Technical guidance for developing research databases using existing health and medical data_Chinese Journal of Evidence-Based Medicine

Authors：

 WANG Wen ¹ ^# , GAO Pei ² ^# , WU Jing ³ ^# , XUAN Jianwei ⁴ , HE Xiaoning ³ , HU Ming ⁵ , LI Hongchao ⁶ , DOU Fengman ⁷ , YU Chuan ⁸ , YAN Yingying ⁹ ,  SUN Xin ¹ , On behalf of China REal world data and studies ALliance (ChinaREAL)

1. Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu, 610041, P.R.China;
2. Department of Epidemiology and Biostatistics, Peking University Health Science Center, Beijing, 100191, P.R.China;
3. School of Pharmacology Science and Technology, Tianjin University, Tianjin, 300072, P.R.China;
4. Institute of Medical Eeconomics, Sun Yat-Sen University, Guangzhou, 510275, P.R.China;
5. Pharmaceutical Policy & Pharmacoeconomics Research Center, West China Hospital, School of Pharmacy, Sichuan University, Chengdu, 610041, P.R.China;
6. School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, 211198, P.R.China;
7. Chengdu Medical Information Institute, Chengdu, 610091, P.R.China;
8. West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, 610041, P.R.China;
9. Peking University Third Hospital, Beijing, 100191, P.R.China;

Corresponding author：

WANG Wen, Email: wangwen83@outlook.com; SUN Xin, Email: sunx79@hotmail.com

Keywords：

Real-world data; Existing health and medical data; Research database; Technical guidance

DOI：

10.7507/1672-2531.201904160

Video：

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Abstract Full text Figures/Tables Video References Cited by

As an important source for real-world data, existing health and medical data have gained wide attentions recently. As the first part of the serial technical guidance for real-world data and studies, this report introduced the concepts, features and potential applications of existing medical and health data, proposed recommendations for planning and developing a research database using existing health and medical data, and developed essential indicators for assessing the quality of such research databases. The technical guidance may standardize and improve the development of research database using existing health and medical data in China.

Citation： WANG Wen, GAO Pei, WU Jing, XUAN Jianwei, HE Xiaoning, HU Ming, LI Hongchao, DOU Fengman, YU Chuan, YAN Yingying, SUN Xin, On behalf of China REal world data and studies ALliance (ChinaREAL). Technical guidance for developing research databases using existing health and medical data. Chinese Journal of Evidence-Based Medicine, 2019, 19(7): 763-770. doi: 10.7507/1672-2531.201904160 Copy

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5.	Berger ML, Mamdani M, Atkins D, et al. Good research practices for comparative effectiveness research: defining, reporting and interpreting nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report-Part I. Value Health, 2009, 12(8): 1044-1052.
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8.	Herrett E, Gallagher AM, Bhaskaran K, et al. Data resource profile: clinical practice research datalink (CPRD). Int J Epidemiol, 2015, 44(3): 827-836.
9.	Jordan KP, Timmis A, Croft P, et al. Prognosis of undiagnosed chest pain: linked electronic health record cohort study. BMJ, 2017, 357: j1194.
10.	王雯, 谭婧, 于川, 等. 基于中国医院电子病历数据的药品安全性评价模式探索. 中国药物警戒, 2019, 16(3): 134-138.
11.	Benchimol EI, Manuel DG, To T, et al. Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data. J Clin Epidemiol, 2011, 64(8): 821-829.
12.	李洪, 魏来, 郭晓蕙, 等. 真实世界研究伦理审查初探. 中国循证医学杂志, 2018, 18(11): 1198-1202.
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14.	Peduzzi P, Concato J, Kemper E, et al. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol, 1996, 49(12): 1373-1379.

1. Benchimol EI, Smeeth L, Guttmann A, et al. The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. PLoS Med, 2015, 12(10): e1001885.
2. Sun X, Tan J, Tang L, et al. Real world evidence: experience and lessons from China. BMJ, 2018, 360: j5262.
3. 王雯, 刘艳梅, 谭婧, 等. 回顾性数据库研究的概念、策划与研究数据库构建. 中国循证医学杂志, 2018, 18(2): 230-237.
4. U. S. Food & Drug Administration. Best Practices for Conducting and Reporting Pharmacoepidemiologic Safety Studies Using Electronic Healthcare Data. Available at: https://wwwfdagov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm243537pdf.
5. Berger ML, Mamdani M, Atkins D, et al. Good research practices for comparative effectiveness research: defining, reporting and interpreting nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report-Part I. Value Health, 2009, 12(8): 1044-1052.
6. Cox E, Martin BC, Van Staa T, et al. Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report--Part II. Value Health, 2009, 12(8): 1053-1061.
7. Johnson ML, Crown W, Martin BC, et al. Good research practices for comparative effectiveness research: analytic methods to improve causal inference from nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report-Part III. Value Health, 2009, 12(8): 1062-1073.
8. Herrett E, Gallagher AM, Bhaskaran K, et al. Data resource profile: clinical practice research datalink (CPRD). Int J Epidemiol, 2015, 44(3): 827-836.
9. Jordan KP, Timmis A, Croft P, et al. Prognosis of undiagnosed chest pain: linked electronic health record cohort study. BMJ, 2017, 357: j1194.
10. 王雯, 谭婧, 于川, 等. 基于中国医院电子病历数据的药品安全性评价模式探索. 中国药物警戒, 2019, 16(3): 134-138.
11. Benchimol EI, Manuel DG, To T, et al. Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data. J Clin Epidemiol, 2011, 64(8): 821-829.
12. 李洪, 魏来, 郭晓蕙, 等. 真实世界研究伦理审查初探. 中国循证医学杂志, 2018, 18(11): 1198-1202.
13. van Walraven C, English S, Austin PC. Administrative database code accuracy did not vary notably with changes in disease prevalence. J Clin Epidemiol, 2016, 79: 86-89.
14. Peduzzi P, Concato J, Kemper E, et al. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol, 1996, 49(12): 1373-1379.

Chinese Journal of Evidence-Based Medicine

Technical guidance for developing research databases using existing health and medical data

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