Exploring cross-city hospital visiting trips for medical service evaluation in urban agglomeration areas based on automobile navigation data

BACKGROUND: Understanding the supply-demand relationship of medical services is essential for regional planning. Existing city-scale studies typically exclude cross-city flows, whereas national-scale studies often overlook intra-city heterogeneity. In urban agglomerations, healthcare resources and transport infrastructure are usually planned by cities, although patients may cross city boundaries to seek care. The implications of cross-city trips for regional medical services remain insufficiently understood. Taking the Pearl River Delta as a case, this study investigates cross-city hospital visiting trips and their implications for medical service evaluation. METHODS: Using 91.2 million automobile navigation records collected in 2019, 1.37 million hospital visiting trips to Grade 3 hospitals were identified through a modified spatial join method. A population-hospital bipartite network and a multi-scale analytical framework were constructed. Cross-city demand and supply indices were developed at the city, subdistrict, and hospital scales to characterize cross-city medical service patterns and influencing factors. Accessibility and Gini coefficients were computed under intra-city and regional evaluation scenarios to assess how incorporating cross-city hospital visiting trips affects medical service evaluation. RESULTS: Based on automobile navigation data, 9.1% of identified hospital visiting trips crossed city boundaries. Guangzhou and Shenzhen served as dominant regional suppliers, with cross-city supply indices of 55.9% and 21.8%, respectively. Cross-city demand was negatively associated with distance to boundary, GDP per capita, and hospital beds. Cross-city service share was negatively associated with distance to boundary, whereas contributions to regional cross-city service provision were positively associated with hospital size and hospital grade. Incorporating cross-city flows increased accessibility in most peripheral areas and reduced the regional population-weighted Gini coefficient from 0.596 to 0.522. CONCLUSIONS: Based on automobile navigation data, cross-city hospital visiting trips constitute an important component of medical service utilization in urban agglomerations. At the subdistrict scale, cross-city demand was jointly associated with boundary proximity and local economic and medical conditions. At the hospital scale, the cross-city service share was higher among hospitals closer to city boundaries, whereas contributions to regional cross-city medical service provision were greater among larger and higher-grade hospitals. Evaluation frameworks relying solely on intra-city data tend to underestimate accessibility in boundary areas and, in most cases, overestimate the Gini coefficient.

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Journal
BMC Health Services Research
Published
2026-05-08
DOI
https://doi.org/10.1186/s12913-026-14649-1
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
0.00

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article

Exploring cross-city hospital visiting trips for medical service evaluation in urban agglomeration areas based on automobile navigation data

Jizhe Xia, Sa Ma, X H Yu, Renzhong Guo et al.
BMC Health Services Research
Urban Transport and Accessibility
article

Exploring cross-city hospital visiting trips for medical service evaluation in urban agglomeration areas based on automobile navigation data

Jizhe Xia, Sa Ma, X H Yu, Renzhong Guo, Zhengdong Huang
article en

Abstract

BACKGROUND: Understanding the supply-demand relationship of medical services is essential for regional planning. Existing city-scale studies typically exclude cross-city flows, whereas national-scale studies often overlook intra-city heterogeneity. In urban agglomerations, healthcare resources and transport infrastructure are usually planned by cities, although patients may cross city boundaries to seek care. The implications of cross-city trips for regional medical services remain insufficiently understood. Taking the Pearl River Delta as a case, this study investigates cross-city hospital visiting trips and their implications for medical service evaluation. METHODS: Using 91.2 million automobile navigation records collected in 2019, 1.37 million hospital visiting trips to Grade 3 hospitals were identified through a modified spatial join method. A population-hospital bipartite network and a multi-scale analytical framework were constructed. Cross-city demand and supply indices were developed at the city, subdistrict, and hospital scales to characterize cross-city medical service patterns and influencing factors. Accessibility and Gini coefficients were computed under intra-city and regional evaluation scenarios to assess how incorporating cross-city hospital visiting trips affects medical service evaluation. RESULTS: Based on automobile navigation data, 9.1% of identified hospital visiting trips crossed city boundaries. Guangzhou and Shenzhen served as dominant regional suppliers, with cross-city supply indices of 55.9% and 21.8%, respectively. Cross-city demand was negatively associated with distance to boundary, GDP per capita, and hospital beds. Cross-city service share was negatively associated with distance to boundary, whereas contributions to regional cross-city service provision were positively associated with hospital size and hospital grade. Incorporating cross-city flows increased accessibility in most peripheral areas and reduced the regional population-weighted Gini coefficient from 0.596 to 0.522. CONCLUSIONS: Based on automobile navigation data, cross-city hospital visiting trips constitute an important component of medical service utilization in urban agglomerations. At the subdistrict scale, cross-city demand was jointly associated with boundary proximity and local economic and medical conditions. At the hospital scale, the cross-city service share was higher among hospitals closer to city boundaries, whereas contributions to regional cross-city medical service provision were greater among larger and higher-grade hospitals. Evaluation frameworks relying solely on intra-city data tend to underestimate accessibility in boundary areas and, in most cases, overestimate the Gini coefficient.

BMC Health Services Research
Southwest University (CN), Shenzhen University (CN), Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality (CN), Urban Planning & Design Institute of Shenzhen (China) (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 5%
Urban Transport and Accessibility
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