Kerman University of Medical Sciences International Journal of Health Policy and Management 2322-5939 13 1 2024 12 01 Impact of the Diagnosis-Intervention Packet Payment Reform on Provider Behavior in China: A Controlled Interrupted Time Series Study 1 10 4677 10.34172/ijhpm.8463 EN Ruixin Wang School of Public Health, Fudan University, Shanghai, China Jiaqi Yan School of Public Health, Fudan University, Shanghai, China Xinyu Zhang School of Public Health, Fudan University, Shanghai, China Mengcen Qian School of Public Health, Fudan University, Shanghai, China Xiaohua Ying School of Public Health, Fudan University, Shanghai, China Key Laboratory of Health Technology Assessment (Fudan University), Ministry of Health, Shanghai, China Journal Article 2024 02 18 Background China has developed a novel case-based payment method called the diagnosis-intervention packet (DIP) to regulate healthcare providers’ behavior. G city, a metropolis in southeast China, has shifted its payment policy from fixed rate per admission to DIP under regional global budget since 2018. This study examined the immediate and trend changes in provider behavior after this payment reform. Methods Discharge data in G city between 2016 and 2019 was used, covering more than 10 million inpatient cases in 320 hospitals. A counterfactual scenario was developed to assign insured and uninsured inpatients across the study period to specific DIP groups under consistent rules. Controlled interrupted time series (ITS) analyses were performed, with uninsured inpatients as control. Outcomes included inpatient volume, average DIP weight (similar to case-mix index [CMI] in diagnosis-related groups [DRGs]), and two innovative indicators (average diagnostic weight and average treatment weight) to decompose the changes in DIP weight. Subgroup analyses were conducted for different hospital levels and 21 major disease categories. Results After the DIP reform, monthly trend of inpatient volume decreased (-1085.34, P = .052), while monthly growth of average DIP weight increased (2.17, P = .02). No significant changes in average diagnostic weight were observed. Monthly trend of average treatment weight increased (2.38, P = .001) after the reform. Secondary and tertiary hospitals experienced insignificantly decreased inpatient volume and elevated average DIP weight, accompanied by negligible change in average diagnostic weight and significant increase in average treatment weight. Primary hospitals experienced reduced inpatient volume and stable average DIP weight, along with increase in average diagnostic weight and decrease in average treatment weight. Conclusion By differentiated payments for severity, DIP induced hospitals to shift their focus from volume to weight of inpatients. Instead of diagnostic upcoding, hospitals responded to the DIP reform primarily by increasing treatment intensity. Primary hospitals may face financial risks under regional competition.

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