Transparent reporting of routinely-collected data studies is key to producing valid and reliable research that can inform decisions about patient care and health systems. This article discusses some of the unique challenges in using these data sources, and explains how the REporting of studies Conducted using Observational Routinely-collected Data (RECORD) guidelines were developed to help researchers and journals to maintain a high level of quality in reporting of healthcare studies using routinely-collected data

Benchimol, E

Harron, K

Langan, S

UCL Discovery

International Journal of Population Data Science (2018) 3:2International Journal ofPopulation Data ScienceJournal Website: www.ijpds.orgUsing the RECORD guidelines to improve transparent reporting of studies basedon routinely collected dataHarron, K1*, Benchimol, E2,3, and Langan, S4Submission HistorySubmitted: 14/09/2017Accepted: 14/12/2017Published: 24/01/20181Department of Health ServicesResearch and Policy, LondonSchool of Hygiene and TropicalMedicine2Department of Pediatrics andSchool of Epidemiology, PublicHealth and Preventive Medicine,University of Ottawa, Ottawa,Canada3Institute for Clinical EvaluativeSciences, Ottawa, Canada4Department of Non-communicable Disease Epi-demiology, London School ofHygiene & Tropical MedicineSummaryTransparent reporting of routinely-collected data studies is key to producing valid and reliableresearch that can inform decisions about patient care and health systems. This article discussessome of the unique challenges in using these data sources, and explains how the REporting of studiesConducted using Observational Routinely-collected Data (RECORD) guidelines were developed tohelp researchers and journals to maintain a high level of quality in reporting of healthcare studiesusing routinely-collected data.Routinely-collected data, i.e. individual-level records col-lected for financial, administrative, or clinical managementpurposes, contain rich, detailed information on patient path-ways, and their great potential for research and quality im-provement has been increasingly exploited internationally overrecent years1. The strengths of routinely-collected data andtheir value in health research are well established. However,researchers are faced with unique challenges when conduct-ing research with data sources that were collected for otherpurposes2. In particular, data quality is an ongoing concern- electronic clinical data do not always contain the complete,accurate information that researchers require. For example,consider a simple study comparing patients with and withoutdiabetes. If a patient is to be correctly classified as having dia-betes, we require that i) the clinician recognises the diagnosis,ii) the diagnosis is recorded in clinical notes, iii) the medicalcoders correctly code the diagnosis and iv) the researcher in-cludes the correct codes in their analysis. Omissions in any ofthese steps could lead to missing information. Missing datacan lead to bias - smoking and blood pressure may be im-portant confounders for diabetes, yet meaningful smoking sta-tus is rarely available in electronic clinical data unless thereare incentives for recording, and missingness in blood pres-sure measurements may be informative (e.g. data points aremore likely to be recorded in patients with high blood pres-sure values)3. Completeness of data may also be related toexternal factors such as financial incentives to code specificindicators or diseases4. The limitations of electronic clinicaldata and inherent challenges for analysis are well recognisedby researchers5. Transparency in reporting of these issues iskey to producing valid and reliable research, allowing thought-ful interpretation of findings, and enabling those working inpolicy to make informed decisions on patient care and healthsystems based on electronic data sources.Reporting guidelines such as CONSORT for clinical trialsand STROBE for observational studies aim to improve trans-parency, allowing identification of potential biases, critical as-sessments of robustness, and importantly, replication in dif-ferent settings6, 7. Many leading health journals now activelyendorse reporting guidelines, requiring authors to submit rel-evant checklists or referring authors to the EQUATOR (En-hancing the QUAlity and Transparency Of health Research)network website (www.equator-network.org) in their Instruc-tions to Authors. The