The reporting of studies conducted using observational routinely-collected health data (RECORD) statement_Chinese Journal of Evidence-Based Medicine

Authors：

Translated by: NIE Xiaolu ,  PENG Xiaoxia , 译

Clinical Epidemjology & Evidence-based Medicine Center, Beijing Children's Hospital, Capital Medical University, Beijing, 100045, P. R. China;

Corresponding author：

PENG Xiaoxia, Email: pengxiaoxia@bch.com.cn

Keywords：

RECORD 规范; 指南

DOI：

10.7507/1672-2531.201702009

Video：

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Abstract Full text Figures/Tables Video References Cited by

常规收集卫生数据是指基于管理和临床目的且事先没有特定研究目标而收集的数据，已被越来越多地用于研究。此类数据发展迅速，可及性好，但相关注意事项并未在现有的报告规范中被提及，如加强观察性流行病学研究报告的声明（strengthening the reporting of observational studies in epidemiology statement，STROBE）。使用常规收集卫生数据开展观察性研究的报告规范（the report of studies conducted using observational routinely collected data，RECORD）可填补该空缺。RECORD 规范是 STROBE 规范扩展版，其可用来提出针对使用常规收集卫生数据开展观察性研究有关报告的条件要求。RECORD 清单扩展了包括题目、摘要、前言、方法、结果、讨论和其他内容等需要在此类研究报告中包含的 13 个条目内容。该规范包括了清单、详尽的解释性信息以提高清单的使用。该规范还给出每条 RECORD 清单条目良好的报告实例。本文及其官网和留言板（http://www.record-statement.org）可提高 REDORD 规范的应用和理解。通过应用 RECORD，作者、期刊编辑和同行评议者可促进研究报告的质量。

Citation： Translated by: NIE Xiaolu, PENG Xiaoxia. The reporting of studies conducted using observational routinely-collected health data (RECORD) statement. Chinese Journal of Evidence-Based Medicine, 2017, 17(4): 475-487. doi: 10.7507/1672-2531.201702009 Copy

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2. Morrato EH, Elias M, Gericke CA. Using population-based routine data for evidence-based health policy decisions: lessons from three examples of setting and evaluating national health policy in Australia, the UK and the USA. J Public Health, 2007, 29(4): 463-471.
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5. 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.
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25. Prokosch HU, Ganslandt T. Perspectives for medical informatics. Reusing the electronic medical record for clinical research. Methods Inf Med, 2009, 48(1): 38-44.
26. Benchimol EI, Manuel DG, Guttmann A,et al. Changing age demographics of inflammatory bowel disease in ontario, canada: a population-based cohort study of epidemiology trends. Inflamm Bowel Dis, 2014, 20(10): 1761-1769.
27. Ducharme R, Benchimol EI, Deeks SL,et al. Validation of diagnostic codes for intussusception and quantification of childhood intussusception incidence in ontario, Canada: a population-based study. J Pediatr, 2013, 163(4): 1073-1079.
28. Herrett E, Shah AD, Boggon R,et al. Completeness and diagnostic validity of recording acute myocardial infarction events in primary care, hospital care, disease registry, and national mortality records: cohort study. BMJ, 2013, 346: f2350.
29. van Herk-Sukel MP, van de Poll-Franse LV, Lemmens VE,et al. New opportunities for drug outcomes research in cancer patients: the linkage of the Eindhoven Cancer Registry and the PHARMO Record Linkage System. Eur J Cancer, 2010, 46(2): 395-404.
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40. Shahian DM, Wolf RE, Iezzoni LI,et al. Variability in the measurement of hospital-wide mortality rates. N Engl J Med, 2010, 363(26): 2530-2539.
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42. Dommett RM, Redaniel MT, Stevens MC,et al. Features of childhood cancer in primary care: a population-based nested case-control study. Br J Cancer, 2012, 106(5): 982-987.
43. Tsang C, Bottle A, Majeed A,et al. Adverse events recorded in English primary care: observational study using the General Practice Research Database. Br J Gen Pract, 2013, 63(613): e534-42.
44. Harron K, Goldstein H, Wade A,et al. Linkage, evaluation and analysis of national electronic healthcare data: application to providing enhanced blood-stream infection surveillance in paediatric intensive care. PLOS One, 2013, 8(12): e85278.
45. Adams MM, Wilson HG, Casto DL,et al. Constructing reproductive histories by linking vital records. Am J Epidemiol, 1997, 145(4): 339-348.
46. Ford JB, Roberts CL, Taylor LK. Characteristics of unmatched maternal and baby records in linked birth records and hospital discharge data. Paediatr Perinat Epidemiol, 2006, 20(4): 329-337.
47. Weiskopf NG, Weng C. Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research. J Am Med Inform Assoc, 2013, 20(1): 144-151.
48. Sandall J, Murrells T, Dodwell M,et al. The efficient use of the maternity workforce and the implications for safety and quality in maternity care: a population-based, cross-sectional study. Health Serv Deliv Res, 2014, 2: 38. Available at: .
49. Welch C, Petersen I, Walters K,et al. Two-stage method to remove population- and individual-level outliers from longitudinal data in a primary care database. Pharmacoepidemiol Drug Saf, 2012, 21(7): 725-732.
50. Van den Broeck J, Cunningham SA, Eeckels R,et al. Data cleaning: detecting, diagnosing, and editing data abnormalities. PLOS Med, 2005, 2(10): e267.
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