 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. Methods This 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. Results The 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. Conclusion The 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.

Source: Frontiers in Public Health

DOI: 10.3389/fpubh.2025.1515532

Authors: Wei Jiang, Boyi Yang, Xiaoli Dai, Shanshan Li

Institutions: Tongji Hospital, Huazhong University of Science and Technology

Language: English

Topic: Efficiency Analysis Using DEA

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Good health and well-being, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,801