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Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China

OBJECTIVE: The study aimed to measure time trends of inequalities of the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used a spatial autocorrelation analysis method to precisely detect the priority areas for optimizing health resource reallocation in...

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Autores principales: Dong, Enhong, Sun, Xiaoting, Xu, Ting, Zhang, Shixiang, Wang, Tao, Zhang, Lufa, Gao, Weimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10060654/
https://www.ncbi.nlm.nih.gov/pubmed/37006575
http://dx.doi.org/10.3389/fpubh.2023.1074417
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author Dong, Enhong
Sun, Xiaoting
Xu, Ting
Zhang, Shixiang
Wang, Tao
Zhang, Lufa
Gao, Weimin
author_facet Dong, Enhong
Sun, Xiaoting
Xu, Ting
Zhang, Shixiang
Wang, Tao
Zhang, Lufa
Gao, Weimin
author_sort Dong, Enhong
collection PubMed
description OBJECTIVE: The study aimed to measure time trends of inequalities of the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used a spatial autocorrelation analysis method to precisely detect the priority areas for optimizing health resource reallocation in metropolises like Shanghai in developing countries. METHODS: The study used secondary data from the Shanghai Health Statistical Yearbook and the Shanghai Statistical Yearbook from 2011 to 2017. Five indicators on health resources, namely, health institutions, beds, technicians, doctors, and nurses, were employed to quantitatively measure the healthcare resource in Shanghai. The Theil index and the Gini coefficient were applied to assess the global inequalities in the geographic distribution of these resources in Shanghai. Global and local spatial autocorrelation was performed using global Moran's index and local Moran's index to illustrate the spatial changing patterns and identify the priority areas for two types of healthcare resource allocation. RESULTS: Shanghai's healthcare resources showed decreasing trends of inequalities at large from 2010 to 2016. However, there still existed an unchanged over-concentration distribution in healthcare facilities and workforce density among districts in Shanghai, especially for doctors at the municipal level and facility allocation at the rural level. Through spatial autocorrelation analysis, it was found that there exhibited a significant spatial autocorrelation in the density distribution of all resources, and some identified priority areas were detected for resource re-allocation policy planning. CONCLUSION: The study identified the existence of inequality in some healthcare resource allocations in Shanghai from 2010 to 2016. Hence, more detailed area-specific healthcare resource planning and distribution policies are required to balance the health workforce distribution at the municipal level and institution distribution at the rural level, and particular geographical areas (low–low and low–high cluster areas) should be focused on and fully considered across all the policies and regional cooperation to ensure health equality for municipal cities like Shanghai in developing countries.
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spelling pubmed-100606542023-03-31 Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China Dong, Enhong Sun, Xiaoting Xu, Ting Zhang, Shixiang Wang, Tao Zhang, Lufa Gao, Weimin Front Public Health Public Health OBJECTIVE: The study aimed to measure time trends of inequalities of the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used a spatial autocorrelation analysis method to precisely detect the priority areas for optimizing health resource reallocation in metropolises like Shanghai in developing countries. METHODS: The study used secondary data from the Shanghai Health Statistical Yearbook and the Shanghai Statistical Yearbook from 2011 to 2017. Five indicators on health resources, namely, health institutions, beds, technicians, doctors, and nurses, were employed to quantitatively measure the healthcare resource in Shanghai. The Theil index and the Gini coefficient were applied to assess the global inequalities in the geographic distribution of these resources in Shanghai. Global and local spatial autocorrelation was performed using global Moran's index and local Moran's index to illustrate the spatial changing patterns and identify the priority areas for two types of healthcare resource allocation. RESULTS: Shanghai's healthcare resources showed decreasing trends of inequalities at large from 2010 to 2016. However, there still existed an unchanged over-concentration distribution in healthcare facilities and workforce density among districts in Shanghai, especially for doctors at the municipal level and facility allocation at the rural level. Through spatial autocorrelation analysis, it was found that there exhibited a significant spatial autocorrelation in the density distribution of all resources, and some identified priority areas were detected for resource re-allocation policy planning. CONCLUSION: The study identified the existence of inequality in some healthcare resource allocations in Shanghai from 2010 to 2016. Hence, more detailed area-specific healthcare resource planning and distribution policies are required to balance the health workforce distribution at the municipal level and institution distribution at the rural level, and particular geographical areas (low–low and low–high cluster areas) should be focused on and fully considered across all the policies and regional cooperation to ensure health equality for municipal cities like Shanghai in developing countries. Frontiers Media S.A. 2023-03-16 /pmc/articles/PMC10060654/ /pubmed/37006575 http://dx.doi.org/10.3389/fpubh.2023.1074417 Text en Copyright © 2023 Dong, Sun, Xu, Zhang, Wang, Zhang and Gao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Dong, Enhong
Sun, Xiaoting
Xu, Ting
Zhang, Shixiang
Wang, Tao
Zhang, Lufa
Gao, Weimin
Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China
title Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China
title_full Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China
title_fullStr Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China
title_full_unstemmed Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China
title_short Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China
title_sort measuring the inequalities in healthcare resource in facility and workforce: a longitudinal study in china
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10060654/
https://www.ncbi.nlm.nih.gov/pubmed/37006575
http://dx.doi.org/10.3389/fpubh.2023.1074417
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