{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T04:58:20Z","timestamp":1775192300496,"version":"3.50.1"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2022,2,15]],"date-time":"2022-02-15T00:00:00Z","timestamp":1644883200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000133","name":"Agency for Healthcare Research and Quality","doi-asserted-by":"publisher","award":["R18HS026198"],"award-info":[{"award-number":["R18HS026198"]}],"id":[{"id":"10.13039\/100000133","id-type":"DOI","asserted-by":"publisher"}]},{"name":"U.S. National Library of Medicine of the National Institutes of Health through","award":["T15LM007124"],"award-info":[{"award-number":["T15LM007124"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,4,13]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>The US Preventive Services Task Force (USPSTF) requires the estimation of lifetime pack-years to determine lung cancer screening eligibility. Leading electronic health record (EHR) vendors calculate pack-years using only the most recently recorded smoking data. The objective was to characterize EHR smoking data issues and to propose an approach to addressing these issues using longitudinal smoking data.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>In this cross-sectional study, we evaluated 16\u200a874 current or former smokers who met USPSTF age criteria for screening (50\u201380 years old), had no prior lung cancer diagnosis, and were seen in 2020 at an academic health system using the Epic\u00ae EHR. We described and quantified issues in the smoking data. We then estimated how many additional potentially eligible patients could be identified using longitudinal data. The approach was verified through manual review of records from 100 subjects.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Over 80% of evaluated records had inaccuracies, including missing packs-per-day or years-smoked (42.7%), outdated data (25.1%), missing years-quit (17.4%), and a recent change in packs-per-day resulting in inaccurate lifetime pack-years estimation (16.9%). Addressing these issues by using longitudinal data enabled the identification of 49.4% more patients potentially eligible for lung cancer screening (P\u2009&amp;lt;\u2009.001).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>Missing, outdated, and inaccurate smoking data in the EHR are important barriers to effective lung cancer screening. Data collection and analysis strategies that reflect changes in smoking habits over time could improve the identification of patients eligible for screening.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>The use of longitudinal EHR smoking data could improve lung cancer screening.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocac020","type":"journal-article","created":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T20:11:58Z","timestamp":1643746318000},"page":"779-788","source":"Crossref","is-referenced-by-count":81,"title":["Inaccuracies in electronic health records smoking data and a potential approach to address resulting underestimation in determining lung cancer screening eligibility"],"prefix":"10.1093","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5576-1486","authenticated-orcid":false,"given":"Polina V","family":"Kukhareva","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6560-0547","authenticated-orcid":false,"given":"Tanner J","family":"Caverly","sequence":"additional","affiliation":[{"name":"Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, Michigan, USA"},{"name":"Department of Learning Health Sciences, University of Michigan, Ann Arbor, Michigan, USA"},{"name":"Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"}]},{"given":"Haojia","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA"}]},{"given":"Hormuzd A","family":"Katki","sequence":"additional","affiliation":[{"name":"Division of Cancer Epidemiology & Genetics, National Cancer Institute, Bethesda, Maryland, USA"}]},{"given":"Li C","family":"Cheung","sequence":"additional","affiliation":[{"name":"Division of Cancer Epidemiology & Genetics, National Cancer Institute, Bethesda, Maryland, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1081-1670","authenticated-orcid":false,"given":"Thomas J","family":"Reese","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA"}]},{"given":"Guilherme","family":"Del Fiol","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA"}]},{"given":"Rachel","family":"Hess","sequence":"additional","affiliation":[{"name":"Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA"},{"name":"Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA"}]},{"given":"David W","family":"Wetter","sequence":"additional","affiliation":[{"name":"Department of Population Health Sciences and Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA"}]},{"given":"Yue","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA"}]},{"given":"Teresa Y","family":"Taft","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA"}]},{"given":"Michael C","family":"Flynn","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA"},{"name":"Community Physicians Group, University of Utah Health, Salt Lake City, Utah, USA"},{"name":"Community Physicians Group, University of Utah, Salt Lake City, UT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4282-9338","authenticated-orcid":false,"given":"Kensaku","family":"Kawamoto","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, University of Utah, Salt Lake City, 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