Qiu Zenghui, Fu Meiling, Liu Lanfang, Yao Lan, Yin Shanshan, Chen Wen, Huang Jingjing, Jin Jiahui
The School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 40030, China.
Shenzhen Health Development Research and Data Management Center, Shenzhen, 518028, China.
Sci Rep. 2025 Apr 22;15(1):13936. doi: 10.1038/s41598-025-96922-7.
Examined the synergistic development and spatio-temporal evolution of China's multi-level medical insurance system (MMIS) on a macroscopic level. We assess the comprehensive development of the MMIS across China's 31 provinces from 2011 to 2020 by constructing a comprehensive indicators evaluation model. Subsequently, a coupling coordination index (CCI) model is employed to provide precise insights into the coupling coordination effects among various medical insurance schemes comprising MMIS. Lastly, spatial autocorrelation analysis is conducted to evaluate both the global and local spatio-temporal evolutionary characteristics of MMIS. The CCI of MMIS at the national average level exhibited a fluctuating upward trend, progressing from the moderate disorder recession degree (0.287) in 2011 to the well-coordinated degree (0.887) in 2020. However, the majority of provinces (83.87%) still lingered within the realm of barely coordinated degree ([0.500-0.600]). Specifically, the CCI within the eastern coastal region surpassed that of the western and central regions, with the central region showing the most pronounced increase in CCI. Over the past decade, MMIS demonstrated significant spatial agglomeration, as evidenced by the global Moran's I ranging from [0.1668-0.3037]. Furthermore, findings from local spatial autocorrelation analysis suggest a gradual attenuation in the spatial clustering disparity of CCI across various provinces. Government ought to focus on the spatio-temporal evolution patterns of MMIS, and strengthen cooperation between the government and market in health governance, while utilizing information technology and data sharing to improve the overall quality of medical insurance benefits.
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