The selection of data governance model of clinical study based on real-world data_Chinese Journal of Evidence-Based Medicine

Authors：

 LI Xueying ¹ , SHA Ruoqi ² ,  YAO Chen ^1,3 , JIN Feifei ¹ , WANG Xicheng ⁴ , YAN Xiaoyan ³ , ZHU Sainan ¹ , SHANG Meixia ¹

1. Department of Biostatistics, Peking University First Hospital, Beijing 100034, P.R.China;
2. Data Governance Center, Baoshang Bank, Beijing 100101, P.R.China;
3. Peking University Clinical Research Institute, Beijing 100191, P.R.China;
4. Beijing Dublin International Collage, Beijing University of Technology, Beijing 100124, P.R.China;

Corresponding?author：

LI Xueying, Email: xyinglee@163.com; YAO Chen, Email: yaochen@hsc.pku.edu.cn

Keywords：

Data governance; Clinical study; Real-world data; Source data

DOI：

10.7507/1672-2531.202003122

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

Objectives To establish an appropriate data governance mode in according with the database status of clinical study.Methods Forty-six doctors of different seniority with clinical research experience from six hospitals in Beijing were selected by stratified purposeful sampling and semi-structured interview and were used to understand the status and shortcomings of data acquisition and storage in clinical research. The data resource of current clinical studies were summarized and the main target of data governance and the characteristics of clinical study data were explored to establish the domains of clinical study data governance to construct the framework of clinical research data governance.Results Currently, the data sources of clinical studies were diverse, including real-world data from various medical and health records, data collected independently for clinical studies and numerous other sources. However, since collecting the data from electronic medical records was difficult for numerous reasons, a large number of researchers still collected research data by hand writing and stored it insecurely. In addition, the combination of electronic information from multiple sources was difficult. Building ALCOA+CCEA standard clinical research data management system based on clinical research data governance was urgent. Data governance includes data architecture, data model, data standards, data quality, master data, timeliness management, metadata and data security, while life cycle management and data insight were not essential parts.Conclusions Based on the real-world data resources, domains of data governance in clinical study should include data architecture, data model, data standards, data quality, master data, timeliness management, metadata and data security.

Citation： LI Xueying, SHA Ruoqi, YAO Chen, JIN Feifei, WANG Xicheng, YAN Xiaoyan, ZHU Sainan, SHANG Meixia. The selection of data governance model of clinical study based on real-world data. Chinese Journal of Evidence-Based Medicine, 2020, 20(10): 1150-1156. doi: 10.7507/1672-2531.202003122 Copy

