Evidence map›Paper›PMID 40189513›Full record

ArticleBMC medicine2025

Assessing healthcare payment reforms' effects on economic inequities and catastrophic expenditures among cancer patients in ethnic minority regions of China.

Xin Xiang, Yu Li, Ning Liang, Bangqin Wang, Hongzhi Wang

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Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xin Xiang *Institute of Fiscal and Finance, Shandong Academy of Social Sciences, Jinan, China.
Yu Li *Medical Insurance Department, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Ning LiangMedical Insurance Department, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Bangqin WangMedical Insurance Department, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China. wangbangqin@hotmail.com.
Hongzhi WangResearch Center of Hospital Management and Medical Prevention, Guangxi Academy of Medical Sciences, The People's Hospital of Guangxi Zhuang Autonomous Region, 6 Taoyuan Road, Nanning, Guangxi, 530021, China. m13557710133@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEthnic minority groups are particularly vulnerable to healthcare inequities, with catastrophic medical expenditures often pushing them into poverty. However, empirical research on the impact of healthcare reforms on these populations remains limited. This study aims to address this gap by exploring the effects of healthcare payment reforms on healthcare outcomes and financial protection during serious illnesses among ethnic minority populations.

methodsA cross-sectional study was conducted using data from three major ethnic minority groups in China: the Zhuang, Hui, and Manchu. The analysis is based on hospitalization data from 59,622 ethnic minority cancer patients spanning from 2013 to 2024. Ordinary least squares (OLS) linear regression was employed to assess the effects of healthcare payment reforms on healthcare expenses and cost-sharing.

resultsThe findings indicate that, compared to traditional payment methods, the implementation of diagnosis-related group (DRG) payment reforms led to reductions in hospitalization, drug, and treatment expenses for ethnic minority patients. However, a closer examination of the cost structure reveals that while DRG payment systems have reduced expenditures for public health insurance fund, they have simultaneously increased out-of-pocket costs for minority patients.

conclusionsGiven that many ethnic minority patients belong to economically disadvantaged groups with limited financial resources, the rise in out-of-pocket costs exacerbates their economic burden, making them more vulnerable to catastrophic medical expenditures. This situation poses a severe challenge to minority patients already in precarious financial circumstances. This study offers insights and lessons from China that may guide governments worldwide in mitigating healthcare inequities faced by vulnerable populations.

Indexed as

EthnicityHealthcare DisparitiesHealth Care ReformHealth ExpendituresMinority GroupsNeoplasmsAdultAgedChinaCross-Sectional StudiesEast Asian PeopleFemaleHospitalizationHumansMaleMiddle AgedCatastrophic health expendituresEthnic minoritiesHealth inequitiesHealth reform

Identifiers

PMID40189513
PMCPMC11974073

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LicenceCC BY-NC-ND
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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.