A study of spatial and temporal variability in the equitable and efficient allocation of primary health care resources

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Abstract

Background China is a large developing country, and the allocation of primary health care resources is of particular importance, as it concerns the right to health resource utilization of all citizens. Despite the Chinese government's efforts to strengthen primary health care services, there is still room for improvement. The present study has been designed to assess the regional equity and utilization efficiency of primary health care resource allocation in China from 2014 to 2021. In addition, the study will analyse the dynamic evolution patterns and key influencing factors, and formulate relevant recommendations. METHODS The Dagum Gini coefficient was utilized to evaluate the utilization of primary healthcare institutions in each region. Subsequently, the DEAP 2.1 software was employed to conduct data envelopment analysis (DEA). The BCC model and the Malquist model were then employed to analyse the input and output efficiencies of resources, respectively. Finally, the coupled coordination model was employed to analyse the synergistic indices of equity and efficiency. RESULTS The overall Gini coefficient of China is influenced by the contribution of interregional disparities, with North China, Northeast China, East China, and Central China exhibiting inefficient utilization of health resources. The national level of technological progress has exhibited a decline of an average of 4.The annual growth rate of the total factor productivity (TFP) of other provinces, with the exception of Zhejiang, Guizhou, and Shaanxi Provinces, has consistently maintained a value below 1%. The decline in the TFP of Qinghai and Ningxia has been primarily constrained by the level of technological advancement. However, there has been a gradual enhancement in the degree of coupling and coordination between these regions. CONCLUSION The allocation of healthcare resources in China is marked by considerable regional disparities, necessitating the implementation of bespoke intervention strategies. The influence of technological progress is evident in the necessity to promote the intelligent upgrading of equipment and the training of targeted medical students. Concurrently, incentive mechanisms for technological innovation and urban-rural resource mobility should be established to realize the sustainable synergistic development of primary resources.

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