Exploring the patterns of real-world data governance in the context of special healthcare policy_Chinese Journal of Evidence-Based Medicine

Authors：

JIA Yulong ^1,2,3 , YAO Minghong ^1,2,3 , LIU Yanmei ^1,2,3 , REN Yan ^1,2,3 , ZOU Kang ^1,2,3 ,  LI Yaohua ⁴ ,  SUN Xin ^1,2,3

1. Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P.R.China;
2. NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, Chengdu 610041, P.R.China;
3. Sichuan Center of Technology Innovation for Real World Data, Chengdu 610041, P.R.China;
4. Hainan Provincial Drug and Medical Device Evaluation Service Center, Haikou 570216, P.R.China;

Corresponding author：

LI Yaohua, Email: sunx79@hotmail.com; SUN Xin, Email: sunxin@wchscu.cn

Keywords：

Licensed medical care; Boao hope city; Real-world study; Data management; Data governance

DOI：

10.7507/1672-2531.202108147

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

With the increasing improvement of real-world evidence as a research system and guideline specification for pre-market registration and post-market regulatory decision support of clinically urgent drug and mechanical products, identifying an approach to ensure the high quality and standards of real-world data and establishing a basis for the generation of real-world evidence is receiving increasing attention and concern from regulatory authorities. Based on the experience of Boao hope city real-world data research pattern and ophthalmic data platform construction, this paper discussed the "source data-database-evidence chain" generation process, data management, and data governance in real-world study from the special features and necessity of multiple sources and heterogeneity of data, multiple research designs, and standardized regulatory requirements, and provided references for further construction of comprehensive research data platforms in the future.

Citation： JIA Yulong, YAO Minghong, LIU Yanmei, REN Yan, ZOU Kang, LI Yaohua, SUN Xin. Exploring the patterns of real-world data governance in the context of special healthcare policy. Chinese Journal of Evidence-Based Medicine, 2021, 21(12): 1373-1380. doi: 10.7507/1672-2531.202108147 Copy

