Evidence map›Paper›PMID 36215249›Full record

ArticlePloS one2022

Trends in the disparities and equity of the distribution of traditional Chinese medicine health resources in China from 2010 to 2020.

Rixiang Xu, Tingyu Mu, Yulian Liu, Yaping Ye, Caiming Xu

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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  11. Spatial accessibility and equity of primary healthcare in Zhejiang, China.International journal for equity in health · 2024
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Rixiang XuSchool of Humanities and Management, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China.ORCID 0000-0002-3869-5691
Tingyu MuSchool of Nursing, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China.
Yulian LiuSchool of Humanities and Management, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China.
Yaping YeSchool of Humanities and Management, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China.
Caiming XuSchool of Law, Zhejiang University City College, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAt present, improving the accessibility to traditional Chinese medicine (TCM) health resources is an important component of China's health policy. This study evaluated the trends in the disparities and equity of TCM health resource allocation from 2010 to 2020 to inform optimal future local health planning and policy.

methodThe data for this study were extracted from the China Health Statistical Yearbook (2011-2021) and China Urban Statistical Yearbook (2020). The equity and rationality of the allocation of TCM health resources at the national and provincial levels were evaluated using the Gini coefficient and the health resource aggregation degree, respectively.

resultThe number of TCM-related institutions, beds, health staff, outpatients and admissions increased by 1.97, 2.61, 2.35, 1.72 and 2.41 times, respectively, between 2010 and 2020. The population-based Gini coefficients for health staff, beds and institutions were 0.12, 0.23 and 0.13, respectively, indicating acceptable equity, while the geographical area-based Gini index for health staff, beds and institutions were 0.65, 0.62 and 0.62, respectively, indicating serious inequity. The agglomeration degree as a function of geographical area was as follows: eastern region > central region > western region. Moreover, the institutional and health staff gaps between the geographical areas increased from 2012 to 2020. In addition, there was a relatively balanced agglomeration degree based on the population in these three regions and an increasingly equitable allocation of institutions and health staff.

conclusionIn recent years, China's TCM health resources and services have increased rapidly, but their proportions within the overall health system remain low. The equity and rationality of TCM health allocated by the population was better than that by the geographic area. Regional differences and inequalities, especially for institutions, still exist. A series of policies to promote the balanced development of TCM need to be implemented.

Indexed as

Health EquityHealth ResourcesChinaHealth PolicyHumansMedicine, Chinese TraditionalResource Allocation

Identifiers

PMID36215249
PMCPMC9550081

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.