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

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 (C...

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Autores principales: Chen, Liutong, Zeng, Huatang, Wu, Liqun, Tian, Qiannan, Zhang, Ning, He, Rongxin, Xue, Hao, Zheng, Junyao, Liu, Jinlin, Liang, Fengchao, Zhu, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10187614/
https://www.ncbi.nlm.nih.gov/pubmed/37200630
http://dx.doi.org/10.1029/2022GH000753
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author Chen, Liutong
Zeng, Huatang
Wu, Liqun
Tian, Qiannan
Zhang, Ning
He, Rongxin
Xue, Hao
Zheng, Junyao
Liu, Jinlin
Liang, Fengchao
Zhu, Bin
author_facet Chen, Liutong
Zeng, Huatang
Wu, Liqun
Tian, Qiannan
Zhang, Ning
He, Rongxin
Xue, Hao
Zheng, Junyao
Liu, Jinlin
Liang, Fengchao
Zhu, Bin
author_sort Chen, Liutong
collection PubMed
description 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.
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spelling pubmed-101876142023-05-17 Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen Chen, Liutong Zeng, Huatang Wu, Liqun Tian, Qiannan Zhang, Ning He, Rongxin Xue, Hao Zheng, Junyao Liu, Jinlin Liang, Fengchao Zhu, Bin Geohealth Research Article 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. John Wiley and Sons Inc. 2023-05-16 /pmc/articles/PMC10187614/ /pubmed/37200630 http://dx.doi.org/10.1029/2022GH000753 Text en © 2023 The Authors. GeoHealth published by Wiley Periodicals LLC on behalf of American Geophysical Union. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Article
Chen, Liutong
Zeng, Huatang
Wu, Liqun
Tian, Qiannan
Zhang, Ning
He, Rongxin
Xue, Hao
Zheng, Junyao
Liu, Jinlin
Liang, Fengchao
Zhu, Bin
Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen
title Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen
title_full Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen
title_fullStr Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen
title_full_unstemmed Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen
title_short Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen
title_sort spatial accessibility evaluation and location optimization of primary healthcare in china: a case study of shenzhen
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10187614/
https://www.ncbi.nlm.nih.gov/pubmed/37200630
http://dx.doi.org/10.1029/2022GH000753
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