EQUATOR network was established toimprove the reliability and usability of health research litera-ture by facilitating accurate and complete reporting of researchstudies8. Their website provides a comprehensive collection ofresources and reporting guidelines to support transparent pub-lication of research.Until recently, no guidelines adequately addressed theunique challenges of using routinely-collected data for re-search. To fill this gap, we proposed an extension to theSTROBE checklist, the guidelines for the REporting of stud-ies Conducted using Observational Routinely-collected Data∗Corresponding Author:Email Address: k.harron@ucl.ac.uk (K Harron)http://dx.doi.org/10.23889/ijpds.v3i1.419January 2018 c© The Authors. Open Access under CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en)Harron, K et. al. / International Journal of Population Data Science (2018) 3:2(RECORD)9. The RECORD initiative involved Delphi surveysof over 100 international stakeholders to prioritize themes,face-to-face meetings of a working committee to establishconsensus and wording, and feedback and review by stake-holders before the final checklist and explanatory documentwere produced10. RECORD aims to provide guidance for re-searchers, peer reviewers, journal editors and readers of stud-ies based on routinely-collected data. Our website (record-statement.org) provides access to the RECORD checklist andan explanatory document with examples of studies that reportin a transparent way. Translations are currently available inChinese, Japanese and German, and further translations arebeing developed. The website also contains a list of journalsthat have endorsed and implemented RECORD for submittedmanuscripts (including the International Journal of PopulationData Science). RECORD is particularly relevant for researcharticles submitted to the IJPDS, as it highlights specific issuesrelating to the use of routinely-collected data, including theuse of linkage between data sources, access and availability ofdata, and validation of codes or algorithms used to identifysubjects, exposures, outcomes or confounders.Whilst providing robust evidence on the impact of guide-lines on quality of reporting is not straightforward, it is clearthat these guidelines are a useful tool to help researchers gener-ate accurate and complete representations of their work11-13.However, due to the way in which routinely-collected dataare generated, extracted, and curated for analysis, with frag-mented processes often involving multiple organisations, re-searchers can find it challenging to obtain the information theyneed to fully report their research. This is particularly relevantfor data linkage studies for which trusted third parties are usedto link data from different sources. Datasets transferred to theresearcher for analysis are often limited in terms of metadataor information about the linkage process, making it difficult forresearchers to adhere to reporting guidelines14. To help ad-dress this issue, GUILD (Guidance for Information about Link-ing Datasets) recommends information that should be madeavailable at each step of the data linkage pathway (by dataproviders, linkers, analysts and those writing reports)15. Shar-ing of this information, whilst preserving data privacy, couldimprove reproducibility of research, and promote the increaseduse of methods to address linkage error16.As the use of population-level patient data continues toexpand, public perception on how and why these data are col-lected and used is becoming increasingly important, with themedia and the public being vocal about the need to understandthe purposes for which data are collected and used17. Theimpetus is on authors to maintain a high level of quality in re-porting of health research, yet journals also have an importantrole to play. Through encouraging responsible and completereporting of research using these data, journal endorsement ofthe RECORD checklist is an important step towards achievingthis goal, and we are pleased that the editors of IJPDS supportthis initiative. However, it is the joint responsibility of jour-nals, researchers and data providers to strive for a high levelof transparency, and to support the public in making informeddecisions about the use of their data, in order to continue ex-ploiting electronic health data for improving health and healthservices18.References1. Jutte DP, Roos L, Brownell MD. Administrative recordlinkage as a tool for public health research. Annu RevPublic Health. 