Evidence map›Paper›PMID 35058675›Full record

ArticleChina economic review2020

Impact of supplementary private health insurance on hospitalization and physical examination in China.

Yawen Jiang, Weiyi Ni

Open access · greenAbstract read
In one paragraph

Article in China economic review, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

16 citing papers in PubMed, 28 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

2 authors at 2 institutions in 2 countries.

Yawen JiangSchool of Public Health (Shenzhen), Sun Yat-sen University, Room 215, Mingde Garden #6, 132 East Outer Ring Road, Pan-yu District, Guangzhou, Guangdong, China.
Weiyi NiDepartment of Pharmaceutical and Health Economics, University of Southern California, USC Schaeffer Center, 635 Downey Way, Verna & Peter Dauterive Hall (VPD) Suite 210, Los Angeles, CA 90089-3333, USA.
Sun Yat-sen University · CNUniversity of Southern California · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Private health insurance (PHI) is considered an important supplement to the basic social health insurance schemes in the Chinese healthcare system. However, whether the strategy of engaging PHI as supplementary coverage is effective cannot be determined without knowing the impact of supplementary PHI on healthcare access and utilization, the evidence on which is currently absent in China. Therefore, we aimed to investigate the effects of supplementary PHI on hospitalization and physical examination to provide such evidence in the Chinese setting. We conducted a cross-sectional analysis using data from the 2015 wave of China Health and Retirement Longitudinal Study (CHARLS). Using probit models and bivariate probit models with instrumental variables (IVs), we evaluated the effects of supplementary PHI on the utilization of hospitalization and physical examination. Our analyses provided evidence that supplementary PHI increased the probability of physical examination but decreased that of hospitalization. Our findings suggest that supplementary PHI in China may effectively promote the use of high-value preventive care, thereby reducing subsequent utilization of expensive medical services. The present study provided preliminary evidence that the China healthcare system can benefit from engaging PHI as supplements to SHI.

Indexed as

ChinaHospitalizationPreventive carePrivate health insuranceSupplementary coverage

Identifiers

PMID35058675
PMCPMC7333596
OpenAlexW3039818059

What OpenQuestion holds

Textmetadata
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.