Abraham G Hartzema, Adel Gehchan, Jennifer D Guo, Jianwei Xuan
{"title":"Real-World Evidence for Drug Value Assessment in China: Learning from International Experiences.","authors":"Abraham G Hartzema, Adel Gehchan, Jennifer D Guo, Jianwei Xuan","doi":"10.1007/s40801-026-00557-7","DOIUrl":null,"url":null,"abstract":"<p><p>In China, the national medical insurance system has undergone rapid development over the past two decades. The National Healthcare Security Administration was established to manage the growing healthcare expenditure. Since then, this administration has maintained the drug formulary, known as the National Reimbursement Drug List. The list comprises Category A (essential and cost-effective drugs) and Category B (effective drugs with relatively higher cost profiles), with the Commercial Insurance Innovative Drug list (referred to as Category C) added in 2025. China has made progress in adopting real-world evidence into healthcare decision making. Real-world evidence helps address key uncertainties related to safety, effectiveness, and long-term outcomes to complement clinical trial findings using real-world data from routine clinical practice. Evolving international experiences provide practical insights into the use of real-world evidence to support drug reimbursement and reassessment decisions. This paper proposes practical strategies supporting the integration of real-world evidence into China's drug value assessment to better inform national formulary management and reimbursement pathways.</p>","PeriodicalId":11282,"journal":{"name":"Drugs - Real World Outcomes","volume":" ","pages":"153-157"},"PeriodicalIF":2.0000,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287191/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drugs - Real World Outcomes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40801-026-00557-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/6/4 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
In China, the national medical insurance system has undergone rapid development over the past two decades. The National Healthcare Security Administration was established to manage the growing healthcare expenditure. Since then, this administration has maintained the drug formulary, known as the National Reimbursement Drug List. The list comprises Category A (essential and cost-effective drugs) and Category B (effective drugs with relatively higher cost profiles), with the Commercial Insurance Innovative Drug list (referred to as Category C) added in 2025. China has made progress in adopting real-world evidence into healthcare decision making. Real-world evidence helps address key uncertainties related to safety, effectiveness, and long-term outcomes to complement clinical trial findings using real-world data from routine clinical practice. Evolving international experiences provide practical insights into the use of real-world evidence to support drug reimbursement and reassessment decisions. This paper proposes practical strategies supporting the integration of real-world evidence into China's drug value assessment to better inform national formulary management and reimbursement pathways.
期刊介绍:
Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.