Spatially heterogeneous and nonlinear factors influencing intercity patient mobility for chronic kidney disease: a nationwide study in China

Abstract Uneven distribution of high-quality nephrology care in China has driven rising intercity patient mobility for chronic kidney disease (CKD). This study examined the spatial correlates of this mobility using over 4 million cross-city hospitalization records from 2014 to 2018. First, the Geodetector model was used to identify the key factors and their complex interactions driving patient inflows and outflows, including socioeconomic status, healthcare resource availability, and transportation accessibility. Then, multiscale geographically weighted regression (MGWR) was applied to explore geographical heterogeneity in the influence of these factors on intercity patient mobility. According to the Geodetector model, the leading correlates of patient outflows included hospital bed density, doctor density, and population growth rate, with evident nonlinear and synergistic associations. Patient inflows were mainly influenced by nephrology workforce availability and population structure. MGWR analysis revealed substantial spatial variation in the associations of general and nephrology-specific healthcare resources on intercity patient mobility, underscoring the complex interaction between healthcare capacity and geographic context. This study proposes a novel framework for understanding the spatial correlates of intercity CKD patient mobility in China and highlights the geographic heterogeneity of their associations. The findings support policies aimed at improving the equity and efficiency of CKD care across regions.