1.	王雯, 谭婧, 任燕, 等. 重新认识真实世界数据研究: 更新与展望. 中国循证医学杂志, 2020, 20(11): 1241-1246.
2.	孙鑫, 谭婧, 唐立, 等. 重新认识真实世界研究. 中国循证医学杂志, 2017, 17(2): 126-130.
3.	国家药品监督管理局药品审评中心. 用于产生真实世界证据的真实世界数据指导原则(试行), 2021. Available at: http://www.cde.org.cn/news.do?method=largeInfo&id=eaed86b800e8d9d9.
4.	国家发展改革委, 国家卫生健康委, 国家中医药局, 等. 关于支持建设博鳌乐城国际医疗旅游先行区的实施方案, 2019. Available at:http://www.gov.cn/xinwen/2019-09/17/content_5430452.htm.
5.	任燕, 姚明宏, 姚晨, 等. 特许创新药械在博鳌乐城开展真实世界数据研究的模式探索. 中国食品药品监管, 2020, (11): 14-20.
6.	任燕, 梁远波, 刘密密, 等. 构建博鳌乐城创新药械真实世界数据研究体系: 基于我国首个使用境内真实世界数据获批上市的医疗器械研究的探讨. 中国循证医学杂志, 2020, 20(10): 1117-1123.
7.	姚明宏, 贾玉龙, 任燕, 等. 特许医疗政策下的药械真实世界数据研究常见设计及其关键考虑. 中华流行病学杂志, 2021, 42(7): 1306-1311.
8.	国家药品监督管理局药品审评中心. 真实世界证据支持药物研发与审评的指导原则(试行), 2020. Available at: https://www.nmpa.gov.cn/yaopin/ypggtg/ypqtgg/20200107151901190.html.
9.	U. S. FDA. Framework for FDA’s real world evidence program, 2018. Available at:https://www.fda.gov/drugs/webinar-framework-fdas-real-world-evidence-program-mar-15-2019.
10.	国家药品监督管理局. 临床试验数据管理工作技术指南, 2016. Available at: https://wenku.baidu.com/view/3e468e1f5ef7ba0d4b733bc0.html.
11.	U. S. FDA. Guidance for industry computerized systems used in clinical investigations, 2007. Available at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/computerized-systems-used-clinical-investigations.
12.	European Medicines Agency. Reflection paper on expectations for electronic source data and data transcribed to electronic data collection tools in clinical trials, 2010. Available at: https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/reflection-paper-expectations-electronic-source-data-data-transcribed-electronic-data-collection_en.pdf.
13.	国家药品监督管理局. 临床试验的电子数据采集技术指导原则, 2016. Available at: https://www.nmpa.gov.cn/yaopin/ypggtg/ypqtgg/20160729184001958.html.
14.	国家药品监督管理局. 真实世界数据用于医疗器械临床评价技术指导原则(试行), 2020. Available at: https://www.nmpa.gov.cn/xxgk/ggtg/qtggtg/20201126090030150.html.
15.	国家药品监督管理局, 国家卫生健康委员会. 药物临床试验质量管理规范, 2020. Available at:https://www.nmpa.gov.cn/xxgk/ggtg/qtggtg/20200426162401243.html.
16.	Society for Clinical Data Management. Good clinical data management practices, 2013. Available at: http://www.doctorama.com/event/Good-Clinical-Data-Management-Practices-GCDMP-28264.htm.
17.	国家药品监督管理局药品审评中心. 药物临床试验数据递交指导原则(试行), 2020. Available at: https://www.nmpa.gov.cn/yaopin/ypggtg/ypqtgg/20200720171201514.html.
18.	Andriole KP. Security of electronic medical information and patient privacy: what you need to know. J Am Coll Radiol, 2014, 11(12PtB): 1212-1216.
19.	谭婧, 程亮亮, 王雯, 等. 患者登记研究的策划与患者登记数据库构建: 基于观察性设计的真实世界研究. 中国循证医学杂志, 2017, 17(12): 1365-1372.
20.	Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng, 2018, 2(10): 719-731.
21.	张淑杰. 基于云计算技术的大数据分析平台设计与开发. 电子测试, 2021, (2): 78-79,94.
22.	丁发明, 闫慧, 黄天娇. 对临床试验中运用远程智能技术的监管策略的科学建议. 中国食品药品监管, 2020, (11): 125-133.
23.	Health Level Seven International. HL7 Standards, 2021. Available at:https://www.hl7.org/.
24.	Khvastova M, Witt M, Essenwanger A, et al. Towards interoperability in clinical research - enabling fhir on the open-source research platform XNAT. J Med Syst, 2020, 44(8): 137.
25.	李雪迎, 姚晨, 晋菲斐, 等. 面向真实世界数据的临床研究数据治理模式选择. 中国循证医学杂志, 2020, 20(10): 1150-1156.
26.	国务院办公厅. 关于促进和规范健康医疗大数据应用发展的指导意见, 2016. Available at: http://www.gov.cn/zhengce/content/2016-06/24/content_5085091.htm#.
27.	Foundation O. What is openEHR? 2021. Available at:https://www.openehr.org/about/what_is_openehr.
28.	Wulff A, Mast M, Hassler M, et al. Designing an openEHR-based pipeline for extracting and standardizing unstructured clinical data using natural language processing. Methods Inf Med, 2020, 59(S02): e64-e78.
29.	国家卫生计生委. 卫生信息共享文档编制规范, 2016. Available at:http://www.nhc.gov.cn/wjw/s9497/201607/f1472d0f82bf48ebb8da4ffe5000e0aa.shtml.
30.	CDISC Submission Data Standards Team. Study data tabulation model implementation guide: human clinical trials version 3.3 (final), 2018. Available at: http://www.sastricks.com/cdisc/SDTMIG_v3.3_FINAL.pdf.
31.	Riepenhausen S, Mertens C, Dugas M. Comparing SDTM and FHIR® for real world data from electronic health records for clinical trial submissions. Stud Health Technol Inform, 2021, 281: 585-589.
32.	OMOP. Common data model, 2021. Available at: https://github.com/OHDSI/CommonDataModel.
33.	侯丽, 李露琪, 唐灵逸, 等. OHDSI通用数据模型及医学术语标准国内应用现状分析. 医学信息学杂志, 2020, 41(2): 1-10.
34.	阎小妍, 董冲亚, 姚晨. 保障中国临床试验数据的准确性. 英国医学杂志中文版, 2018, 21(11): 639-640.
35.	中国医院协会信息专业委员会. 医疗机构医疗大数据平台建设指南(征求意见稿). 北京: 中国工信出版集团, 2019.
36.	国家药品监督管理局. 深刻认识和准确把握“十四五”时期我国发展面临的外部环境, 2020. Available at: https://www.nmpa.gov.cn/zhuanti/bwchx/bwxxjl/20201218085425130.html.

