Evidence map›Paper›PMID 31665019›Full record

ArticleInternational journal for equity in health2019

Effects of health insurance integration on health care utilization and its equity among the mid-aged and elderly: evidence from China.

Chaofan Li, Chengxiang Tang, Haipeng Wang

Abstract read
In one paragraph

Article in International journal for equity in health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
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37citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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.

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3 · Its place in the literature

Who cites it

37 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Chaofan LiGraduate School at Shenzhen, Tsinghua University, Shenzhen, 518000, China.
Chengxiang TangSchool of Public Administration, Guangzhou University, Guangzhou, 510006, China.
Haipeng WangSchool of Health Care Management, Shandong University, Jinan, 250012, China. wanghaipeng@sdu.edu.cn.ORCID 0000-0002-1315-3474

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe fragmentation of health insurance schemes in China has undermined equity in access to health care. To achieve universal health coverage by 2020, the Chinese government has decided to consolidate three basic medical insurance schemes. This study aims to evaluate the effects of integrating Urban and Rural Residents Basic Medical Insurance schemes on health care utilization and its equity in China.

methodsThe data for the years before (2013) and after (2015) the integration were obtained from the China Health and Retirement Longitudinal Study. Respondents in pilot provinces were considered as the treatment group, and those in other provinces were the control group. Difference-in-difference method was used to examine integration effects on probability and frequency of health care visits. Subgroup analysis across regions of residence (urban/rural) and income groups and concentration index were used to examine effects on equity in utilization.

resultsThe integration had no significant effects on probability of outpatient visits (β = 0.01, P > 0.05), inpatient visits (β = 0.01, P > 0.05), and unmet hospitalization needs (β =0.01, P > 0.05), while it had significant and positive effects on number of outpatient visits (β = 0.62, P < 0.05) and inpatient visits (β = 0.39, P < 0.01). Moreover, the integration had significant and positive effects on number of outpatient visits (β = 0.77, P < 0.05) and inpatient visits (β = 0.49, P < 0.01) for rural residents but no significant effects for urban residents. Furthermore, the integration led to an increase in the frequency of inpatient care utilization for the poor (β = 0.78, P < 0.05) among the piloted provinces but had no significant effects for the rich (β = 0.25, P > 0.05). The concentration index for frequency of inpatient visits turned into negative direction in integration group, while that in control group increased by 0.011.

conclusionsThe findings suggest that the integration of fragmented health insurance schemes could promote access to and improve equity in health care utilization. Successful experiences of consolidating health insurance schemes in pilot provinces can provide valuable lessons for other provinces in China and other countries with similar fragmented schemes.

Indexed as

ChinaFemaleHealthcare DisparitiesHealth Services AccessibilityHumansInsurance, HealthLongitudinal StudiesMaleMiddle AgedPatient Acceptance of Health CareRural PopulationUrban PopulationEquityHealth care utilizationHealth insurance integrationPolicy evaluation

Identifiers

PMID31665019
PMCPMC6820904

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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.