Purpose: China's diagnosis-intervention packet (DIP) policy, a medical insurance payment system leveraging big data, was implemented in Wuhu, China, in January 2021. Studies have proven that the DIP has been effective in reducing medication costs for elderly hospital patients with hypertension. However, research on hospitalization costs for other patients remains limited. As the incidence of malignant tumors has increased dramatically in China, this study assesses the system's impact on hospitalization costs for patients with malignant tumors to confirm its broader effects.

Patients And Methods: Data on patients with malignant tumors (ICD codes C00-C97) were collected from a tertiary medical institution in Wuhu, using the policy's implementation in January 2021 as the beginning timepoint. Outcome indicators included average monthly hospitalization expenses and sub-expenses for hospitalized patients with malignant tumors. A 48-month time-series database was constructed and the interruption time series model used to evaluate the changing trends in expenses before and after the DIP implementation.

Results: After DIP implementation, average hospitalization costs for patients with malignant tumors showed a statistically significant downward trend. Subgroup analysis revealed that patients with shorter hospital stays (1-5 days) and cured outcomes saw the biggest expense drop from hospital cost-control effects. The DIP policy also affected cost structures, initially increasing diagnostic fees and consumable costs, but significantly reducing treatment fees, medication costs, and other related costs.

Conclusion: The study confirmed the effectiveness of the DIP policy in controlling hospitalization costs for patients with malignant tumors. Going forward, the government should optimize DIP rules to clarify cost calculation methods and prevent excessive use of high-cost diagnostics and consumables. Continued monitoring and evaluation are essential to ensure that the policy's benefits are maintained over time. Medical institutions should improve resource allocation, diagnosis, and treatment efficiency; reduce unnecessary stays; and provide tailored treatment plans and cost support for patients with poor prognosis.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11874756PMC
http://dx.doi.org/10.2147/RMHP.S502474DOI Listing

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