1. 王雯, 谭婧, 任燕, 等. 重新认识真实世界数据研究: 更新与展望. 中国循证医学杂志, 2020, 20(11): 1241-1246.
2. 孙鑫, 谭婧, 唐立, 等. 重新认识真实世界研究. 中国循证医学杂志, 2017, 17(2): 126-130.
3. 国家药品监督管理局药品审评中心. 用于产生真实世界证据的真实世界数据指导原则(试行), 2021. Available at: http://www.cde.org.cn/news.do?method=largeInfo&id=eaed86b800e8d9d9.
4. 国家发展改革委, 国家卫生健康委, 国家中医药局, 等. 关于支持建设博鳌乐城国际医疗旅游先行区的实施方案, 2019. Available at:http://www.gov.cn/xinwen/2019-09/17/content_5430452.htm.
5. 任燕, 姚明宏, 姚晨, 等. 特许创新药械在博鳌乐城开展真实世界数据研究的模式探索. 中国食品药品监管, 2020, (11): 14-20.
6. 任燕, 梁远波, 刘密密, 等. 构建博鳌乐城创新药械真实世界数据研究体系: 基于我国首个使用境内真实世界数据获批上市的医疗器械研究的探讨. 中国循证医学杂志, 2020, 20(10): 1117-1123.
7. 姚明宏, 贾玉龙, 任燕, 等. 特许医疗政策下的药械真实世界数据研究常见设计及其关键考虑. 中华流行病学杂志, 2021, 42(7): 1306-1311.
8. 国家药品监督管理局药品审评中心. 真实世界证据支持药物研发与审评的指导原则(试行), 2020. Available at: https://www.nmpa.gov.cn/yaopin/ypggtg/ypqtgg/20200107151901190.html.
9. U. S. FDA. Framework for FDA’s real world evidence program, 2018. Available at:https://www.fda.gov/drugs/webinar-framework-fdas-real-world-evidence-program-mar-15-2019.
10. 国家药品监督管理局. 临床试验数据管理工作技术指南, 2016. Available at: https://wenku.baidu.com/view/3e468e1f5ef7ba0d4b733bc0.html.
11. U. S. FDA. Guidance for industry computerized systems used in clinical investigations, 2007. Available at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/computerized-systems-used-clinical-investigations.
12. European Medicines Agency. Reflection paper on expectations for electronic source data and data transcribed to electronic data collection tools in clinical trials, 2010. Available at: https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/reflection-paper-expectations-electronic-source-data-data-transcribed-electronic-data-collection_en.pdf.
13. 国家药品监督管理局. 临床试验的电子数据采集技术指导原则, 2016. Available at: https://www.nmpa.gov.cn/yaopin/ypggtg/ypqtgg/20160729184001958.html.
14. 国家药品监督管理局. 真实世界数据用于医疗器械临床评价技术指导原则(试行), 2020. Available at: https://www.nmpa.gov.cn/xxgk/ggtg/qtggtg/20201126090030150.html.
15. 国家药品监督管理局, 国家卫生健康委员会. 药物临床试验质量管理规范, 2020. Available at:https://www.nmpa.gov.cn/xxgk/ggtg/qtggtg/20200426162401243.html.
16. Society for Clinical Data Management. Good clinical data management practices, 2013. Available at: http://www.doctorama.com/event/Good-Clinical-Data-Management-Practices-GCDMP-28264.htm.
17. 国家药品监督管理局药品审评中心. 药物临床试验数据递交指导原则(试行), 2020. Available at: https://www.nmpa.gov.cn/yaopin/ypggtg/ypqtgg/20200720171201514.html.
