Hospital response to a new case-based payment system in China: the patient selection effect.
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2024-05
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Providers have intended and unintended responses to payment reforms, such as China's new case-based payment system, i.e. Diagnosis-Intervention Packet (DIP) under global budget, that classified patients based on the combination of principal diagnosis and procedures. Our study explores the impact of DIP payment reform on hospital selection of patients undergoing total hip/knee arthroplasty (THA/TKA) or with arteriosclerotic heart disease (AHD) from July 2017 to June 2021 in a large city. We used a difference-in-differences approach to compare the changes in patient age, severity reflected by the Charlson Comorbidity Index (CCI), and a measure of treatment intensity [relative weight (RW)] in hospitals that were and were not subject to DIP incentives before and after the DIP payment reform in July 2019. Compared with non-DIP pilot hospitals, trends in patient age after the DIP reform were similar for DIP and non-DIP hospitals for both conditions, while differences in patient severity grew because severity in DIP hospitals increased more for THA/TKA (P = 0.036) or dropped in non-DIP hospitals for AHD (P = 0.011) following DIP reform. Treatment intensity (measured via RWs) for AHD patients in DIP hospitals increased 5.5% (P = 0.015) more than in non-DIP hospitals after payment reform, but treatment intensity trends were similar for THA/TKA patients in DIP and non-DIP hospitals. When the DIP payment reform in China was introduced just prior to the pandemic, hospitals subject to this reform responded by admitting sicker patients and providing more treatment intensity to their AHD patients. Policymakers need to balance between cost containment and the unintended consequences of prospective payment systems, and the DIP payment could also be a new alternative payment system for other countries.
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Zhang, Xinyu, Shenglan Tang, Ruixin Wang, Mengcen Qian, Xiaohua Ying and Matthew L Maciejewski (2024). Hospital response to a new case-based payment system in China: the patient selection effect. Health policy and planning, 39(5). pp. 519–527. 10.1093/heapol/czae022 Retrieved from https://hdl.handle.net/10161/31269.
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Scholars@Duke
![Zhang](https://scholars.duke.edu/profile-images/thumbnail200/0958969.jpg)
Xinyu Zhang
![Tang](https://scholars.duke.edu/profile-images/thumbnail200/0579184.jpg)
Shenglan Tang
Areas of Expertise: Health Services Research, Health Policy, Disease Control Strategy, and Implementation Science
![Maciejewski](https://scholars.duke.edu/profile-images/thumbnail200/0406259.jpg)
Matthew Leonard Maciejewski
Matt Maciejewski, PhD is a Professor in the Department of Population Health Sciences. He is also a Senior Research Career Scientist and Director of the Non-randomized Design Lab in the Center of Innovation to Accelerate Discovery and Practice Transformation at the Durham VA Medical Center. Matt also holds Adjunct Professor appointments in the Schools of Public Health and Pharmacy at the University of North Carolina at Chapel Hill.
He has received funding from NIDDK, NIDA, CMS, AHRQ, VA HSR&D, and the RWJ Foundation to conduct evaluation of long-term clinical and economic outcomes of surgical interventions, behavioral interventions and Medicare program/policy changes on patients with obesity or cardiometabolic conditions. He is also interested in methods for addressing unobserved confounding in observational studies. Matt evaluated the first-ever population-based implementation of value-based insurance design and led the first-ever linkage of lab results and Medicare FFS claims. He has published over 250 papers in peer-reviewed journals such as JAMA, JAMA Internal Medicine, JAMA Surgery, Annals of Internal Medicine, Health Economics, Medical Care, Health Services Research, Journal of Clinical Epidemiology and Diabetes Care.
Areas of expertise: Health Services Research, Health Economics, Health Policy, Multimorbidity
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