Concept and planning of retrospective database study and development of research database_Chinese Journal of Evidence-Based Medicine

Authors：

WANG Wen , LIU Yanmei , TAN Jing , YU Chuan , LI Jijie , CHENG Liangliang ,  SUN Xin

Chinese Evidence-based Medicine Center and CREAT Group, West China Hospital, Sichuan University, Chengdu, 610041, P.R.China;

Corresponding author：

SUN Xin, Email: sunx79@hotmail.com

Keywords：

DOI：

10.7507/1672-2531.201712085

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Retrospective database study is an important type of real world study that employ observational designs, which has received wide attention. However, misunderstandings and inappropriate conduct of retrospective database studies are very common. We systematically introduced the concept, features and applications of retrospective database study, as well as discussed the methods to plan a retrospective database study and how to develop a research database. This article is expected to offer guidance for the quality production and appropriate use of retrospective database study.

Citation： WANG Wen, LIU Yanmei, TAN Jing, YU Chuan, LI Jijie, CHENG Liangliang, SUN Xin. Concept and planning of retrospective database study and development of research database. Chinese Journal of Evidence-Based Medicine, 2018, 18(2): 230-237. doi: 10.7507/1672-2531.201712085 Copy

1.	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.
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10.	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.
11.	Sorensen HT, Sabroe S, Olsen J. A framework for evaluation of secondary data sources for epidemiological research. Int J Epidemiol, 1996, 25(2): 435-442.
12.	Gamble JM, Chibrikov E, Twells LK, et al. Association of insulin dosage with mortality or major adverse cardiovascular events: a retrospective cohort study. Lancet Diabetes Endocrinol, 2017, 5(1): 43-52.
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14.	Currie CJ, Peters JR, Tynan A, et al. Survival as a function of HbA1c in people with type 2 diabetes: a retrospective cohort study. Lancet, 2010, 375: 481-489.
15.	Dosunmu EO, Hatt SR, Leske DA, et al. Incidence and etiology of presumed fourth cranial nerve palsy: a population-based study. Am J Ophthalmol, 2017, 185(1): 110-114.
16.	Hess LM, Michael D, Mytelka DS, et al. Chemotherapy treatment patterns, costs, and outcomes of patients with gastric cancer in the United States: a retrospective analysis of electronic medical record (EMR) and administrative claims data. Gastric Cancer, 2016, 19(2): 607-615.
17.	Raccah D, Chou E, Colagiuri S, et al. A global study of the unmet need for glycemic control and predictor factors among patients with type 2 diabetes mellitus who have achieved optimal fasting plasma glucose control on basal insulin. Diabetes Metab Res Rev, 2017, 33(3): e2858.
18.	Lee J. Patient-specific predictive modeling using random forests: an observational study for the critically Ⅲ. JMIR Med Inform, 2017, 5(1): e3.
19.	李鹤, 夏苏建. 2006 年～2012 年广州市慢性髓系白血病参保患者医疗费用统计分析. 中国病案, 2014, 15(12): 44-46.
20.	Altman D, Frist WH. Medicare and Medicaid at 50 years: perspectives of beneficiaries, health care professionals and institutions, and policy makers. JAMA, 2015, 314(4): 384-395.
21.	Dore DD, Bloomgren GL, Wenten M, et al. A cohort study of acute pancreatitis in relation to exenatide use. Diabetes Obes Metab, 2011, 13(6): 559-566.
22.	Hsiao FY, Hsieh PH, Huang WF, et al. Risk of bladder cancer in diabetic patients treated with rosiglitazone or pioglitazone: a nested case-control study. Drug safety, 2013, 36(8): 643-649.
23.	Yu OH, Filion KB, Azoulay L, et al. Incretin-based drugs and the risk of congestive heart failure. Diabetes Care, 2015, 38(2): 277-284.
24.	Herrett E, Gallagher AM, Bhaskaran K, et al. Data resource profile: clinical practice research datalink (CPRD). Int J Epidemiol, 2015, 44(3): 827-836.
25.	Shu T, Liu H, Goss FR, et al. EHR adoption across China's tertiary hospitals: a cross-sectional observational study. Int J Med Inform, 2014, 83(2): 113-121.
26.	庞涛. 厦门模式-区域卫生信息化的实践蓝本. 中国信息界, 2013, 10: 117.
27.	黄晓琴, 林鸿波. 基于区域卫生信息平台的医疗卫生大数据研究. 中国卫生信息管理杂志, 2016, 16(6): 601-605.
28.	Wilson J. The benefit of using both claims data and electronic medical record data in health care analysis. Available at: https://wwwoptumcom/content/dam/optum/resources/whitePapers/Benefits-of-using-both-claims-and-EMR-data-in-HC-analysis-WhitePaper-ACSpdf.
29.	Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol, 2005, 58(4): 323-337.
30.	Wilchesky M, Tamblyn RM, Huang A. Validation of diagnostic codes within medical services claims. J Clin Epidemiol, 2004, 57(2): 131-141.
31.	Zhang Y, Chaisson CE, McAlindon T, et al. The online case-crossover study is a novel approach to study triggers for recurrent disease flares. J Clin Epidemiol, 2007, 60(1): 50-55.
32.	Schneeweiss S. Developments in post-marketing comparative effectiveness research. Clin Pharmacol Ther, 2007, 82(2): 143-156.

