Randomized double-blind controlled trials (RCTs) conduct researches in carefully selected populations to ensure results of RCTs are unaffected by external disturbances and provide evidence of safety and efficacy. Real-world researches further help to understand the real world effects of new technologies in different medical environments after-market authorization. RCTs are the evidence foundation of real-world researches, and real-world researches provide valuable complement to RCTs. Medical insurance database is one of the most important database in real-world researches. Now, China's national medical insurance is entering a new era and transits from passive payment and compensation into a value-based strategic purchase mechanism for its insured population to buy the most cost-effective services. It is necessary to establish a mature, well-organized and value-based mechanism. The core of such mechanism is values, which is the price/performance ratio of innovative medicines and technologies rather than looking at the price solely. Demonstrating innovative drug value is an essential part of health care assessment. The authors argue that the assessment of the overall value of innovative technologies or medicines should include and based on the following four dimensions: clinical value, economic value, patient value and society value.
Citation:
XUAN Jianwei, LI Youping. Real-world research and demonstration of innovative drug value. Chinese Journal of Evidence-Based Medicine, 2018, 18(4): 273-276. doi: 10.7507/1672-2531.201801090
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- 1. ISPOR Connection. Real-life data: a growing need. Available at: http://www.ispor.org/News/articles/Oct07/RLD.asp.
- 2. U.S. Department of Health and Human Services of Food and Drug Administration, Center for Devices and Radiological Health of Center for Biologics Evaluation and Research. Draft guidance for industry and food and drug administration staff- use of real-world evidence to support regulatory decision-making for medical devices. Available at: https://wwwn.cdc.gov/cliac/pdf/Addenda/cliac0811/T_ addendum_FDA_Draft_Guidance_for_Mobile_Medical_Devices.pdf.
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- 4. 周光华, 辛英, 张雅洁, 等. 医疗卫生领域大数据应用探讨. 中国卫生信息管理杂志, 2013, 10(4): 296-300, 304.
- 5. 王潇, 张爱迪, 严谨. 大数据在医疗卫生中的应用前景. 中国全科医学, 2015, 18(1): 113-115.