Strategies to Overcome Challenges in Real-World Value Assessment amid Full DRG Implementation

  • Li Zhao The First Affiliated Hospital of Air Force Medical University, Xi’an 710832, Shaanxi, China
  • Xiaolei Liu The First Affiliated Hospital of Air Force Medical University, Xi’an 710832, Shaanxi, China
  • Xinqi Tian The First Affiliated Hospital of Air Force Medical University, Xi’an 710832, Shaanxi, China
  • Yang Liu The First Affiliated Hospital of Air Force Medical University, Xi’an 710832, Shaanxi, China
  • Xiaochun Li The First Affiliated Hospital of Air Force Medical University, Xi’an 710832, Shaanxi, China
Keywords: DRG payment, Health economics, Real-world data (RWD), Real-world evidence (RWE)

Abstract

Against the backdrop of the comprehensive implementation of Diagnosis-Related Groups (DRG), Real-World Value Assessment (RWVA) has become a crucial support for driving healthcare payment system reform and value-oriented decision-making. This paper systematically reviews the evolving trends in international Real-World Evidence (RWE) methodology from 2020 to 2025, analyzing its integration pathways with health economics and the development direction of dynamic value assessment models. Within the context of China’s DRG-based payment policy implementation, it explores the application bottlenecks of Real-World Data (RWD) in technology access and price negotiations, proposing optimization strategies from three dimensions: data, methodology, and policy. The study argues that high-quality, interoperable data infrastructure should be constructed, models integrating RWE and health economics should be refined, and a value-oriented payment decision-making system should be established to optimize healthcare resource allocation and enhance the scientific nature of medical insurance payments. By implementing these strategies, the study anticipates the establishment of a closed-loop mechanism linking evidence generation, value assessment, and payment decision-making, thereby improving the transparency, efficiency, and sustainability of China’s healthcare payment system. The expected outcome is a more data-driven and outcome-oriented policy framework that aligns real-world clinical performance with medical insurance value recognition.

References

Andre E, Gee M, Magnus C, et al., 2024, The Open Hand Initiative: Facilitating the Use of Real-World Evidence in Regulatory Submissions Through Collaboration and Transparency. Clinical Pharmacology and Therapeutics, 117(4): 1072–1077.

Guang M, Erchang Z, Xinlei F, et al., 2024, Evaluation of the Effect of DRG Payment Policy Based on Interrupted Time Series Modeling: Evidence from a Tertiary Hospital in Anhui Province. Health Research Policy and Systems, 22(1): 167.

Nugraha R, Rahadi A, Suharlim C, 2024, Using Real-World Evidence for Health Technology Assessment in Asia: Suggested Typology and Scoping Review. Value in Health Regional Issues, 2024(46): 101068.

Craddock M, Dempsey D, Abdulwahid J, et al., 2024, Challenges and Opportunieis for Real-World Evidence in Clinical Oncology: A View from the UK: Proceedings of a National Workshop. ESMO Real World Data and Digital Oncology, 2024(6): 100089.

Royo A, Jhj R, Weibel D, et al., 2024, Real-World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming. Pharmacoepidemiology and Drug Safety, 33(12): e70062.

Heinz S, Kumari C, Ataide J, et al., 2024, P54 An Insight Into Real-World Evidence (RWE) As a Component of Submission to NICE & CADTH in the Last 3 Years. Value in Health, 27(12S): S13.

Lee A, Yuan Y, Eccles L, et al., 2024, CO86 A Systematic Literature Review (SLR) of Real-World Evidence (RWE) on the First-Line Treatment of Advanced, Metastatic, or Recurrent Non-Small Cell Lung Cancer (NSCLC) With Immunotherapy. Value in Health, 27(12S): S31.

Pignot M, Dagher M, Garcia T, et al., 2024, RWD177 Real-World Evidence (RWE) Study on Burden, Healthcare Resource Utilization, & Cost of Illness Among Patients Diagnosed With Myopia in Germany: Retrospective, Longitudinal, Observational Cohort Claims Data Study. Value in Health, 27(12S): S608.

Wang X, Ye M, Hu M, 2024, HPR29 Impact of Diagnosis-Related Groups (DRG) Payment on the Quality and Efficiency of Peripheral Arterial Disease (PAD) Care: A Mixed-Methods Study. Value in Health, 27(12S): S281.

Luo A, Wang Z, Jiang F, et al., 2024, Influencing factors and mechanism of physicians’ strategic behavior under the DRG payment system. Journal of Central South University (Medical Sciences), 49(11): 1828–1839.

Piers M, Geoff H, Andre D, et al., 2023, Harnessing Oncology Real-World Data with AI. Nature Cancer, 4(12): 1627–1629.

Yuan L, Rahman M, Concato J, 2023, Comparison of Two Assessments of Real-World Data and Real-World Evidence for Regulatory Decision-Making. Clinical and Translational Science, 17(1): e13702.

Lockhart C, McDermott C, 2023, RWD136 Use and Potential of Real-World Data (RWD) and Real-World Evidence (RWE) to Inform Pre-Market Regulatory Decisions: A Scoping Review. Value in Health, 26(12S): S530.

Gendy S, Kumar D, Maskin J, et al., 2023, CO76 Does Next Generation Sequencing (NGS) Improve Outcome in Non-Small Cell Lung Cancer (NSCLC)? A Real-World Data (RWD) Example. Value in Health, 26(12S): S28.

Alagoz O, Winge-Main A, Srinivasan S, et al., 2023, MSR12 Analysis of Long-Term Survivorship (LTS) Rates for Stage 2B/2C Melanoma Using Published Real-World Data (RWD) and Data From Randomized Controlled Trials (RCTS). Value in Health, 26(12S: S395.

Published
2025-11-10