Wang Yifei, Zhai Duanqiang, Xie Wuqi, Huang Shan
College of Architecture and Urban Planning, Tongji University, Shanghai, China.
Innovation and Research Center, Shanghai Tongji Urban Planning and Design Institute Co., Ltd., Shenyang, China.
Front Public Health. 2025 Jul 25;13:1640070. doi: 10.3389/fpubh.2025.1640070. eCollection 2025.
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.
在快速城市化和人口老龄化加速的背景下，医疗设施分布的空间不平等已成为沈阳面临的紧迫挑战。城市核心区域高水平医疗资源过度集中，而周边地区基层医疗服务供给不足这一双重问题，凸显了医疗公平与效率方面的系统性失衡。基于空间公平概念，本研究运用先进的空间分析和大数据融合技术，整合了多源数据，包括人口统计数据、设施位置数据和交通网络数据。通过核密度估计、双变量空间自相关分析和服务区网络分析，全面评估了三级、二级和基层医疗设施的空间分布和可达性模式。为了量化空间不平等，引入了基尼系数，证实了各行政单位人均医疗资源分配存在显著差异。通过结合服务覆盖范围建模和区位配置（LA）模型，本研究识别出“医疗服务荒漠”，并提出了与中国分级诊疗体系相契合的多层次空间优化策略。模拟结果显示出明显的“中心集中 - 周边稀缺”模式，沈北和浑南等地区的不足尤为突出。规划干预建议新增6家三级医院和6家二级/基层医院，同时对260个社区卫生服务站进行空间重新布局，将总体人口覆盖率提高到98.98%。本研究为通过“核心疏解 - 周边强化”方法改善医疗空间公平性提供了实证依据和可推广的规划框架。它还强调了政策引导下开发商参与和协同治理在加强新城市化地区服务供给方面的作用。该研究为构建一个可及、高效且有韧性的多层次医疗体系提供了实际见解，支持了“健康沈阳”倡议的目标，并为类似城市环境提供了可复制的模式。
