{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T15:59:18Z","timestamp":1773849558403,"version":"3.50.1"},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T00:00:00Z","timestamp":1675814400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000092","name":"National Library of Medicine","doi-asserted-by":"publisher","award":["R21LM013645"],"award-info":[{"award-number":["R21LM013645"]}],"id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["L1TR003098"],"award-info":[{"award-number":["L1TR003098"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006093","name":"Patient-Centered Outcomes Research Institute","doi-asserted-by":"publisher","award":["AWD00005533-141011"],"award-info":[{"award-number":["AWD00005533-141011"]}],"id":[{"id":"10.13039\/100006093","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,4,19]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objectives<\/jats:title><jats:p>Collider bias is a common threat to internal validity in clinical research but is rarely mentioned in informatics education or literature. Conditioning on a collider, which is a variable that is the shared causal descendant of an exposure and outcome, may result in spurious associations between the exposure and outcome. Our objective is to introduce readers to collider bias and its corollaries in the retrospective analysis of electronic health record (EHR) data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Target audience<\/jats:title><jats:p>Collider bias is likely to arise in the reuse of EHR data, due to data-generating mechanisms and the nature of healthcare access and utilization in the United States. Therefore, this tutorial is aimed at informaticians and other EHR data consumers without a background in epidemiological methods or causal inference.<\/jats:p><\/jats:sec><jats:sec><jats:title>Scope<\/jats:title><jats:p>We focus specifically on problems that may arise from conditioning on forms of healthcare utilization, a common collider that is an implicit selection criterion when one reuses EHR data. Directed acyclic graphs (DAGs) are introduced as a tool for identifying potential sources of bias during study design and planning. References for additional resources on causal inference and DAG construction are provided.<\/jats:p><\/jats:sec>","DOI":"10.1093\/jamia\/ocad013","type":"journal-article","created":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T15:17:00Z","timestamp":1675869420000},"page":"971-977","source":"Crossref","is-referenced-by-count":33,"title":["Healthcare utilization is a collider: an introduction to collider bias in EHR data reuse"],"prefix":"10.1093","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0365-909X","authenticated-orcid":false,"given":"Nicole G","family":"Weiskopf","sequence":"first","affiliation":[{"name":"Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University , Portland, Oregon, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2318-7261","authenticated-orcid":false,"given":"David A","family":"Dorr","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University , Portland, Oregon, USA"}]},{"given":"Christie","family":"Jackson","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University , Portland, Oregon, USA"}]},{"given":"Harold P","family":"Lehmann","sequence":"additional","affiliation":[{"name":"Division of Health Science Informatics, Department of Medicine, Johns Hopkins University School of Medicine , Baltimore, Maryland, USA"}]},{"given":"Caroline A","family":"Thompson","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina, USA"},{"name":"Division of Cancer Epidemiology, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina, USA"}]}],"member":"286","published-online":{"date-parts":[[2023,2,8]]},"reference":[{"key":"2023041909002648700_ocad013-B1","doi-asserted-by":"crossref","first-page":"103822","DOI":"10.1016\/j.jbi.2021.103822","article-title":"Clinical comparison between trial participants and potentially eligible patients using electronic health record data: a generalizability assessment method","volume":"119","author":"Rogers","year":"2021","journal-title":"J Biomed Inform"},{"key":"2023041909002648700_ocad013-B2","first-page":"1472","article-title":"Sick patients have more data: the non-random completeness of electronic health records","volume":"2013","author":"Weiskopf","year":"2013","journal-title":"AMIA Annu Symp Proc"},{"key":"2023041909002648700_ocad013-B3","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1186\/1472-6947-14-51","article-title":"Hidden in plain sight: bias towards sick patients when sampling patients with sufficient electronic health record data for research","volume":"14","author":"Rusanov","year":"2014","journal-title":"BMC Med Inform Decis Mak"},{"issue":"6","key":"2023041909002648700_ocad013-B4","doi-asserted-by":"crossref","first-page":"1134","DOI":"10.1093\/jamia\/ocx071","article-title":"Biases introduced by filtering electronic health records for patients with \u201ccomplete data\u201d","volume":"24","author":"Weber","year":"2017","journal-title":"J