Evidence map›Paper›PMID 41291777›Full record

ArticleCost effectiveness and resource allocation : C/E2025

Key factors associated with China's basic medical insurance fund revenue-expenditure balance: a grey relational analysis.

Guangwen Gong, Wang Dan, Hu Wei, Li Xiping

Abstract read
In one paragraph

Article in Cost effectiveness and resource allocation : C/E, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

  1. Article
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Guangwen GongSchool of Management, Hubei University of Chinese Medicine, Wuhan, China.
Wang DanSchool of Management, Hubei University of Chinese Medicine, Wuhan, China.
Hu WeiSchool of Management, Hubei University of Chinese Medicine, Wuhan, China.
Li XipingSchool of Management, Hubei University of Chinese Medicine, Wuhan, China. 65089954@qq.com.

Funding

Hubei Provincial Natural Science Foundation 2024AFD232Hubei Provincial Natural Science Foundation 2025AFD600
6 · The paper itself

Abstract

introductionThe financial equilibrium of China’s Basic Medical Insurance Fund (BMIF) is pivotal, as it directly influences the sustainability, equity, and stability of the healthcare security system. Nevertheless, rapid population aging, increasing burdens chronic diseases, and rising hospitalization rates pose growing threats to this balance. Therefore, identifying key factors affecting the BMIF’s fiscal balance and developing targeted regulatory strategies are of considerable theoretical and practical significance.

methodsUsing national data from 2018 to 2023, Grey Relational Analysis (GRA) was employed to assess the correlation between BMIF revenue–expenditure balance and several indicators: insured population metrics, medical fund revenue patterns, healthcare utilization trends and associated costs, and reimbursement ratios.

resultsFor the Urban Employees’ Basic Medical Insurance (UEBMI) fund, revenue-expenditure balance was most strongly associated with hospitalization utilization (grey correlation degree = 0.940), reimbursement ratio (0.925), and cross-regional medical treatment (0.916). Fund income growth (0.805) and insured population growth (0.838) shown moderate correlations, while the growth of hospitalization costs (0.611) had the weaker association. In contrast, the revenue-expenditure balance of the Urban and Rural Residents’ Basic Medical Insurance (URRBMI) fund was most closely linked to reimbursement ratio(0.814), hospitalization utilization (0.804), and fund income growth rate (0.802). Cross-regional medical visits (0.777) and hospitalization costs (0.736) demonstrated moderate associations, while insured population growth (0.578) exhibited a negligible relationship.

conclusionThe financial equilibrium of UEBMI and URRBMI funds is associated with distinct primary factors: service utilization patterns and cost-sharing mechanisms exhibit the strongest associations for UEBMI, while URRBMI shows the highest grey relational degree with—though utilization and reimbursement rates remain importantly associated. To promote sustainable fiscal balance across both funds, coordinated policies that target these key associated factors are essential, such as those aimed at hospitalization demand, optimizing reimbursement structures, and managing cross-regional care. Additionally, implementing income-based subsidy schemes and contribution mechanisms could be a viable strategy for enhancing URRBMI’s financial resilience, as our analysis indicates a strong association between revenue fluctuations and its balance.

Indexed as

AssociationBasic medical insuranceChinaGrey relational analysisRevenue-expenditure balance

Identifiers

PMID41291777
PMCPMC12645762

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.