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诊断-干预包(DIP)改革对中国中部低收入人群住院服务的影响:一项多阶段中断时间序列分析

Impact of Diagnosis-Intervention Packet (DIP) reforms on inpatient services for low-income populations in central China: A multi-stage interrupted time-series analysis.

作者信息

Shen Keyi, Tao Yingying, Li Yile, Jin Ziqian, Li Chengcheng, Wu Dan, Meng Xuehui

机构信息

School of Humanities and Management, Zhejiang Chinese Medical University, Hangzhou, China.

出版信息

PLoS One. 2025 May 22;20(5):e0323194. doi: 10.1371/journal.pone.0323194. eCollection 2025.

Abstract

As global healthcare costs continue to rise, concerns about health equity have become increasingly prominent. In response, China introduced the Diagnosis-Intervention Packet (DIP) reform in 2021 to optimize healthcare resource allocation and control costs. While the reform has been widely discussed in terms of its overall cost-control effects, its heterogeneous impact on low-income populations, especially across different hospital tiers, remains unclear. This study aims to fill this gap by examining the differentiated impact of the DIP reform on low-income patients' inpatient service utilization. Using multi-stage interrupted time series (ITS) analysis, we analyzed 1.17 million hospitalization records from low-income patients in City S, a pilot city in central China. The study reveals that DIP significantly reduced total hospitalization costs and length of stay (LOS) but led to increased readmission rates, indicating a trade-off between efficiency gains and potential risks to care quality. The reform's effects varied by hospital tier: primary hospitals saw increased demand for non-acute hospitalization due to reduced out-of-pocket (OOP) payments, exposing resource shortages; secondary hospitals balanced cost control and revenue by shortening stays and increasing admission frequency, which raised readmission risks; and tertiary hospitals, treating critically ill patients, enhanced treatment completeness, though multiple hospitalizations were still needed for full recovery. The study introduces a two-dimensional framework- "hospital tier-policy cycle"-demonstrating that differences in service capacity across hospital levels are central to the heterogeneous effects of the DIP reform. These findings suggest that future policies should strengthen primary care resources, introduce quality assurance mechanisms, and consider bundled payment models for critical care. This research contributes valuable insights for optimizing equity in DIP reform and offers implications for similar healthcare payment systems globally.

摘要

随着全球医疗成本持续上升,对健康公平性的担忧日益凸显。作为回应,中国于2021年推出了疾病诊断相关分组(DIP)改革,以优化医疗资源配置并控制成本。尽管该改革在总体成本控制效果方面已得到广泛讨论,但其对低收入人群的异质性影响,尤其是在不同医院层级间的影响仍不明确。本研究旨在通过考察DIP改革对低收入患者住院服务利用的差异化影响来填补这一空白。我们采用多阶段中断时间序列(ITS)分析方法,分析了中国中部试点城市S市117万低收入患者的住院记录。研究表明,DIP显著降低了总住院成本和住院时长(LOS),但导致再入院率上升,这表明在效率提升与护理质量潜在风险之间存在权衡。改革的效果因医院层级而异:基层医院因自付费用(OOP)减少,非急性住院需求增加,暴露出资源短缺问题;二级医院通过缩短住院时长和增加入院频率来平衡成本控制和收入,这增加了再入院风险;三级医院治疗重症患者,提高了治疗完整性,不过患者仍需多次住院才能完全康复。该研究引入了一个二维框架——“医院层级-政策周期”,表明不同医院层级的服务能力差异是DIP改革异质性影响的核心。这些发现表明,未来政策应加强基层医疗资源,引入质量保证机制,并考虑对重症护理采用捆绑支付模式。本研究为优化DIP改革中的公平性提供了有价值的见解,并对全球类似的医疗支付系统具有启示意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c4c/12143900/e90d80cb7d98/pone.0323194.g001.jpg

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