Abstract

The rapid development of socio-economic has challenged pediatric health services in the new era. Assessing the efficiency of pediatric health services in China and utilizing them will facilitate the continued and stable development of pediatric health services in the face of these challenges. Based on a Three-stage DEA model of generalized modified panel, this paper uses panel data from 31 provinces and cities in China from 2008 to 2019 to estimate efficiency of pediatric health services and analyze the influential factors influencing the efficiency of pediatric services. The research establishes a multi-dimensional evaluation model of input-output-environment-impact. Fully consider the transformation of input elements such as pediatric beds, technical experts, pediatric finance, and pediatric policies in technical, professional, and economic environments. And with the help of long-term and short-term service effects of pediatrics, pediatric income, pediatric infrastructure, social satisfaction and other factors to output. Objectively summarize the real service effect of pediatrics. The model corrects for the interference of technical and non-administrative factors and obtains the most realistic pediatric performance based on changing social dynamics. The study found: (1) while the efficiency of pediatric healthcare services in China's provincial areas has been increasing year by year, there are specific geographical differences, and further improvements and rational allocation of healthcare resources are needed. Among them, the southern developed regions are 16.25% higher than the average efficiency of the northern regions. The annual floating span is 9.54%. Geography is a key factor that dominates the efficiency gap.(2) There is significant redundancy and disparity in the resources invested in pediatric services, and optimization of the economic, technological, and professional environment will continue to eliminate the impact of redundancy and drive the growth of pediatric service efficiency.The redundant scale of various input elements accounted for 31.81%. It shows that nearly 30% of the input resources have not been fully utilized. Among them, the redundancy of beds is relatively small in China, only 21.77%. It shows that the construction of pediatric beds in China is relatively effective, but the pediatric redundancy in developed areas is only 3.24%, and the adjustment of input resources across regions is the key to the optimization of pediatric services. (3) Increase in the health care price index will have a negative effect on the efficiency of pediatric services. In contrast, an increase in urbanization levels, education levels, and birth rates will drive the optimization of pediatric service efficiency.

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