Spatial optimization of hierarchical healthcare facilities driven by multi-source data: a case study of Shenyang, China

Amid rapid urbanization and accelerated population aging, spatial inequality in the distribution of healthcare facilities has become a pressing challenge in Shenyang. The dual problem of overconcentration of high-level medical resources in the urban core and insufficient primary care provision in peripheral areas highlights systemic imbalances in healthcare equity and efficiency. Grounded in the concept of spatial equity, this study integrates multi-source data-including population statistics, facility locations, and transportation networks-using advanced spatial analysis and big data fusion techniques. Through kernel density estimation, bivariate spatial autocorrelation, and service area network analysis, the spatial distribution and accessibility patterns of healthcare facilities across tertiary, secondary, and primary levels are comprehensively evaluated. To quantify spatial inequity, the Gini coefficient is introduced, confirming significant disparities in per capita healthcare resource allocation across administrative units. By combining service coverage modeling and the Location-Allocation (LA) model, the study identifies "healthcare deserts" and proposes a multi-tiered spatial optimization strategy aligned with China's hierarchical diagnosis and treatment system. Simulation results demonstrate a pronounced "central concentration-peripheral scarcity" pattern, with particularly acute deficiencies in districts such as Shenbei and Hunnan. The planning intervention recommends the addition of six tertiary and six secondary/primary hospitals, along with the spatial reconfiguration of 260 community health service stations, increasing the overall population coverage rate to 98.98%. This research offers empirical evidence and a transferable planning framework for improving healthcare spatial equity through a "core decongestion-periphery reinforcement" approach. It also highlights the role of policy-guided developer participation and collaborative governance in enhancing service provision in newly urbanized areas. The study contributes practical insights for building an accessible, efficient, and resilient multi-level healthcare system, supporting the goals of the "Healthy Shenyang" initiative and offering a replicable model for similar urban contexts.

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Publication Details

Journal
Frontiers in Public Health
Published
2025-07-25
DOI
https://doi.org/10.3389/fpubh.2025.1640070
Citations
3
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
6.53
Controls
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article

Spatial optimization of hierarchical healthcare facilities driven by multi-source data: a case study of Shenyang, China

Duanqiang Zhai, Yifei Wang, Shan Huang, W. Xie
3 citations
Frontiers in Public Health
Urban Transport and Accessibility
6.53
article

Spatial optimization of hierarchical healthcare facilities driven by multi-source data: a case study of Shenyang, China

Duanqiang Zhai, Yifei Wang, Shan Huang, W. Xie
article en
3 citations

Abstract

Amid rapid urbanization and accelerated population aging, spatial inequality in the distribution of healthcare facilities has become a pressing challenge in Shenyang. The dual problem of overconcentration of high-level medical resources in the urban core and insufficient primary care provision in peripheral areas highlights systemic imbalances in healthcare equity and efficiency. Grounded in the concept of spatial equity, this study integrates multi-source data-including population statistics, facility locations, and transportation networks-using advanced spatial analysis and big data fusion techniques. Through kernel density estimation, bivariate spatial autocorrelation, and service area network analysis, the spatial distribution and accessibility patterns of healthcare facilities across tertiary, secondary, and primary levels are comprehensively evaluated. To quantify spatial inequity, the Gini coefficient is introduced, confirming significant disparities in per capita healthcare resource allocation across administrative units. By combining service coverage modeling and the Location-Allocation (LA) model, the study identifies "healthcare deserts" and proposes a multi-tiered spatial optimization strategy aligned with China's hierarchical diagnosis and treatment system. Simulation results demonstrate a pronounced "central concentration-peripheral scarcity" pattern, with particularly acute deficiencies in districts such as Shenbei and Hunnan. The planning intervention recommends the addition of six tertiary and six secondary/primary hospitals, along with the spatial reconfiguration of 260 community health service stations, increasing the overall population coverage rate to 98.98%. This research offers empirical evidence and a transferable planning framework for improving healthcare spatial equity through a "core decongestion-periphery reinforcement" approach. It also highlights the role of policy-guided developer participation and collaborative governance in enhancing service provision in newly urbanized areas. The study contributes practical insights for building an accessible, efficient, and resilient multi-level healthcare system, supporting the goals of the "Healthy Shenyang" initiative and offering a replicable model for similar urban contexts.

Frontiers in Public HealthVol. 13
Shenyang Institute of Engineering (CN), Tongji University (CN), Liaoning Planning and Design Institute of Post and Telecommunication (CN), Shanghai Tongji Urban Planning and Design Institute (CN), Shenyang Jianzhu University (CN)
Sustainable cities and communities
Openalex Percentile: Top 4%
Urban Transport and Accessibility
6.53
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