Am Med Inform Assoc"},{"issue":"05","key":"2023041909002648700_ocad013-B5","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1017\/S1463423615000596","article-title":"Exploring practical approaches to maximising data quality in electronic healthcare records in the primary care setting and associated benefits. Report of panel-led discussion held at SAPC in July 2014","volume":"17","author":"Dungey","year":"2016","journal-title":"Prim Health Care Res Dev"},{"issue":"1","key":"2023041909002648700_ocad013-B6","doi-asserted-by":"crossref","first-page":"e10293","DOI":"10.1002\/lrh2.10293","article-title":"Developing real-world evidence from real-world data: Transforming raw data into analytical datasets","volume":"6","author":"Bastarache","year":"2022","journal-title":"Learn Health Syst"},{"issue":"1","key":"2023041909002648700_ocad013-B7","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1186\/s12911-022-01830-9","article-title":"Identifying primary care datasets and perspectives on their secondary use: a survey of Australian data users and custodians","volume":"22","author":"Canaway","year":"2022","journal-title":"BMC Med Inform Decis Mak"},{"issue":"6","key":"2023041909002648700_ocad013-B8","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1016\/j.puhe.2015.04.001","article-title":"Exposing some important barriers to health care access in the rural USA","volume":"129","author":"Douthit","year":"2015","journal-title":"Public Health"},{"issue":"5","key":"2023041909002648700_ocad013-B9","doi-asserted-by":"crossref","first-page":"976","DOI":"10.1007\/s10900-013-9681-1","article-title":"Traveling towards disease: transportation barriers to health care access","volume":"38","author":"Syed","year":"2013","journal-title":"J Community Health"},{"issue":"32","key":"2023041909002648700_ocad013-B10","doi-asserted-by":"crossref","first-page":"882","DOI":"10.15585\/mmwr.mm6732a3","article-title":"Prevalence of disabilities and health care access by disability status and type among adults\u2014United States, 2016","volume":"67","author":"Okoro","year":"2018","journal-title":"MMWR Morb Mortal Wkly Rep"},{"issue":"3","key":"2023041909002648700_ocad013-B11","doi-asserted-by":"crossref","first-page":"47","DOI":"10.2307\/3002000","article-title":"Limitations of the application of fourfold table analysis to hospital data","volume":"2","author":"Berkson","year":"1946","journal-title":"Biometrics"},{"issue":"1","key":"2023041909002648700_ocad013-B12","doi-asserted-by":"crossref","first-page":"5749","DOI":"10.1038\/s41467-020-19478-2","article-title":"Collider bias undermines our understanding of COVID-19 disease risk and severity","volume":"11","author":"Griffith","year":"2020","journal-title":"Nat Commun"},{"issue":"6","key":"2023041909002648700_ocad013-B13","first-page":"1887","article-title":"Robust causal inference using directed acyclic graphs: the R package 'dagitty","volume":"45","author":"Textor","year":"2016","journal-title":"Int J Epidemiol"},{"issue":"3","key":"2023041909002648700_ocad013-B14","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1111\/resp.12238","article-title":"Introduction to causal diagrams for confounder selection","volume":"19","author":"Williamson","year":"2014","journal-title":"Respirology"},{"issue":"1","key":"2023041909002648700_ocad013-B15","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1097\/00001648-199901000-00008","article-title":"Causal diagrams for epidemiologic research","volume":"10","author":"Greenland","year":"1999","journal-title":"Epidemiology"},{"key":"2023041909002648700_ocad013-B16","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1186\/1471-2288-8-70","article-title":"Reducing bias through directed acyclic graphs","volume":"8","author":"Shrier","year":"2008","journal-title":"BMC Med Res Methodol"},{"issue":"9","key":"2023041909002648700_ocad013-B17","doi-asserted-by":"crossref","first-page":"1418","DOI":"10.1093\/ndt\/gfu325","article-title":"Graphical presentation of confounding in directed acyclic graphs","volume":"30","author":"Suttorp","year":"2015","journal-title":"Nephrol Dial Transplant"},{"key":"2023041909002648700_ocad013-B18","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.jclinepi.2021.08.001","article-title":"Tutorial on directed acyclic graphs","volume":"142","author":"Digitale","year":"2022","journal-title":"J Clin Epidemiol"},{"key":"2023041909002648700_ocad013-B19","first-page":"393","volume-title":"Methods in Social Epidemiology","author":"Glymour","year":"2006"},{"issue":"4","key":"2023041909002648700_ocad013-B20","doi-asserted-by":"crossref","first-page":"433","DOI":"10.2217\/ijr.13.45","article-title":"Occurrence of gout in rheumatoid arthritis: it does happen! A population-based study","volume":"8","author":"Jebakumar","year":"2013","journal-title":"Int J Clin Rheumtol"},{"issue":"3","key":"2023041909002648700_ocad013-B21","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1007\/s10067-016-3477-5","article-title":"Comorbidity of gout and rheumatoid arthritis in a large