Strengthening clinical research source data management in hospitals to promote data quality of clinical research in China_Chinese Journal of Evidence-Based Medicine

Authors：

DONG Chongya ¹ ,  YAO Chen ^1,2 , GAO Song ³ , YAN Xiaoyan ² , JIN Feifei ¹ , ZHU Sainan ¹

1. Department of Biostatistics, Peking University First Hospital, Beijing, 100034, P.R.China;
2. Peking University Clinical Research Institute, Beijing, 100191, P.R.China;
3. Center of Information Management, Peking University First Hospital, Beijing, 100034, P.R.China;

Corresponding?author：

YAO Chen, Email: yaochen@hsc.pku.edu.cn

Keywords：

Clinical research; Source data; Data quality; Transparency; Electronic medical record; Electronic health record

DOI：

10.7507/1672-2531.201908047

Video：

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Data integrity, accuracy, and traceability are key elements of high-quality clinical research, as well as weak links in the promotion of clinical research transparency. How to promote data quality has become a major concern to all clinical research stakeholders. In this article, we dissected and analyzed data generation and capturing process in clinical research, and identified a key aspect in improving data quality: to promote electronic source data, especially to break the barrier between electronic health records and clinical research systems. Additionally, we summarized the experiences regarding this issue in China and overseas to propose a solution suitable for China to improve data quality in clinical research: to strengthen clinical research source data management by building clinical research source data platform and adopt common source data management process in hospitals.

Citation： DONG Chongya, YAO Chen, GAO Song, YAN Xiaoyan, JIN Feifei, ZHU Sainan. Strengthening clinical research source data management in hospitals to promote data quality of clinical research in China. Chinese Journal of Evidence-Based Medicine, 2019, 19(11): 1255-1261. doi: 10.7507/1672-2531.201908047 Copy

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1. National Institutes of Health. NIH clinical research trials and you. Available at: https://www.nih.gov/health-information/nih-clinical-research-trials-you.
2. 董沖亞, 楊莉, 韓鴻賓, 等. 深化臨床研究透明化理念加強對研究全過程的監督及管理. 中華醫學科研管理雜志, 2019, 32(2): 146-150.
3. Woodhead M. 80% of China's clinical trial data are fraudulent, investigation finds. BMJ, 2016, 355: i5396.
4. 胡金富, 史玉民. 國外學術期刊同行評審造假的分析及啟示-基于 2015 年三次大撤稿事件的分析. 中國科學基金, 2016, (6): 568-571.
5. U.S. Food and drug administration guidance for industry-electronic source data in clinical investigations. Available at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/electronic-source-data-clinical-investigations.
6. Society for Clinical Data Management The Good Clinical Data Management Practices (GCDMP). Available at: https://scdm.org/publications/gcdmp/.
7. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Efficacy Guidelines (E8)-General Considerations for Clinical Trials (R1). Available at: https://www.ich.org/products/guidelines/efficacy/article/efficacy-guidelines.html.
8. 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.
9. 孫鑫, 譚婧, 唐立, 等. 重新認識真實世界研究. 中國循證醫學雜志, 2017, 17(2): 126-130.
10. U.S. Food and Drug Administration Guidance for Industry - Computerized Systems Used in Clinical Investigations. Available at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/computerized-systems-used-clinical-investigations.
11. 國家食品藥品監管總局. 臨床試驗數據管理工作技術指南. Available at: http://samr.cfda.gov.cn/WS01/CL0087/160961.html.
12. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Efficacy Guidelines (E6)-Guideline for Good Clinical Practice (R2).Available at: https://www.ich.org/products/guidelines/efficacy/article/efficacy-guidelines.html.
13. Society for Clinical Data Management. eSource implementation in clinical research: a data management perspective. Available at: https://www.scdm.org/publications/white-papers/#.
14. Nosek BA, Alter G, Banks GC, et al. Scientific standards. Promoting an open research culture. Science, 2015, 348(6242): 1422-1425.
15. Altman DG, Moher D. Declaration of transparency for each research article. BMJ, 2013, 347: f4796.
16. Health Canada. Elements of real world data/evidence quality throughout the prescription drug product life cycle. Available at: https://www.canada.ca/en/services/health/publications/drugs-health-products/real-world-data-evidence-drug-lifecycle-report.html.
17. 國家藥品監督管理局藥品審評中心. 真實世界證據支持藥物研發的基本考慮(征求意見稿)中文版. Available at: http://www.cde.org.cn/news.do?method=viewInfoCommon&id=314865.
18. Yan X, Dong C, Yao C. Protecting the accuracy of clinical trial data in China. Available at: https://blogs.bmj.com/bmj/2018/06/07/protecting-the-accuracy-of-clinical-trial-data-in-china/.
19. The Office of the National Coordinator for Health Information Technology (ONC). About The ONC Health IT Certification Program. Available at: https://www.healthit.gov/topic/certification-ehrs/about-onc-health-it-certification-program.
20. U.S. Food and Drug Administration Guidance for Industry-Use of Electronic Health Record Data in Clinical Investigations. Available at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/use-electronic-health-record-data-clinical-investigations-guidance-industry.
21. De Moor G, Sundgren M, Kalra D, et al. Using electronic health records for clinical research: the case of the EHR4CR project. J Biomed Inform, 2015, 53: 162-173.
22. The European Institute for Innovation through Health Data (i-HD). From Electronic Health Records to Electronic Data Capture systems. Available at: https://www.i-hd.eu/index.cfm/services/research/ehr2edc/.
23. 王強, 易應萍. 臨床醫療大數據治理和應用. 醫學信息學雜志, 2018, 39(8): 1-6.
24. 國務院辦公廳關于促進和規范健康醫療大數據應用發展的指導意見. Available at: http://www.gov.cn/zhengce/content/2016-06/24/content_5085091.htm.

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