• Assessing regional disparities...

Treffer: Assessing regional disparities and trends in health resource allocation from sub-provincial cities in China.

Title:
Assessing regional disparities and trends in health resource allocation from sub-provincial cities in China.
Authors:
Zhou M; Department of Administration Office, Luzhou People's Hospital, Luzhou, Sichuan, China.
Source:
Annals of medicine [Ann Med] 2025 Dec; Vol. 57 (1), pp. 2522962. Date of Electronic Publication: 2025 Jun 26.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Informa Healthcare Country of Publication: England NLM ID: 8906388 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1365-2060 (Electronic) Linking ISSN: 07853890 NLM ISO Abbreviation: Ann Med Subsets: MEDLINE
Imprint Name(s):
Publication: London : Informa Healthcare
Original Publication: Helsinki : Finnish Medical Society Duodecim, 1989-
MeSH Terms:
Health Expenditures*/trends , Health Expenditures*/statistics & numerical data , Resource Allocation*/trends , Healthcare Disparities*/trends , Healthcare Disparities*/economics , Health Care Rationing*/trends, Humans ; China ; Cities
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Contributed Indexing:
Keywords: China; dynamic evolution; health resource allocation; regional differences; sub-provincial cities
Entry Date(s):
Date Created: 20250627 Date Completed: 20250627 Latest Revision: 20250629
Update Code:
20250630
PubMed Central ID:
PMC12203693
DOI:
10.1080/07853890.2025.2522962
PMID:
40574271
Database:
MEDLINE

Weitere Informationen

Background: To analyze the regional disparities and trends in health resource allocation in sub-provincial cities, to inform strategies for achieving equitable health resource allocation across sub-provincial cities.
Methods: Dagum Gini coefficient and kernel density estimation based on the health resource density index were used to analyze the regional disparities and trends in health resource allocation in sub-provincial cities from 2018 to 2022.
Results: The overall Gini coefficient of health expenditure is the highest, above 0.373. The differences in health expenditure are larger in the eastern region, and smaller in the central and western regions in terms of medical and health institutions, number of beds, health technicians, licensed (assistant) physicians and registered nurses. The inter-regional contribution rate is the main source of differences, with the lowest value of the inter-regional contribution rate being 45.08% of health expenditure in 2020 and the highest value being 67.60% of licensed (assistant) physicians in 2020. The longer and longer right trailing tail of the health expenditure kernel density curve indicates a significant difference in health expenditure. The kernel density curves of health expenditure and medical and health institutions have a multi-peaked distribution, indicating a low degree of equalization, while the rest of the distribution of health resources is relatively more balanced.
Conclusion: Health resources in sub-provincial cities have continued to grow. Sub-provincial cities have a more balanced distribution of health resources, but there are significant differences in health expenditure. Inter-regional differences are the main cause of differences in health resource allocation in sub-provincial cities.