Real-world studies(RWSs)have emerged as a transformative force in oncology research,complementing traditional randomized controlled trials(RCTs)by providing comprehensive insights into cancer care within routine clini...Real-world studies(RWSs)have emerged as a transformative force in oncology research,complementing traditional randomized controlled trials(RCTs)by providing comprehensive insights into cancer care within routine clinical settings.This review examines the evolving landscape of RWSs in oncology,focusing on their implementation,methodological considerations,and impact on precision medicine.We systematically analyze how RWSs leverage diverse data sources,including electronic health records(EHRs),insurance claims,and patient registries,to generate evidence that bridges the gap between controlled clinical trials and real-world clinical practice.The review underscores the key contributions of RWSs,including capturing therapeutic outcomes in traditionally underrepresented populations,expanding drug indications,and evaluating long-term safety and effectiveness in routine clinical settings.While acknowledging significant challenges,including data quality variability and privacy concerns,we discuss how emerging technologies like artificial intelligence are helping to address these limitations.The integration of RWSs with traditional clinical research is revolutionizing the paradigm of precision oncology and enabling more personalized treatment approaches based on real-world evidence.展开更多
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 valueoriented de...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 valueoriented 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.展开更多
基金supported by the Zhejiang Provincial Natural Science Foundation(No.ZCLY24H1601)the National Natural Science Foundation of China(No.82403697)+1 种基金the Medical and Health Science and Technology Project of Zhejiang Province(No.2025KY411)the National Key R&D Program of China(No.2022YFC2505100).
文摘Real-world studies(RWSs)have emerged as a transformative force in oncology research,complementing traditional randomized controlled trials(RCTs)by providing comprehensive insights into cancer care within routine clinical settings.This review examines the evolving landscape of RWSs in oncology,focusing on their implementation,methodological considerations,and impact on precision medicine.We systematically analyze how RWSs leverage diverse data sources,including electronic health records(EHRs),insurance claims,and patient registries,to generate evidence that bridges the gap between controlled clinical trials and real-world clinical practice.The review underscores the key contributions of RWSs,including capturing therapeutic outcomes in traditionally underrepresented populations,expanding drug indications,and evaluating long-term safety and effectiveness in routine clinical settings.While acknowledging significant challenges,including data quality variability and privacy concerns,we discuss how emerging technologies like artificial intelligence are helping to address these limitations.The integration of RWSs with traditional clinical research is revolutionizing the paradigm of precision oncology and enabling more personalized treatment approaches based on real-world evidence.
基金25th batch of key projects of the Chinese Society of Health Economics:Exploration of Practical Paths for the Integration of Business and Finance in Public Hospitals(Project No.:CHEA2425040403)。
文摘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 valueoriented 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.