population database","volume":"36","author":"Merdler-Rabinowicz","year":"2017","journal-title":"Clin Rheumatol"},{"issue":"1","key":"2023041909002648700_ocad013-B22","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1136\/emj.20.1.54","article-title":"Observational research methods. Research design II: cohort, cross sectional, and case-control studies","volume":"20","author":"Mann","year":"2003","journal-title":"Emerg Med J"},{"issue":"1","key":"2023041909002648700_ocad013-B23","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1093\/ije\/dyp174","article-title":"How to assess the external validity of therapeutic trials: a conceptual approach","volume":"39","author":"Dekkers","year":"2010","journal-title":"Int J Epidemiol"},{"key":"2023041909002648700_ocad013-B24","first-page":"89","article-title":"Characterization of the biomedical query mediation process","volume":"2013","author":"Hruby","year":"2013","journal-title":"AMIA Jt Summits Transl Sci Proc"},{"issue":"2","key":"2023041909002648700_ocad013-B25","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1136\/amiajnl-2013-001935","article-title":"A review of approaches to identifying patient phenotype cohorts using electronic health records","volume":"21","author":"Shivade","year":"2014","journal-title":"J Am Med Inform Assoc"},{"issue":"3","key":"2023041909002648700_ocad013-B26","doi-asserted-by":"crossref","first-page":"794","DOI":"10.4338\/ACI-2016-12-RA-0210","article-title":"Comparison of EHR-based diagnosis documentation locations to a gold standard for risk stratification in patients with multiple chronic conditions","volume":"8","author":"Martin","year":"2017","journal-title":"Appl Clin Inform"},{"key":"2023041909002648700_ocad013-B27","first-page":"903","article-title":"Towards augmenting structured EHR data: a comparison of manual chart review and patient self-report","volume":"2019","author":"Weiskopf","year":"2019","journal-title":"AMIA Annu Symp Proc"},{"issue":"10","key":"2023041909002648700_ocad013-B28","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1016\/j.ijmedinf.2015.06.011","article-title":"Problem list completeness in electronic health records: a multi-site study and assessment of success factors","volume":"84","author":"Wright","year":"2015","journal-title":"Int J Med Inform"},{"key":"2023041909002648700_ocad013-B29","doi-asserted-by":"crossref","first-page":"211","DOI":"10.2147\/JMDH.S104807","article-title":"Information bias in health research: definition, pitfalls, and adjustment methods","volume":"9","author":"Althubaiti","year":"2016","journal-title":"J Multidiscip Healthc"},{"issue":"4","key":"2023041909002648700_ocad013-B30","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1007\/s10067-019-04868-9","article-title":"Recent updates on worldwide gout epidemiology","volume":"39","author":"Mattiuzzi","year":"2020","journal-title":"Clin Rheumatol"},{"issue":"5","key":"2023041909002648700_ocad013-B31","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1097\/01.ede.0000135174.63482.43","article-title":"A structural approach to selection bias","volume":"15","author":"Hernan","year":"2004","journal-title":"Epidemiology"},{"issue":"4","key":"2023041909002648700_ocad013-B32","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1111\/aogs.13319","article-title":"How to investigate and adjust for selection bias in cohort studies","volume":"97","author":"Nohr","year":"2018","journal-title":"Acta Obstet Gynecol Scand"},{"issue":"3","key":"2023041909002648700_ocad013-B33","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1001\/jamainternmed.2019.6282","article-title":"Characteristics of Americans with primary care and changes over time, 2002-2015","volume":"180","author":"Levine","year":"2020","journal-title":"JAMA Intern Med"},{"issue":"4","key":"2023041909002648700_ocad013-B34","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1158\/1055-9965.EPI-19-0882","article-title":"Population-based registry linkages to improve validity of electronic health record-based cancer research","volume":"29","author":"Thompson","year":"2020","journal-title":"Cancer Epidemiol Biomarkers Prev"}],"container-title":["Journal of the American Medical Informatics Association"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/30\/5\/971\/49873008\/ocad013.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/30\/5\/971\/49873008\/ocad013.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,5]],"date-time":"2023-12-05T19:29:18Z","timestamp":1701804558000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jamia\/article\/30\/5\/971\/7031302"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,8]]},"references-count":34,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2023,2,8]]},"published-print":{"date-parts":[[2023,4,19]]}},"URL":"https:\/\/doi.org\/10.1093\/jamia\/ocad013","relation":{},"ISSN":["1067-5027","1527-974X"],"issn-type":[{"value":"1067-5027","type":"print"},{"value":"1527-974X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,5,1]]},"published":{"date-parts":[[2023,2,8]]}}}