Background: The distribution of medical resources in China is seriously imbalanced due to imbalanced economic development in the country; unbalanced distribution of medical resources makes patients try to seek better health services. Against this backdrop, this study aims to analyze the spatial network characteristics and spatial effects of China’s health economy, and then find evidence that affects patient mobility. Methods: Data for this study were drawn from the China Health Statistical Yearbooks and China Statistical Books. The gravitational value of China’s health spatial network was calculated to establish a network of gravitational relationships. The social network analysis method was used for centrality analysis and spillover effect analysis. Results: A gravity correlation matrix was constructed among provinces by calculating the gravitational value, indicating the spatial relationships of different provinces in the health economic network. Economically developed provinces, such as Shanghai and Jiangsu, are at the center of the health economic network (centrality degree = 93.333). These provinces also play a strong intermediary role in the network and have connections with other provinces. In the CONCOR analysis, 31 provinces are divided into four blocks. The spillover effect of the blocks indicates provinces with medical resource centers have beneficial effects, while provinces with insufficient resources have obvious spillover effects. Conclusion: There is a significant gap in the geographical distribution of medical resources, and the health economic spatial network structure needs to be improved. Most medical resources are concentrated in economically developed provinces, and these provinces’ positions in the health economic spatial network are becoming more centralized. By contrast, economically underdeveloped regions are at the edge of the network, causing patients to move to provinces with medical resource centers. There are health risks of the increasing pressure to seek medical treatment in developed provinces with abundant medical resources.

Background: The equity of public resources triggered by city shrinkage is a global challenge. Significantly, the impact of city shrinkage on the allocation of health service resources needs to be better understood. This study explores the impact of population change on government investment and health service delivery in shrinking cities.Data and method: Using data from China’s Urban Statistical Yearbook (2010–2020), we employ regression discontinuity (RD) and fixed-effect models to examine the causal relationship between city shrinkage and health service provision.Result: Shrinking cities show significant disparities in health resources, particularly in bed numbers (−1,167.58, p < 0.05) and doctor availability (−538.54, p < 0.05). Economic development (p < 0.01) and financial autonomy (p < 0.01) influence hospital bed distribution. Investments in public services (primary schools and teachers, p < 0.01) affect health resource delivery. Robustness tests support our results.Conclusion: This study reveals how city shrinkage disrupts health service provision and equity, establishing a causal relationship between city shrinkage/expansion and health resource allocation, emphasizing the imbalance caused by urban population changes. City expansion intensifies competition for health resources, while shrinking cities struggle to provide adequate resources due to government reluctance. Policymakers should adapt health resource allocation strategies to meet patient demands in changing urban landscapes.

Background: The distribution of medical resources in China is seriously imbalanced due to imbalanced economic development in the country, and unbalanced distribution of medical resources makes patients try to seek better health services. Against this backdrop, this study aims to analyse the spatial network characteristics and spatial effects of China's health economy ,and then find evidence that affects patient mobility. Methods: Data for this study were drawn from the China Health Statistical Yearbooks and China Statistical Books. The gravitational value of China’s health spatial network was calculated to establish a network of gravitational relationships. The social network analysis method is used for centrality analysis and spillover effect analysis. Based on the gravitational value, we used indicators for visits, health expenditure, GDP and geographical distance, as well as an illustrative index for the population, bed utilization, and burden of consultations per day. Results: A gravity correlation matrix was constructed among provinces by calculating the gravitational value, indicating the spatial relationships of different provinces in the health economic network. Economically developed provinces, such as Shanghai and Jiangsu, are at the centre of the health economic network (centrality degree=93.333). These provinces also play a strong intermediary role in the network and have connections with other provinces. In the CONCOR analysis, 31 provinces are divided into four blocks. In the traditional meaning analysis, the gap between eastern and western China is still obvious. In comparing the northern and southern regions, this study finds that the concentration of medical resources in northern provinces seems to be higher. The spillover effect of the blocks indicates provinces with medical resource centres have beneficial effects, while provinces with insufficient resources have obvious spillover effects. Conclusion: There is a significant gap in the geographical distribution of medical resources, and the health economic spatial network structure needs to be improved. Most medical resources are concentrated in economically developed provinces, and these provinces’ positions in the health economic spatial network are becoming more centralized. By contrast, economically underdeveloped regions are at the edge of the network, causing patients to move to provinces with medical resource centres. There are health risks of the increasing