Resource allocation efficiency and population alignment of community health centers: a home-based healthcare perspective

Background Faced with the dual pressures of a global aging population and strained health resources, community health service centers serve as a hub connecting hospitals with home-based healthcare. The efficiency of their resource allocation and their alignment with population needs directly impact the operational effectiveness of the primary health care system. Given the significant disparities in socioeconomic development across China’s 31 provincial-level administrative regions, a systematic assessment is needed to determine whether the spatial distribution of community health service resources aligns with population size and to evaluate their operational efficiency. Methods Based on official data from China’s National Bureau of Statistics and the National Health Commission for the period 2015–2024, this study uses the Health Resource Aggregation Degree (HRAD) index to measure the spatial alignment between community health service resources and the permanent resident population, employs a three-stage DEA model to evaluate their static allocation efficiency, and utilizes the Malmquist index to track dynamic trends in total factor productivity (TFP). Results HRAD analysis showed that the density of community health service resources in eastern provinces was significantly higher than in central and western provinces, with the difference between the highest and lowest HRAD values exceeding 10,000-fold, indicating stark interprovincial disparities in the alignment of resources and population. After three-stage DEA adjustment, the TE decreased from 0.635 to 0.624, with PTE rising slightly and SE declining; The TFP was 0.942, showing an annual decline of 5.8%. Five provinces achieved efficiency improvements, one province remained stable, and the remaining 25 provinces all showed a downward trend. The lag in technological progress (TC = 0.943) was a key contributing factor to the decline in efficiency. Conclusion China’s community health care resources face significant interprovincial spatial imbalances and declining efficiency, and lagging technological progress is one of the key factors contributing to this decline in efficiency. It is recommended that, while increasing the total investment in resources, priority be given to promoting technology transfer and service model innovation in central and western regions, and that differentiated regional resource allocation strategies be implemented. This study provides empirical evidence for community health resource planning at the provincial level and offers a practical, evidence-based model for other countries and regions facing population aging to improve their primary healthcare systems.

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Journal
Frontiers in Public Health
Published
2026-10-30
DOI
https://doi.org/10.3389/fpubh.2026.1936096
Primary Topic
Efficiency Analysis Using DEA
Type
article
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article

Resource allocation efficiency and population alignment of community health centers: a home-based healthcare perspective

刘兰秋, Zhonghua Luo, Binghong Guo, Yaning Zhang et al.
3 links
Frontiers in Public Health
Efficiency Analysis Using DEA
article

Resource allocation efficiency and population alignment of community health centers: a home-based healthcare perspective

刘兰秋, Zhonghua Luo, Binghong Guo, Yaning Zhang, Yahui Ba, Yilan Chen
article en

Abstract

Background Faced with the dual pressures of a global aging population and strained health resources, community health service centers serve as a hub connecting hospitals with home-based healthcare. The efficiency of their resource allocation and their alignment with population needs directly impact the operational effectiveness of the primary health care system. Given the significant disparities in socioeconomic development across China’s 31 provincial-level administrative regions, a systematic assessment is needed to determine whether the spatial distribution of community health service resources aligns with population size and to evaluate their operational efficiency. Methods Based on official data from China’s National Bureau of Statistics and the National Health Commission for the period 2015–2024, this study uses the Health Resource Aggregation Degree (HRAD) index to measure the spatial alignment between community health service resources and the permanent resident population, employs a three-stage DEA model to evaluate their static allocation efficiency, and utilizes the Malmquist index to track dynamic trends in total factor productivity (TFP). Results HRAD analysis showed that the density of community health service resources in eastern provinces was significantly higher than in central and western provinces, with the difference between the highest and lowest HRAD values exceeding 10,000-fold, indicating stark interprovincial disparities in the alignment of resources and population. After three-stage DEA adjustment, the TE decreased from 0.635 to 0.624, with PTE rising slightly and SE declining; The TFP was 0.942, showing an annual decline of 5.8%. Five provinces achieved efficiency improvements, one province remained stable, and the remaining 25 provinces all showed a downward trend. The lag in technological progress (TC = 0.943) was a key contributing factor to the decline in efficiency. Conclusion China’s community health care resources face significant interprovincial spatial imbalances and declining efficiency, and lagging technological progress is one of the key factors contributing to this decline in efficiency. It is recommended that, while increasing the total investment in resources, priority be given to promoting technology transfer and service model innovation in central and western regions, and that differentiated regional resource allocation strategies be implemented. This study provides empirical evidence for community health resource planning at the provincial level and offers a practical, evidence-based model for other countries and regions facing population aging to improve their primary healthcare systems.

Frontiers in Public HealthVol. 14
Capital Medical University (CN), Gansu University of Traditional Chinese Medicine (CN)
Good health and well-being, Reduced inequalities
Openalex Percentile: Top 10%
Efficiency Analysis Using DEA
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