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人力资源与医院床位分配的公平性分析及其与新冠肺炎死亡率的关联:以伊朗为例

Analysis of equity in the distribution of human resources and hospital beds and its association with the COVID-19 mortality rate: a case of Iran.

作者信息

Jalilian Habib, Riahi Seyed Mohammad, Heydari Somayeh, Taji Masoomeh

机构信息

Department of Health Services Management, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Department of Family and Community Medicine, School of Medicine, Cardiovascular Diseases Research Center, Birjand University of Medical Sciences, Ghaffari Street, Birjand, 9717853076, Iran.

出版信息

BMC Health Serv Res. 2025 Jan 20;25(1):110. doi: 10.1186/s12913-025-12277-9.

DOI:10.1186/s12913-025-12277-9
PMID:39833844
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11748536/
Abstract

BACKGROUND AND OBJECTIVE

Equitable distribution of health resources is important to achieving equity, guaranteeing access to healthcare services, and improving societies' health status. This study aimed to examine equity in the distribution of health resources and its association with the mortality caused by COVID-19 in South Khorasan province, east Iran.

METHOD

This was a secondary analysis of data from a cross-sectional study conducted in South Khorasan province in 2022. Data were drawn from an existing online database (Farabar) provided by the Public Health Department of the Ministry of Health in Iran. Data related to the number of hospital beds, medical specialists and practitioners, nurses, paramedical workers, health watch, community health workers (Behvarz), healthcare financial resources, and COVID-19 mortality rate were extracted from the Farabar system for each city separately. The equity in the distribution of resources was analyzed by calculating the Gini Coefficient index and using EXCEL software. The Gini Coefficient was used to measure the distribution of health resources and services (i.e. financial resources, human resources, hospital beds, ICU beds) against population size and geographic size. Data were analyzed using SPSS software, version 25.

RESULTS

The Gini Coefficient ranged between 0.006 and 0.320. The Gini Coefficient of health care system financial (0.006) resources distribution was more equitable, while that of hospital beds (0.229) and intensive care beds (0.320) was more inequitable. The Gini Coefficient of the distribution of human resources was estimated at less than 0.3, which is relatively equitable. The COVID-19 mortality rate per 100,000 population was estimated at 113.6, lower than the national average. After controlling the confounding variable (rural population (as % of the total population)), there was no significant correlation between COVID-19 mortality and the distribution of human resources, hospital beds, and healthcare financial resources.

CONCLUSION

According to the results, the distribution of resources relative to the province's population was relatively equitable, and there was no significant correlation between the COVID-19 mortality rate and the distribution of human resources, hospital beds, and healthcare financial resources. This can be due to the equitable distribution of health resources. Having a better and deeper understanding of the regions and populations disproportionately impacted by COVID-19 can help with intervention and resource allocation.

摘要

背景与目的

卫生资源的公平分配对于实现公平、保障医疗服务可及性以及改善社会健康状况至关重要。本研究旨在考察伊朗东部霍拉桑省南部卫生资源分配的公平性及其与新冠病毒病(COVID-19)所致死亡率的关联。

方法

这是对2022年在霍拉桑省南部开展的一项横断面研究数据的二次分析。数据取自伊朗卫生部公共卫生司提供的现有在线数据库(Farabar)。分别从Farabar系统中提取每个城市与医院床位数量、医学专家及从业者、护士、辅助医务人员、健康监测员、社区卫生工作者(Behvarz)、医疗财政资源以及COVID-19死亡率相关的数据。通过计算基尼系数指数并使用EXCEL软件分析资源分配的公平性。基尼系数用于衡量卫生资源与服务(即财政资源、人力资源、医院床位、重症监护床位)相对于人口规模和地理面积的分配情况。使用SPSS 25.0软件进行数据分析。

结果

基尼系数在0.006至0.320之间。医疗系统财政资源分配的基尼系数(0.006)更为公平,而医院床位(0.229)和重症监护床位(0.320)的基尼系数则更不公平。人力资源分配的基尼系数估计小于0.3,相对公平。每10万人口的COVID-19死亡率估计为113.6,低于全国平均水平。在控制混杂变量(农村人口(占总人口的百分比))后,COVID-19死亡率与人力资源、医院床位和医疗财政资源的分配之间无显著相关性。

结论

根据研究结果,相对于该省人口而言,资源分配较为公平,且COVID-19死亡率与人力资源、医院床位和医疗财政资源的分配之间无显著相关性。这可能归因于卫生资源的公平分配。更好、更深入地了解受COVID-19影响较大的地区和人群有助于进行干预和资源分配。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8282/11748536/d312f4a2120f/12913_2025_12277_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8282/11748536/16477f889f0f/12913_2025_12277_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8282/11748536/7ca95aada577/12913_2025_12277_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8282/11748536/6cbe691e7a6e/12913_2025_12277_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8282/11748536/d312f4a2120f/12913_2025_12277_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8282/11748536/16477f889f0f/12913_2025_12277_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8282/11748536/7ca95aada577/12913_2025_12277_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8282/11748536/6cbe691e7a6e/12913_2025_12277_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8282/11748536/d312f4a2120f/12913_2025_12277_Fig4_HTML.jpg

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