Does Payment Variation Across Insurance Types for Diagnosis-Intervention Packet Exacerbate Health Disparities?

Background China's Diagnosis-Intervention Packet (DIP) reform establishes an innovative payment mechanism that combines global budget ceilings with performance-based incentives. However, DIP uses dual-pool financing for Urban Employee Basic Medical Insurance (UEBMI) and Urban-Rural Resident Basic Medical Insurance (URRBMI), each with distinct point values, raising concerns about potential provider selection and equity distortion. This study examined whether DIP implementation influenced provider behavior differently across insurance types and whether point value disparities induced strategic selection against URRBMI patients over time. Methods We used administrative claims data from all public hospitals in City A, a nationally designated DIP pilot city in Central China. We conducted interrupted time series (ITS) analyses across three policy phases of DIP implementation (June 2021–December 2023), including 1,749,036 inpatient admissions across UEBMI and URRBMI schemes. Main outcomes included 7-day all-cause readmission (quality), low- and high-relative weight (RW) case shares (case mix), decomposed admissions (strategic behavior), and admission volume shifts by insurance type. Outcomes were aggregated monthly and modeled using ITS with interactions for insurance type and hospital level. Results Hospitals initially favored UEBMI patients, with higher high-RW case shares and lower decomposition rates. URRBMI admissions significantly increased during the first annual budget reconciliation cycle, particularly for low-RW and decomposed admissions, indicating purposeful budget absorption. Significant decreases in decomposition and readmission trends among URRBMI hospitals were noted following the second annual budget reconciliation cycle, suggesting regulatory containment. As case-mix convergence between insurance types developed over time, enhanced regulatory enforcement and standardization led to better procedural equity. Conclusions The implementation of DIP accompanied dynamic behavioral changes influenced by regulatory enforcement, policy feedback, and payment asymmetry. The observed convergence among insurance types was driven not just by equity gains, but also by institutional learning and budget optimization. Policymakers should consider regional capability and monitoring intensity to ensure that future payment models promote equity and efficiency.