1. 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.
2. 唐立, 康德英, 喻佳洁, 等. 实效性随机对照试验: 真实世界研究的重要设计. 中国循证医学杂志, 2017, 17(7): 999-1004.
3. 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.
4. Chen YC, Wu JC, Haschler I, et al. Academic impact of a public electronic health database: bibliometric analysis of studies using the general practice research database. PLoS One, 2011, 6(6): e21404.
5. Chen YC, Yeh HY, Wu JC, et al. Taiwan’s National Health Insurance Research Database: administrative health care database as study object in bibliometrics. Scientometrics, 2010, 86(2): 365-380.
6. Motheral B, Brooks J, Clark MA, et al. A checklist for retrospective database studies--report of the ISPOR task force on retrospective databases. Value Health, 2003, 6(2): 90-97.
7. 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.
8. 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.
9. 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.
10. 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.
11. Sorensen HT, Sabroe S, Olsen J. A framework for evaluation of secondary data sources for epidemiological research. Int J Epidemiol, 1996, 25(2): 435-442.
12. Gamble JM, Chibrikov E, Twells LK, et al. Association of insulin dosage with mortality or major adverse cardiovascular events: a retrospective cohort study. Lancet Diabetes Endocrinol, 2017, 5(1): 43-52.
13. Singh S, Chang HY, Richards TM, et al. Glucagonlike peptide 1-based therapies and risk of hospitalization for acute pancreatitis in type 2 diabetes mellitus: a population-based matched case-control study. JAMA Intern Med, 2013, 173(7): 534-539.
14. Currie CJ, Peters JR, Tynan A, et al. Survival as a function of HbA1c in people with type 2 diabetes: a retrospective cohort study. Lancet, 2010, 375: 481-489.
15. Dosunmu EO, Hatt SR, Leske DA, et al. Incidence and etiology of presumed fourth cranial nerve palsy: a population-based study. Am J Ophthalmol, 2017, 185(1): 110-114.
16. Hess LM, Michael D, Mytelka DS, et al. Chemotherapy treatment patterns, costs, and outcomes of patients with gastric cancer in the United States: a retrospective analysis of electronic medical record (EMR) and administrative claims data. Gastric Cancer, 2016, 19(2): 607-615.
17. Raccah D, Chou E, Colagiuri S, et al. A global study of the unmet need for glycemic control and predictor factors among patients with type 2 diabetes mellitus who have achieved optimal fasting plasma glucose control on basal insulin. Diabetes Metab Res Rev, 2017, 33(3): e2858.
18. Lee J. Patient-specific predictive modeling using random forests: an observational study for the critically Ⅲ. JMIR Med Inform, 2017, 5(1): e3.
19. 李鹤, 夏苏建. 2006 年～2012 年广州市慢性髓系白血病参保患者医疗费用统计分析. 中国病案, 2014, 15(12): 44-46.
20. Altman D, Frist WH. Medicare and Medicaid at 50 years: perspectives of beneficiaries, health care professionals and institutions, and policy makers. JAMA, 2015, 314(4): 384-395.
21. Dore DD, Bloomgren GL, Wenten M, et al. A cohort study of acute pancreatitis in relation to exenatide use. Diabetes Obes Metab, 2011, 13(6): 559-566.
22. Hsiao FY, Hsieh PH, Huang WF, et al. Risk of bladder cancer in diabetic patients treated with rosiglitazone or pioglitazone: a nested case-control study. Drug safety, 2013, 36(8): 643-649.
23. Yu OH, Filion KB, Azoulay L, et al. Incretin-based drugs and the risk of congestive heart failure. Diabetes Care, 2015, 38(2): 277-284.
24. Herrett E, Gallagher AM, Bhaskaran K, et al. Data resource profile: clinical practice research datalink (CPRD). Int J Epidemiol, 2015, 44(3): 827-836.
25. Shu T, Liu H, Goss FR, et al. EHR adoption across China's tertiary hospitals: a cross-sectional observational study. Int J Med Inform, 2014, 83(2): 113-121.
26. 庞涛. 厦门模式-区域卫生信息化的实践蓝本. 中国信息界, 2013, 10: 117.
27. 黄晓琴, 林鸿波. 基于区域卫生信息平台的医疗卫生大数据研究. 中国卫生信息管理杂志, 2016, 16(6): 601-605.
28. Wilson J. The benefit of using both claims data and electronic medical record data in health care analysis. Available at: https://wwwoptumcom/content/dam/optum/resources/whitePapers/Benefits-of-using-both-claims-and-EMR-data-in-HC-analysis-WhitePaper-ACSpdf.
29. Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol, 2005, 58(4): 323-337.
30. Wilchesky M, Tamblyn RM, Huang A. Validation of diagnostic codes within medical services claims. J Clin Epidemiol, 2004, 57(2): 131-141.
31. Zhang Y, Chaisson CE, McAlindon T, et al. The online case-crossover study is a novel approach to study triggers for recurrent disease flares. J Clin Epidemiol, 2007, 60(1): 50-55.
32. Schneeweiss S. Developments in post-marketing comparative effectiveness research. Clin Pharmacol Ther, 2007, 82(2): 143-156.

Chinese Journal of Evidence-Based Medicine

Concept and planning of retrospective database study and development of research database

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