Evidence map›Paper›PMID 32245473›Full record

ArticleInternational journal for equity in health2020

Can the reform of integrating health insurance reduce inequity in catastrophic health expenditure? Evidence from China.

Jiahui Wang, Hong Zhu, Huan Liu, Ke Wu, Xin Zhang, Miaomiao Zhao, Hang Yin, Xinye Qi, Yanhua Hao, Ye Li and 6 more

Open access · goldAbstract read
In one paragraph

Article in International journal for equity in health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
10.9field-weighted citation impact, top 1% of its field
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

39 citing papers in PubMed, 2 syntheses or guidelines pooled it, 68 citations in OpenAlex.

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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

16 authors at 3 institutions in 1 country.

Jiahui WangDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Hong ZhuDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Huan LiuDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Ke WuTong Zhou District's Volunteer Services Guidance Center of Beijing Municipality, Beijing, China.
Xin ZhangDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Miaomiao ZhaoDepartment of Health Management, School of Public Health, Nantong University, Nantong, Jiangsu Province, China.
Hang YinDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Xinye QiDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Yanhua HaoDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Ye LiDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Libo LiangDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Mingli JiaoDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Jiao XuDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Baohua LiuDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China.
Qunhong WuDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China. wuqunhong@163.com.
Linghan ShanDepartment of Social Medicine, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang Province, China. linghanshan@126.com.
Harbin Medical University · CNBeijing Municipal Government · CNNantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChina's fragmentation of social health insurance schemes has become a key obstacle that hampers equal access to health care and financial protection. This study aims to explores if the policy intervention Urban and Rural Residents Basic Medical Insurance (URRBMI) scheme, which integrates Urban Resident Basic Medical Insurance (URBMI) and New Rural Cooperative Medical Scheme (NCMS), can curb the persistent inequity of catastrophic health expenditure (CHE) and further analyses the determinants causing inequity.

methodsData were derived from the Fifth National Health Service Survey (NHSS). A total of 11,104 households covered by URRBMI and 20,590 households covered by URBMI or NCMS were selected to analyze CHE and the impoverishment rate from medical expenses. Moreover, the decomposition method based on a probit model was employed to analyse factors contributing CHE inequity.

resultsThe overall incidence of CHE under integrated insurance scheme was 15.53%, about 1.10% higher than the non-integrated scheme; however, the intensity of CHE and impoverishment among the poorest was improved. Although CHE was still concentrated among the poor under URRBMI (CI = -0.53), it showed 28.38% lower in the degree of inequity. For URRBMI households, due to the promotion of integration reform to the utilization of rural residents' better health services, the factor of residence (24.41%) turns out to be a major factor in increasing inequity, the factor of households with hospitalized members (- 84.53%) played a positive role in reducing inequity and factors related to social economic status also contributed significantly in increasing inequity.

conclusionThe progress made in the integrated URRBMI on CHE equity deserves recognition, even though it did not reduce the overall CHE or the impoverishment rate effectively. Therefore, for enhanced equity, more targeted solutions should be considered, such as promoting more precise insurance intervention for the most vulnerable population and including costly diseases suitable for outpatient treatment into benefit packages. Additionally, comprehensive strategies such as favourable targeted benefit packages or job creation are required for the disadvantaged.

Indexed as

AdultAmbulatory CareChinaFamily CharacteristicsFemaleHealth ExpendituresHealth Services ResearchHumansInsurance, HealthMaleMiddle AgedRural PopulationSocioeconomic FactorsState MedicineUrban PopulationCatastrophic health expendituresHealth insuranceInequityIntegration

Identifiers

PMID32245473
PMCPMC7126184
OpenAlexW3014220216

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.