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Regional disparities and influencing factors of high quality medical resources distribution in China

BACKGROUND: With the gradual increase of residents’ income and the continuous improvement of medical security system, people’s demand for pursuing higher quality and better medical and health services has been released. However, so far little research has been published on China's high quality...

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Autores principales: Yuan, Lei, Cao, Jing, Wang, Dong, Yu, Dan, Liu, Ge, Qian, Zhaoxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832614/
https://www.ncbi.nlm.nih.gov/pubmed/36627636
http://dx.doi.org/10.1186/s12939-023-01825-6
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author Yuan, Lei
Cao, Jing
Wang, Dong
Yu, Dan
Liu, Ge
Qian, Zhaoxin
author_facet Yuan, Lei
Cao, Jing
Wang, Dong
Yu, Dan
Liu, Ge
Qian, Zhaoxin
author_sort Yuan, Lei
collection PubMed
description BACKGROUND: With the gradual increase of residents’ income and the continuous improvement of medical security system, people’s demand for pursuing higher quality and better medical and health services has been released. However, so far little research has been published on China's high quality medical resources (HQMR). This study aims to understand the spatiotemporal variation trend of HQMR from 2006 to 2020, analyze regional disparity of HQMR in 2020, and further explore the main factors influencing the distribution of HQMR in China. METHODS: The study selected Class III level A hospitals (the highest level medical institutions in China) to represent HQMR. Descriptive statistical methods were used to address the changes in the distribution of HQMR from 2006 to 2020. Lorentz curve, Gini coefficient (G), Theil index (T) and High-quality health resource density index (HHRDI) were used to calculate the degree of inequity. The geographical detector method was used to reveal the key factors influencing the distribution of HQMR. RESULTS: The total amount of HQMR in China had increased year by year, from 647 Class III level A hospitals in 2006 to 1580 in 2020. In 2020, G for HQMR by population was 0.166, while by geographic area was 0.614. T was consistent with the results for G, and intra-regional contribution rates were higher than inter-regional contribution rates. HHRDI showed that Beijing, Shanghai, and Tianjin had the highest allocated amounts of HQMR. The results of the geographical detector showed that total health costs, government health expenditure, size of resident populations, GDP, number of medical colleges had a significant impact on the spatial distribution of HQMR and the q values were 0.813, 0.781, 0.719, 0.661, 0.492 respectively. There was an interaction between the influencing factors. CONCLUSIONS: China's total HQMR is growing rapidly but is relatively inadequate. The distribution of HQMR by population is better than by geography, and the distribution by geography is less equitable. Population size and geographical area both need to be taken into account when formulating policies, rather than simply increasing the number of HQMR.
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spelling pubmed-98326142023-01-12 Regional disparities and influencing factors of high quality medical resources distribution in China Yuan, Lei Cao, Jing Wang, Dong Yu, Dan Liu, Ge Qian, Zhaoxin Int J Equity Health Research BACKGROUND: With the gradual increase of residents’ income and the continuous improvement of medical security system, people’s demand for pursuing higher quality and better medical and health services has been released. However, so far little research has been published on China's high quality medical resources (HQMR). This study aims to understand the spatiotemporal variation trend of HQMR from 2006 to 2020, analyze regional disparity of HQMR in 2020, and further explore the main factors influencing the distribution of HQMR in China. METHODS: The study selected Class III level A hospitals (the highest level medical institutions in China) to represent HQMR. Descriptive statistical methods were used to address the changes in the distribution of HQMR from 2006 to 2020. Lorentz curve, Gini coefficient (G), Theil index (T) and High-quality health resource density index (HHRDI) were used to calculate the degree of inequity. The geographical detector method was used to reveal the key factors influencing the distribution of HQMR. RESULTS: The total amount of HQMR in China had increased year by year, from 647 Class III level A hospitals in 2006 to 1580 in 2020. In 2020, G for HQMR by population was 0.166, while by geographic area was 0.614. T was consistent with the results for G, and intra-regional contribution rates were higher than inter-regional contribution rates. HHRDI showed that Beijing, Shanghai, and Tianjin had the highest allocated amounts of HQMR. The results of the geographical detector showed that total health costs, government health expenditure, size of resident populations, GDP, number of medical colleges had a significant impact on the spatial distribution of HQMR and the q values were 0.813, 0.781, 0.719, 0.661, 0.492 respectively. There was an interaction between the influencing factors. CONCLUSIONS: China's total HQMR is growing rapidly but is relatively inadequate. The distribution of HQMR by population is better than by geography, and the distribution by geography is less equitable. Population size and geographical area both need to be taken into account when formulating policies, rather than simply increasing the number of HQMR. BioMed Central 2023-01-10 /pmc/articles/PMC9832614/ /pubmed/36627636 http://dx.doi.org/10.1186/s12939-023-01825-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yuan, Lei
Cao, Jing
Wang, Dong
Yu, Dan
Liu, Ge
Qian, Zhaoxin
Regional disparities and influencing factors of high quality medical resources distribution in China
title Regional disparities and influencing factors of high quality medical resources distribution in China
title_full Regional disparities and influencing factors of high quality medical resources distribution in China
title_fullStr Regional disparities and influencing factors of high quality medical resources distribution in China
title_full_unstemmed Regional disparities and influencing factors of high quality medical resources distribution in China
title_short Regional disparities and influencing factors of high quality medical resources distribution in China
title_sort regional disparities and influencing factors of high quality medical resources distribution in china
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832614/
https://www.ncbi.nlm.nih.gov/pubmed/36627636
http://dx.doi.org/10.1186/s12939-023-01825-6
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