Impacts of Diagnosis-Intervention Packet Payment Reform on the Behaviour of Inpatient Care in Private Hospitals: Evidence From a Pilot City, China

Chen, Ruoxi; Yang, Qiao; Chen, Weizhuo; Zhong, Sisi; Chen, Junyi; Qian, Jiamei; Chen, Yuxuan; Ye, Ting

doi:10.34172/ijhpm.9545

Impacts of Diagnosis-Intervention Packet Payment Reform on the Behaviour of Inpatient Care in Private Hospitals: Evidence From a Pilot City, China

Document Type : Original Article

Authors

Ruoxi Chen ¹^{, 2}

Qiao Yang ¹^{, 2}

Weizhuo Chen ¹^{, 2}

Sisi Zhong ¹^{, 2}

Junyi Chen ¹^{, 2}

Jiamei Qian ¹^{, 2}

Yuxuan Chen ³

Ting Ye ¹^{, 2}

¹ School of Medicine Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

² Research Centre for Rural Health Service, Key Research Institute of Humanities & Social Sciences of Hubei Provincial Department of Education, Wuhan, China

³ School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

10.34172/ijhpm.9545

Abstract

Background
An innovative payment method, the diagnosis-intervention packet (DIP), has been piloted in China since 2020 and was fully implemented in City A in November 2022. However, its specific impact on private hospitals remains inadequately explored. This study aimed to examine how the reform influenced inpatient care behaviours in private hospitals.

Methods
Using a dataset comprising 38 296 inpatient reimbursement records from 2021 to 2023 in a western city in China, 5 private hospitals included in the first batch of pilot institutions were selected as the treatment group, while 3 non-pilot private hospitals constituted the control group. Difference-in-differences (DID) analyses was conducted to estimate policy effects on providers’ inpatient care behaviours across four dimensions: cost control, service-volume adjustment, patient type, and quality risk.

Results
Following the reform, significant changes were observed across several outcome dimensions. Regarding servicevolume adjustment, the average length of stay decreased significantly (-1.94; 95% CI: -3.75 to -0.13), and average monthly admissions also declined (-30.36; 95% CI: -59.52 to -1.20). No statistically significant change was observed in patient type. For cost control, the average expenditure per admission decreased significantly by US $670.50 (95% CI: -1149.80 to -191.18). Out-of-pocket (OOP) expenditure per admission also declined by US $118.89 (95% CI: -188.88 to -48.90), although the share of OOP expenditure in total costs increased slightly (0.02; 95% CI: 0.05-4.64). As for quality risk, perihospitalisation outpatient visits increased significantly (1.473; 95% CI: 0.252-2.694).

Conclusion
The DIP payment reform in private hospitals contributed to cost containment and process optimisation. However, the structural tension between standardised payment mechanisms and market-oriented hospital operations may generate short-term adjustments that prioritise cost control over quality improvement. Under strict cost-control incentives, hospitals may adopt strategic responses such as shortening inpatient stays and adjusting patient composition, which could pose potential risks to healthcare quality.

Keywords

Diagnosis-Intervention Packet

Payment Reform

Private Hospitals

Medical Expenditure

Medical Efficiency

Medical Quality

1. Chen Y, Zhang X, Tang X, Yan J, Qian M, Ying X. How do inpatients’ costs, length of stay, and quality of care vary across age groups after a new case-based payment reform in China? An interrupted time series analysis. BMC Health Serv Res. 2023;23(1):160. doi:10.1186/s12913-023-09109-z

2. Zhang Y, Xu S, Tan G. Unraveling the effects of DIP payment reform on in-patient healthcare: Insights into impacts and challenges. BMC Health Serv Res. 2024;24(1):887. doi:10.1186/s12913-024-11363-8

3. Qian M, Zhang X, Chen Y, Xu S, Ying X. The pilot of a new patient classifi-cation-based payment system in China: The impact on costs, length of stay and qual-ity. Soc Sci Med. 2021;289:114415. doi:10.1016/j.socscimed.2021.114415

4. He AJ. Scaling-up through piloting: Dual-track provider payment reforms in China’s health system. Health Policy Plan. 2023;38(2):218-227. doi:10.1093/heapol/czac080

5. Li XF, Han YB, Yang W. A study of policy synergy in 71 pilot cities of DIP payment. Chin Health Econ. 2024;43(5):37-42.

6. Lin K, Yao Y, Xiong Y, Xiang L. The effect of an innovative payment meth-od on inpatient volume and bed resources and their regional distribution: the case of a central province in China. Int J Equity Health. 2024;23(1):159. doi:10.1186/s12939-024-02243-y

7. Shi H, Cheng Z, Liu Z, Zhang Y, Zhang P. Does a new case-based payment system promote the construction of the ordered health delivery system? Evidence from a pilot city in China. Int J Equity Health. 2024;23(1):55. doi:10.1186/s12939-024-02146-y

8. Wu J, He X, Feng XL. Can case-based payment contain healthcare costs? - a curious case from China. Soc Sci Med. 2022;312:115384. doi:10.1016/j.socscimed.2022.115384

9. Annear PL, Kwon S, Lorenzoni L, et al. Pathways to DRG-based hospital payment systems in Japan, Korea, and Thailand. Health Policy. 2018;122(7):707-713. doi:10.1016/j.healthpol.2018.04.013

10. Kutz A, Gut L, Ebrahimi F, Wagner U, Schuetz P, Mueller B. Association of the Swiss diagnosis-related group reimbursement system with length of stay, mortality, and readmission rates in hospitalized adult patients. JAMA Netw Open. 2019;2(2):e188332. doi:10.1001/jamanetworkopen.2018.8332

