Evidence map›Paper›PMID 36627636›Full record

ArticleInternational journal for equity in health2023

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

Lei Yuan, Jing Cao, Dong Wang, Dan Yu, Ge Liu, Zhaoxin Qian

Abstract read
In one paragraph

Article in International journal for equity in health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lei YuanXiangya Hospital, Central South University, Changsha, Hunan, China.
Jing CaoDepartment of Cardiovascular Medicine, Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
Dong WangXiangya Hospital, Central South University, Changsha, Hunan, China.
Dan YuXiangya Hospital, Central South University, Changsha, Hunan, China.
Ge LiuXiangya Hospital, Central South University, Changsha, Hunan, China.
Zhaoxin QianXiangya Hospital, Central South University, Changsha, Hunan, China. xyqzx@csu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith 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.

methodsThe 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.

resultsThe 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.

conclusionsChina'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.

Indexed as

Health ResourcesHealth ServicesChinaHospitalsHumansIncomeGeographical detectorHigh quality medical resourcesInequityRegional disparities

Identifiers

PMID36627636
PMCPMC9832614

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.