2011. 32:91-108 https://doi.org/10.1146/annurev-publhealth-031210-1007002. Hashimoto RE, Brodt ED, Skelly AC, Dettori JR. Ad-ministrative database studies: goldmine or goose chase?Evid Based Spine Care J. 2014. 5(2):74-6 https://doi.org/10.1055/s-0034-13900273. Welch C, Bartlett J, Petersen I. Application of multipleimputation using the two-fold fully conditional specifi-cation algorithm in longitudinal clinical data. Stata J.2013.4. Smith CJP, Gribbin J, Challen KB, Hubbard RB. Theimpact of the 2004 NICE guideline and 2003 Gen-eral Medical Services contract on COPD in primarycare in the UK. QJM. 2008. 101(2):145-53 https://doi.org/10.1093/qjmed/hcm1555. van Walraven C, Austin P. Administrative database re-search has unique characteristics that can risk biasedresults. J Clin Epidemiol. 2012. 65(2):126-31 https://doi.org/10.1016/j.jclinepi.2011.08.0026. Altman DG, Schulz KF, Moher D, Egger M, DavidoffF, Elbourne D, et al. The revised CONSORT statementfor reporting randomized trials: explanation and elab-oration. Ann Intern Med. 2001. 134 https://doi.org/10.7326/0003-4819-134-8-200104170-000127. Elm Ev, Altman DG, Egger M, Pocock SJ, GøtzschePC, Vandenbroucke JP. Strengthening the reporting ofobservational studies in epidemiology (STROBE) state-ment: guidelines for reporting observational studies.BMJ. 2007. 335(7624):806-8 https://doi.org/10.1136/bmj.39335.541782.AD8. Simera I. Chapter 5.6: Reporting guidelines: a toolto increase completeness, transparency, and value ofhealth research published in your journal. In: SmartP, Maisonneuve H, Polderman A, editors. Science Ed-itors’ Handbook European Association of Science Edi-tors. www.ease.org.uk 2013.9. Nicholls SG, Quach P, von Elm E, Guttmann A, MoherD, Petersen I, et al. The REporting of Studies Con-ducted Using Observational Routinely-Collected HealthData (RECORD) Statement: Methods for Arriving atConsensus and Developing Reporting Guidelines. PLoSONE. 2015. 10(5):e0125620 https://doi.org/10.1371/journal.pone.012562010. The Plos Medicine Editors. From checklists to tools:Lowering the barrier to better research reporting. PLoSMed. 2015. 12(11):e1001910 https://doi.org/10.1371/journal.pmed.100191011. Turner L, Shamseer L, Altman DG, Weeks L, Peters J,Kober T, et al. Does the CONSORT Statement in-fluence the quality of reporting of RCTs published inmedical journals? Cochrane Database Syst Rev. 2012.1(60)2Harron, K et. al. / International Journal of Population Data Science (2018) 3:212. Moher D, Jones A, Lepage L. Use of the CONSORTstatement and quality of reports of randomized tri-als: a comparative before-and-after evaluation. JAMA.2001. 285(15):1992-5 https://doi.org/10.1001/jama.285.15.199213. Harron K, Wade A, Muller-Pebody B, Goldstein H,Gilbert R. Opening the black box of record linkage.J Epidemiol Commun H. 2012. 66(12):1198 https://doi.org/10.1136/jech-2012-20137614. Gilbert R, Lafferty R, Hagger-Johnson G, Harron K,Zhang L-C, Smith P, et al. GUILD: Guidance for Infor-mation about Linking Datasets. J Public Health. 2017.1-8 https://doi.org/10.1093/pubmed/fdx03715. Harron K, Doidge J, Knight H, Gilbert R, GoldsteinH, Cromwell D, et al. A guide to evaluating link-age quality for the analysis of linked data. Int J Epi-demiol. 2017. 46(5):1699-710 https://doi.org/10.1093/ije/dyx17716. Hoeksma J. The NHS’s care.data scheme: what are therisks to privacy? BMJ. 2014. 348 https://doi.org/10.1136/bmj.g154717. McGrail KM, Gutteridge K, Meagher NL. Buildingon Principles: The Case for Comprehensive, Propor-tionate Governance of Data Access. In: Gkoulalas-Divanis A, Loukides G, editors. Medical Data Pri-vacy Handbook. Cham: Springer International Publish-ing; 2015. p. 737-64. https://doi.org/10.1007/978-3-319-23633-9_28ReferencesKH is funded by the Wellcome Trust, grant number103975/Z/14/Z. The RECORD initiative is funded by theCanadian Institutes of Health Research (grant number130512), the Swiss National Science Foundation (grant num-ber IZ32Z0_147388/1), and the Aarhus University Depart-ment of Clinical Epidemiology.3

Using the RECORD guidelines to improve transparent reporting of studies based on routinely collected data

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Using the RECORD guidelines to improve transparent reporting of studies based on routinely collected data

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