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中国基层医疗服务的空间可达性评估与布局优化:以深圳为例

Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen.

作者信息

Chen Liutong, Zeng Huatang, Wu Liqun, Tian Qiannan, Zhang Ning, He Rongxin, Xue Hao, Zheng Junyao, Liu Jinlin, Liang Fengchao, Zhu Bin

机构信息

School of Public Health and Emergency Management Southern University of Science and Technology Shenzhen China.

Shenzhen Health Development Research and Data Management Center Shenzhen China.

出版信息

Geohealth. 2023 May 16;7(5):e2022GH000753. doi: 10.1029/2022GH000753. eCollection 2023 May.

Abstract

The unbalanced allocation of healthcare resources is a major challenge that hinders access to healthcare. Taking Shenzhen as an example, this study aimed to enhance equity in obtaining healthcare services, through measuring and visualizing the spatial accessibility of community healthcare centers (CHC), and optimizing CHC geospatial allocation. We used the number of health technicians per 10,000 to represent the CHC's service capacity, combined with resident points and census data to calculate the population the CHC needs to carry, and then analyzed the accessibility based on the Gaussian two-step floating catchment area method. In 2020, five regions in Shenzhen had better spatial accessibility scores: Nanshan (0.250), Luohu (0.246), Futian (0.244), Dapeng (0.226), and Yantian (0.196). The spatial accessibility of CHCs shows a gradual decrease from the city center to the edge, which is affected by economic and topographic factors. With the support of the maximal covering location problem model, we selected up to 567 candidate locations for the new CHC, which could improve Shenzhen's accessibility score from 0.189 to 0.361 and increase the coverage population by 63.46% within a 15-min impedance. By introducing spatial techniques and maps, this study provides (a) new evidence for promoting equitable access to primary healthcare services in Shenzhen and (b) a foundation for improving the accessibility of public service facilities in other areas.

摘要

医疗资源分配不均衡是阻碍获得医疗服务的一项重大挑战。以深圳为例,本研究旨在通过测量和可视化社区卫生服务中心(CHC)的空间可达性,并优化CHC的地理空间布局,来提高获得医疗服务的公平性。我们用每万名卫生技术人员数量来代表CHC的服务能力,结合居民点和人口普查数据计算CHC需要承载的人口,然后基于高斯两步移动搜寻法分析可达性。2020年,深圳五个区域的空间可达性得分较高:南山(0.250)、罗湖(0.246)、福田(0.244)、大鹏(0.226)和盐田(0.196)。CHC的空间可达性从市中心向边缘逐渐降低,这受到经济和地形因素的影响。在最大覆盖选址问题模型的支持下,我们为新建CHC选出了多达567个候选地点,这可以将深圳的可达性得分从0.189提高到0.361,并在15分钟阻抗范围内将覆盖人口增加63.46%。通过引入空间技术和地图,本研究为促进深圳公平获得基层医疗服务提供了新证据,并为提高其他地区公共服务设施的可达性奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2df/10187614/75676464f81b/GH2-7-e2022GH000753-g002.jpg

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