1.	董沖亞, 閻小妍, 姚亮, 等. 規范多中心臨床試驗勢在必行. 中國循證醫學雜志, 2018, 18(7): 654-656.
2.	孫鑫, 譚婧, 王雯, 等. 真實世界證據助推藥械評價與監管決策. 中國循證醫學雜志, 2019, 19(5): 521-526.
3.	黃亞芳, 閻小妍, 李雪迎, 等. 真實世界證據在醫療器械臨床研究中的應用. 中國循證醫學雜志, 2017, 17(12): 1373-1377.
4.	孫鑫, 譚婧, 唐立, 等. 基于真實世界證據的上市后藥品評價技術框架體系: 思考與建議. 中國循證醫學雜志, 2018, 18(4): 277-283.
5.	中華人民共和國國家質量監督檢驗檢疫總局, 中國國家標準化管理委員會. 數據管理能力成熟度評估模型. Available from: http://openstd.samr.gov.cn/bzgk/gb/newGbInfo?hcno=B282A7BD34CAA6E2D742E0CAB7587DBC.
6.	吳泰相, 卞兆祥, 李幼平, 等. 促進我國臨床試驗數據管理規范化. 中國循證醫學雜志, 2018, 18(6): 532-537.
7.	孫鑫, 譚婧, 王雯, 等. 建立真實世界數據與研究技術規范, 促進中國真實世界證據的產生與使用. 中國循證醫學雜志, 2019, 19(7): 755-762.
8.	U.S. Food and Drug Administration. Guidance for industry computerized systems used in clinical investigations. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/computerized-systems-used-clinical-investigations.
9.	國家藥品監督管理局. 臨床試驗數據管理工作技術指南. Available from: http://www.nmpa.gov.cn/WS04/CL2138/300192.html.
10.	U.S. Food and Drug Administration. Electronic source data in clinical investigations. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/electronic-source-data-clinical-investigations.
11.	The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). Integrated Addendum to ICH E6 (R1): Guideline for Good Clinical Practice (R2). Available from: https://database.ich.org/sites/default/files/E6_R2_Addendum.pdf.
12.	Abraham R, Schneider J, Brocke J. Data governance: a conceptual framework, structured review, and research agenda. Int J Inf Manage, 2019, 49: 424-438.
13.	國家市場監督管理總局, 中國國家標準化管理委員會. 信息技術服務治理第 5 部分: 數據治理規范. Available from: http://openstd.samr.gov.cn/bzgk/gb/newGbInfo?hcno=F3B2108863A2292F5AF0FA645CEE047F.
14.	International Organization for Standardization. Information technology-governance of IT-governance of data-part 1: application of ISO/IEC 38500 to the governance of data ISO/IEC 38505-1: 2017. Available from: https://www.iso.org/standard/56639.html.
15.	The Global Data Management Community. Guide to the data management body of knowledge (DAMA-DMBOK) 2009 functional framework v.3. Available from: https://damadach.org/dama-dmbok-functional-framework/.
16.	胡建平. 醫院數據治理框架、技術和實現. 北京: 人民衛生出版社, 2019.
17.	Wang CS, Lin SL, Chou TH, et a1. An integrated data analytics process to optimize data governance of nonprofit organization. Comput Hum Behav, 2019, 101(12): 495-505.
18.	安小米, 王麗麗. 大數據治理體系構建方法框架研究. 圖書情報工作, 2019, 63(24): 43-51.
19.	Sherman RE, Anderson SA, Dal Pan GJ, et al. Real-world evidence - what is it and what can it tell us? N Engl J Med, 2016, 375(23): 2293-2297.
20.	彭曉霞, 舒嘯塵, 譚婧, 等. 基于真實世界數據評價治療解決的觀察性研究設計技術規范. 中國循證醫學雜志, 2019, 19(7): 779-786.
21.	高培, 王楊, 羅劍鋒, 等. 基于真實世界數據評價治療結局研究的統計分析技術規范. 中國循證醫學雜志, 2019, 19(7): 787-793.
22.	聶曉璐, 武澤昊, 趙厚宇, 等. 使用常規收集醫療衛生數據開展觀察性研究的報告規范(藥物流行病學版)RECORD-PE 規范中文版(上). 藥物流行病學雜志, 2019, 28(3): 190-198, 212.
23.	董沖亞, 姚晨, 高嵩, 等. 加強醫院臨床研究源數據管理, 提高我國臨床研究數據質量. 中國循證醫學雜志, 2019, 19(11): 1255-1261.
24.	曹敏, 張來運, 王鶴, 等. 直腸癌 CT 結構式報告的臨床應用研究. 放射學實踐, 2016, 31(12): 1146-1150.
25.	盧淑祺, 竇志成, 文繼榮. 手術病例中結構化數據抽取研究. 計算機學報, 2019, 42(12): 2754-2768.

