ArticleRisk management and healthcare policy2025
Cost Shifting in Lung Cancer Inpatient Care Under Diagnosis-Intervention Packet Reform: A Pilot Study in China.
Article in Risk management and healthcare policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- High-magnification inpatient cases under DIP payment reform: prevalence, cost burden, and risk factors in an NHC-administered hospital in China.Frontiers in public health · 2026Observational
- Impact of Diagnosis-Intervention Packet Compliance Training on Inpatient Expenditures Under Case-Based Payment Reform: A Quasi-Experimental Study Based on Discharge Records.Journal of multidisciplinary healthcare · 2026Article
- The impact of DIP payment reform on hospitalization costs and equity in type 2 diabetes mellitus patients: evidence from a pilot city in Central China.Frontiers in public health · 2026Article
- The impacts of diagnosis-intervention packet payment on inpatient medical costs for hematologic malignancies and solid tumors: evidence from a retrospective study in China.Frontiers in public health · 2025Article
- Inpatient burden of lung cancer and changes after a hospital performance reform: a real-world study.Frontiers in oncology · 2025Article
- Analysis on the hospitalization expenses structure and correlation degree of lung cancer: evidence from Shanxi Province, China.Frontiers in public health · 2025Article
- Interrupted time series analysis of the impact of DIP reform on hospitalization costs in different types of hospitals.Frontiers in public health · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: China has developed and widely implemented an innovative case-based payment method for inpatient services under a regional global budget, termed the "Diagnosis-Intervention Packet" (DIP). This study aims to examine cost-shifting behaviour in lung cancer inpatient care under the DIP reform. Methods: This study examines the impact of the DIP reform in Zunyi, a national pilot city, using double machine learning (DML). Specifically, we analyze the effects on the total health expenditures (THS), individual payments excluding reimbursement (IPER), proportion of IPER, copayments for category-B, proportion of copayments for category-B, copayments for category-C and proportion of copayments for category-C per case for LC inpatients in tertiary hospitals. Results: The results indicate a significant reduction in THS per case after the DIP reform (β = -0.0778, p < 0.001). Following the reform, there was a significant increase in IPER (β = 0.0689, p < 0.05), copayments for category-B (β = 0.1682, p < 0.01), and the proportion of copayments for category-B (β = 0.0039, p < 0.05). Conversely, the proportion of copayments for category-C significantly decreased (β = -0.0108, p < 0.001). Notably, significant heterogeneity in the cost-containment and cost-shifting effects was observed across different hospital categories, teaching types, and insured classifications. Conclusion: The DIP reform significantly reduced the THS per case for LC inpatients, while shifting in-policy expenditures to IPER. The cost-shifting primarily occurred through the redistribution of copayments from category-C to category-B. It is imperative for policymakers to establish differentiated regulatory policies tailored to various cost categories, hospital types, and insured classifications to optimize the effectiveness of the DIP reform.
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