Evidence map›Paper›PMID 38904006›Full record

ArticleRisk management and healthcare policy2024

Effects of a Diagnosis-Related Group Payment Reform on Length and Costs of Hospitalization in Sichuan, China: A Synthetic Control Study.

Yaqing Liu, Sixian Du, Jianbo Cao, Haoran Niu, Feng Jiang, Liwen Gong

Abstract read
In one paragraph

Article in Risk management and healthcare policy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

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3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Yaqing LiuSchool of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Sixian DuSchool of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.ORCID 0009-0009-9804-4645
Jianbo CaoSchool of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Haoran NiuSchool of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Feng JiangSchool of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Liwen GongSchool of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diagnosis-related group (DRG) payment policies are increasingly recognized as crucial instruments for addressing health care overprovision and escalating health care costs. The synthetic control method (SCM) has emerged as a robust tool for evaluating the efficacy of health policies worldwide. Methods: This study focused on Panzhihua city in Sichuan Province, a pilot city for DRG payment reform implementation, serving as the treatment group. In contrast, 20 nonpilot cities within the province were utilized as potential control units. A counterfactual control group was constructed to evaluate the changes in average inpatient stay duration and health care organization costs following the DRG payment reform initiated in 2018. Results: Focusing on Panzhihua, Sichuan Province, the analysis reveals that following the reform in March 2018, the average length of hospital stay in Panzhihua decreased by 1.35 days during 2019-2021. Additionally, the average cost per hospitalization dropped by 855.48 RMB, the average cost of medication per hospitalization decreased by 68.51 RMB, and the average cost of diagnostic and therapeutic procedures per hospitalization declined by 136.37 RMB. While global evidence backs DRGs for efficiency and cost reduction, challenges persist in addressing emerging issues like new conditions. Conclusion: Since its introduction in 2018, the DRG payment reform in Sichuan Province has effectively reduced both the duration of hospital stays and the operational costs of health care facilities. However, potential drawbacks include compromised service quality and an elevated risk of patient readmission, indicating a need for further refinement in the implementation of DRG payment reforms in China.

Indexed as

average hospital costsaverage hospitalization daysChinadiagnosis-related groupingDRGhealth policy evaluationsynthetic control method

Identifiers

PMID38904006
PMCPMC11189311

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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.