11. Vuagnat A, Yilmaz E, Roussot A, et al. Did case-based payment influence surgical readmission rates in France? A retrospective study. BMJ Open. 2018;8(2):e018164. doi:10.1136/bmjopen-2017-018164

12. Zhang X, Tang S, Wang R, Qian M, Ying X, Maciejewski ML. Hospital response to a new case-based payment system in China: the patient selection effect. Health Policy Plan. 2024;39(5):519-527. doi:10.1093/heapol/czae022

13. Jin P, Biller‐Andorno N, Wild V. Ethical implications of case-based payment in China: A systematic analysis. Dev World Bioeth. 2015;15(3):134-142. doi:10.1111/dewb.12055

14. Ellis RP, McGuire TG. Hospital response to prospective payment: Moral hazard, selection, and practice-style effects. J Health Econ. 1996;15(3):257-277. doi:10.1016/0167-6296(96)00002-1

15. Li T, Yuan Z. Analysis on the performance of urban medical insurance payment by disease-scores in Suqian. China Health Insur. 2016;(8):46-49.

16. Tu XF, Wan XX. The performance of payment by disease-scores under the total budget management in Nanchang. China Health Insur. 2016;(12):43-45.

17. Lai Y, Fu H, Li L, Yip W. Hospital response to a case-based payment scheme under regional global budget: the case of Guangzhou in China. Soc Sci Med. 2022;292:114601. doi:10.1016/j.socscimed.2021.114601

18. Liu X, Lyu H, Jin H. Bridging care hierarchies through regional global budget payment: Evidence from county medical communities in Zhejiang province, China. Health Policy Plan. 2025;40(8):843-853. doi:10.1093/heapol/czaf046

19. Zhang XY, Yan JQ, Wang RX, Lv DW, Qian MH, Ying XH. Study on impact of diagnosis-intervention packet reform on the quality of healthcare. Chin Hosp Manag. 2023;43(12):16-19.

20. Meng Y, Zhang X, Han J. The impact of medical insurance programmes on the health of the insured: evidence from China. Int J Health Plann Manage. 2020;35(3):718-734. doi:10.1002/hpm.2931

21. Ding Y, Yin J, Zheng C, Dixon S, Sun Q. The impacts of diagnosis-intervention packet payment on the providers’ behavior of inpatient care—evidence from a national pilot city in China. Front Public Health. 2023;11:1069131. doi:10.3389/fpubh.2023.1069131

22. Lin H-C, Xirasagar S, Kao S. Association of hospital ownership with patient transfers to outpatient care under a prospective payment system in Taiwan. Health Policy. 2004;69(1):11-19. doi:10.1016/j.healthpol.2003.11.003

23. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383. doi:10.1016/0021-9681(87)90171-8

24. Sundararajan V, Henderson T, Perry C, Muggivan A, Quan H, Ghali WA. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol. 2004;57(12):1288-1294. doi:10.1016/j.jclinepi.2004.03.012

25. Cai J. Empirical research on the implementation effects on diagnosis-intervention packet. Chin Med Rec. 2021;22(4):28-30.

26. Yuan S, Liu W, Wei F, et al. Impacts of hospital payment based on diagnosis related groups (DRGs) with global budget on resource use and quality of care: A case study in China. Iran J Public Health. 2019;48(2):238-246.

27. Zhang T, Xu Y, Ren J, Sun L, Liu C. Inequality in the distribution of health resources and health services in China: hospitals versus primary care institutions. Int J Equity Health. 2017;16(1):42. doi:10.1186/s12939-017-0543-9

28. Zhang Y, Wang Q, Jiang T, Wang J. Equity and efficiency of primary health care resource allocation in mainland China. Int J Equity Health. 2018;17(1):140. doi:10.1186/s12939-018-0851-8

29. Chen ML, Zhao B, Yang X. Analysis and perfection of technical essential in disease-based score payment. Chin Health Econ. 2019;(4):27-31.

30. Wang R, Yan J, Zhang X, Qian M, Ying X. Impact of the diagnosis-intervention packet payment reform on provider behavior in China: A controlled interrupted time series study. Int J Health Policy Manag. 2024;13:8463. doi:10.34172/ijhpm.8463

31. Jian W, Lu M, Liu G, Chan KY, Poon AN. Beijing’s diagnosis-related group payment reform pilot: Impact on quality of acute myocardial infarction care. Soc Sci Med. 2019;243:112590. doi:10.1016/j.socscimed.2019.112590

32. Choi JW, Kim SJ, Park HK, Jang SI, Kim TH, Park EC. Effects of a mandatory DRG payment system in South Korea: analysis of multi-year nationwide hospital claims data. BMC Health Serv Res. 2019;19(1):776. doi:10.1186/s12913-019-4650-8

33. Zhou XD, Li L, Hesketh T. Health system reform in rural China: Voices of healthworkers and service-users. Soc Sci Med. 2014;117:134-141. doi:10.1016/j.socscimed.2014.07.040

34. Zhang A, Nikoloski Z, Mossialos E. Does health insurance reduce out-of-pocket expenditure? Heterogeneity among China’s middle-aged and elderly. Soc Sci Med. 2017;190:11-19. doi:10.1016/j.socscimed.2017.08.005

35. Yang D, Acharya Y, Liu X. Social health insurance consolidation and urban-rural inequality in utilization and financial risk protection in China. Soc Sci Med. 2022;308:115200. doi:10.1016/j.socscimed.2022.115200