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.