Evidence map›Paper›PMID 32606058›Full record

ArticleBMJ open2020

Interpretation of China's 2017 health expenditure: a latent profile analysis of panel data.

Shuang Zang, Meizhen Zhao, Jing OuYang, Xin Wang

Abstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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

4 authors.

Shuang ZangSchool of Nursing, China Medical University, Shenyang, China.
Meizhen ZhaoNursing Department, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jing OuYangHumanity and Management College, Shaanxi University of Chinese Medicine, Xianyang, China.
Xin WangCollege of Humanities and Social Sciences, China Medical University, Shenyang, China wxinsmile@qq.com.ORCID 0000-0001-7591-0103

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the latent structure of health financing and the institutional distribution of health expenditure (focused on hospital expenditure) in provinces, autonomous regions and municipalities of mainland China, and to examine how these profiles may be related to their externalising and internalising characteristics. STUDY

designThe study used panel data harvested from the China National Health Accounts Report 2018.

methodsMainland China's provincial data on health expenditure in 2017 was studied. A latent profile analysis was conducted to identify health financing and hospital health expenditure profiles in China. Additionally, rank-sum tests were used to understand the difference of socioeconomic indicators between subgroups.

resultsA best-fitting three-profile solution for per capita health financing was identified, with government health expenditure (χ

conclusionsPer capita health financing and health expenditure spent in hospitals have discrepant socioeconomic characteristics in different profiles, which may be attributed to macroeconomic factors and government policies. The study provided new and explicit ideas for health financing and health policy regulation in China.

Indexed as

ChinaCommunity Health ServicesEconomics, HospitalFinancing, GovernmentHealth ExpendituresHealth PolicyHumanshealth economicshealth policypublic health

Identifiers

PMID32606058
PMCPMC7328737

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