18. Andriole KP. Security of electronic medical information and patient privacy: what you need to know. J Am Coll Radiol, 2014, 11(12PtB): 1212-1216.
19. 谭婧, 程亮亮, 王雯, 等. 患者登记研究的策划与患者登记数据库构建: 基于观察性设计的真实世界研究. 中国循证医学杂志, 2017, 17(12): 1365-1372.
20. Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng, 2018, 2(10): 719-731.
21. 张淑杰. 基于云计算技术的大数据分析平台设计与开发. 电子测试, 2021, (2): 78-79,94.
22. 丁发明, 闫慧, 黄天娇. 对临床试验中运用远程智能技术的监管策略的科学建议. 中国食品药品监管, 2020, (11): 125-133.
23. Health Level Seven International. HL7 Standards, 2021. Available at:https://www.hl7.org/.
24. Khvastova M, Witt M, Essenwanger A, et al. Towards interoperability in clinical research - enabling fhir on the open-source research platform XNAT. J Med Syst, 2020, 44(8): 137.
25. 李雪迎, 姚晨, 晋菲斐, 等. 面向真实世界数据的临床研究数据治理模式选择. 中国循证医学杂志, 2020, 20(10): 1150-1156.
26. 国务院办公厅. 关于促进和规范健康医疗大数据应用发展的指导意见, 2016. Available at: http://www.gov.cn/zhengce/content/2016-06/24/content_5085091.htm#.
27. Foundation O. What is openEHR? 2021. Available at:https://www.openehr.org/about/what_is_openehr.
28. Wulff A, Mast M, Hassler M, et al. Designing an openEHR-based pipeline for extracting and standardizing unstructured clinical data using natural language processing. Methods Inf Med, 2020, 59(S02): e64-e78.
29. 国家卫生计生委. 卫生信息共享文档编制规范, 2016. Available at:http://www.nhc.gov.cn/wjw/s9497/201607/f1472d0f82bf48ebb8da4ffe5000e0aa.shtml.
30. CDISC Submission Data Standards Team. Study data tabulation model implementation guide: human clinical trials version 3.3 (final), 2018. Available at: http://www.sastricks.com/cdisc/SDTMIG_v3.3_FINAL.pdf.
31. Riepenhausen S, Mertens C, Dugas M. Comparing SDTM and FHIR® for real world data from electronic health records for clinical trial submissions. Stud Health Technol Inform, 2021, 281: 585-589.
32. OMOP. Common data model, 2021. Available at: https://github.com/OHDSI/CommonDataModel.
33. 侯丽, 李露琪, 唐灵逸, 等. OHDSI通用数据模型及医学术语标准国内应用现状分析. 医学信息学杂志, 2020, 41(2): 1-10.
34. 阎小妍, 董冲亚, 姚晨. 保障中国临床试验数据的准确性. 英国医学杂志中文版, 2018, 21(11): 639-640.
35. 中国医院协会信息专业委员会. 医疗机构医疗大数据平台建设指南(征求意见稿). 北京: 中国工信出版集团, 2019.
36. 国家药品监督管理局. 深刻认识和准确把握“十四五”时期我国发展面临的外部环境, 2020. Available at: https://www.nmpa.gov.cn/zhuanti/bwchx/bwxxjl/20201218085425130.html.

Chinese Journal of Evidence-Based Medicine

Exploring the patterns of real-world data governance in the context of special healthcare policy

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content