Evidence map›Paper›PMID 42260506›Full record

ArticleBMC health services research2026

Payment mechanism and medical quality: new evidence from China healthcare reform.

Yaxuan Zuo, Yingtan Mu, Jiali Zhang, Qiuming Hu

Abstract read
In one paragraph

Article in BMC health services research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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.

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yaxuan ZuoThe School of Public Administration, Southwestern University of Finance and Economics, 555, Liutai Avenue, Wenjiang District, Chengdu, Sichuan, P. R. China.
Yingtan MuThe School of Public Administration, Southwestern University of Finance and Economics, 555, Liutai Avenue, Wenjiang District, Chengdu, Sichuan, P. R. China. muyingtan@126.com.
Jiali ZhangThe School of Public Administration, Southwestern University of Finance and Economics, 555, Liutai Avenue, Wenjiang District, Chengdu, Sichuan, P. R. China.
Qiuming HuThe School of Public Administration, Southwestern University of Finance and Economics, 555, Liutai Avenue, Wenjiang District, Chengdu, Sichuan, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReform of payment methods promote to achieve the public value of health insurance through incentive-compatible mechanisms. Payment differentials, defined as the difference between DRG/DIP payment amounts and total medical expenses, together with the rational design of surplus retention mechanisms, are crucial for controlling healthcare costs, improving service quality, ensuring the sustainability of health insurance funds, and guiding medical institutions towards reasonable surplus targets.

methodsThis study constructs a one-shot game model under conditions of information asymmetry among hospitals, patients, and health insurance agencies. Using sample data from health insurance settlements in DRG pilot cities for the years 2021-2022, with readmission rates as the quality indicator and payment differentials as the measurement index, the study explores the association of payment differentials on the service quality of medical institutions.

resultsNegative payment differentials are significantly associated with higher readmission rates and lower measured service quality. This may be consistent with insufficient payment incentives under the DRG system, which prompts medical institutions to adopt more aggressive cost-control measures, such as reducing hospital stays and limiting expenditures on medical services, which in turn may be associated with lower service quality. Moreover, the relationship between payment differentials and service quality varies depending on factors such as the type of surgery, hospital tier, and patient age.

conclusionsThere should be a more effective alignment between medical service pricing and health insurance payment standards, may help guide medical institutions toward more sustainable financial performance through the optimization of treatment processes, and promoting the shift towards a value-based payment system, potentially contributing to improved incentive alignment. Noting that as an observational study, our findings reflect correlations rather than causal effects.

Indexed as

Health Care ReformQuality of Health CareReimbursement MechanismsChinaDiagnosis-Related GroupsHumansPatient ReadmissionReimbursement, IncentiveDRG payment differentialHealthcare service qualityIncentive compatibility

Identifiers

PMID42260506
PMCPMC13474885

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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.