1. 董沖亞, 閻小妍, 姚亮, 等. 規范多中心臨床試驗勢在必行. 中國循證醫學雜志, 2018, 18(7): 654-656.
2. 孫鑫, 譚婧, 王雯, 等. 真實世界證據助推藥械評價與監管決策. 中國循證醫學雜志, 2019, 19(5): 521-526.
3. 黃亞芳, 閻小妍, 李雪迎, 等. 真實世界證據在醫療器械臨床研究中的應用. 中國循證醫學雜志, 2017, 17(12): 1373-1377.
4. 孫鑫, 譚婧, 唐立, 等. 基于真實世界證據的上市后藥品評價技術框架體系: 思考與建議. 中國循證醫學雜志, 2018, 18(4): 277-283.
5. 中華人民共和國國家質量監督檢驗檢疫總局, 中國國家標準化管理委員會. 數據管理能力成熟度評估模型. Available from: http://openstd.samr.gov.cn/bzgk/gb/newGbInfo?hcno=B282A7BD34CAA6E2D742E0CAB7587DBC.
6. 吳泰相, 卞兆祥, 李幼平, 等. 促進我國臨床試驗數據管理規范化. 中國循證醫學雜志, 2018, 18(6): 532-537.
7. 孫鑫, 譚婧, 王雯, 等. 建立真實世界數據與研究技術規范, 促進中國真實世界證據的產生與使用. 中國循證醫學雜志, 2019, 19(7): 755-762.
8. U.S. Food and Drug Administration. Guidance for industry computerized systems used in clinical investigations. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/computerized-systems-used-clinical-investigations.
9. 國家藥品監督管理局. 臨床試驗數據管理工作技術指南. Available from: http://www.nmpa.gov.cn/WS04/CL2138/300192.html.
10. U.S. Food and Drug Administration. Electronic source data in clinical investigations. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/electronic-source-data-clinical-investigations.
11. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). Integrated Addendum to ICH E6 (R1): Guideline for Good Clinical Practice (R2). Available from: https://database.ich.org/sites/default/files/E6_R2_Addendum.pdf.
12. Abraham R, Schneider J, Brocke J. Data governance: a conceptual framework, structured review, and research agenda. Int J Inf Manage, 2019, 49: 424-438.
13. 國家市場監督管理總局, 中國國家標準化管理委員會. 信息技術服務治理第 5 部分: 數據治理規范. Available from: http://openstd.samr.gov.cn/bzgk/gb/newGbInfo?hcno=F3B2108863A2292F5AF0FA645CEE047F.
14. International Organization for Standardization. Information technology-governance of IT-governance of data-part 1: application of ISO/IEC 38500 to the governance of data ISO/IEC 38505-1: 2017. Available from: https://www.iso.org/standard/56639.html.
15. The Global Data Management Community. Guide to the data management body of knowledge (DAMA-DMBOK) 2009 functional framework v.3. Available from: https://damadach.org/dama-dmbok-functional-framework/.
16. 胡建平. 醫院數據治理框架、技術和實現. 北京: 人民衛生出版社, 2019.
17. Wang CS, Lin SL, Chou TH, et a1. An integrated data analytics process to optimize data governance of nonprofit organization. Comput Hum Behav, 2019, 101(12): 495-505.
18. 安小米, 王麗麗. 大數據治理體系構建方法框架研究. 圖書情報工作, 2019, 63(24): 43-51.
19. Sherman RE, Anderson SA, Dal Pan GJ, et al. Real-world evidence - what is it and what can it tell us? N Engl J Med, 2016, 375(23): 2293-2297.
20. 彭曉霞, 舒嘯塵, 譚婧, 等. 基于真實世界數據評價治療解決的觀察性研究設計技術規范. 中國循證醫學雜志, 2019, 19(7): 779-786.
21. 高培, 王楊, 羅劍鋒, 等. 基于真實世界數據評價治療結局研究的統計分析技術規范. 中國循證醫學雜志, 2019, 19(7): 787-793.
22. 聶曉璐, 武澤昊, 趙厚宇, 等. 使用常規收集醫療衛生數據開展觀察性研究的報告規范(藥物流行病學版)RECORD-PE 規范中文版(上). 藥物流行病學雜志, 2019, 28(3): 190-198, 212.
23. 董沖亞, 姚晨, 高嵩, 等. 加強醫院臨床研究源數據管理, 提高我國臨床研究數據質量. 中國循證醫學雜志, 2019, 19(11): 1255-1261.
24. 曹敏, 張來運, 王鶴, 等. 直腸癌 CT 結構式報告的臨床應用研究. 放射學實踐, 2016, 31(12): 1146-1150.
25. 盧淑祺, 竇志成, 文繼榮. 手術病例中結構化數據抽取研究. 計算機學報, 2019, 42(12): 2754-2768.

Chinese Journal of Evidence-Based Medicine

The selection of data governance model of clinical study based on real-world data

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content