{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T12:13:11Z","timestamp":1775131991962,"version":"3.50.1"},"reference-count":79,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T00:00:00Z","timestamp":1668384000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"name":"Australian National Health and Medical Research Council Centre for Research Excellence in Digital Health","award":["APP1134919"],"award-info":[{"award-number":["APP1134919"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>To summarize the research literature evaluating automated methods for early detection of safety problems with health information technology (HIT).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>We searched bibliographic databases including MEDLINE, ACM Digital, Embase, CINAHL Complete, PsycINFO, and Web of Science from January 2010 to June 2021 for studies evaluating the performance of automated methods to detect HIT problems. HIT problems were reviewed using an existing classification for safety concerns. Automated methods were categorized into rule-based, statistical, and machine learning methods, and their performance in detecting HIT problems was assessed. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses extension for Scoping Reviews statement.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Of the 45 studies identified, the majority (n\u2009=\u200927, 60%) focused on detecting use errors involving electronic health records and order entry systems. Machine learning (n\u2009=\u200922) and statistical modeling (n\u2009=\u200917) were the most common methods. Unsupervised learning was used to detect use errors in laboratory test results, prescriptions, and patient records while supervised learning was used to detect technical errors arising from hardware or software issues. Statistical modeling was used to detect use errors, unauthorized access, and clinical decision support system malfunctions while rule-based methods primarily focused on use errors.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>A wide variety of rule-based, statistical, and machine learning methods have been applied to automate the detection of safety problems with HIT. Many opportunities remain to systematically study their application and effectiveness in real-world settings.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocac220","type":"journal-article","created":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T17:48:44Z","timestamp":1668448124000},"page":"382-392","source":"Crossref","is-referenced-by-count":5,"title":["Using automated methods to detect safety problems with health information technology: a scoping review"],"prefix":"10.1093","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2299-2971","authenticated-orcid":false,"given":"Didi","family":"Surian","sequence":"first","affiliation":[{"name":"Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University , Sydney, Australia"}]},{"given":"Ying","family":"Wang","sequence":"additional","affiliation":[{"name":"Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University , Sydney, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6444-6584","authenticated-orcid":false,"given":"Enrico","family":"Coiera","sequence":"additional","affiliation":[{"name":"Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University , Sydney, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8426-5588","authenticated-orcid":false,"given":"Farah","family":"Magrabi","sequence":"additional","affiliation":[{"name":"Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University , Sydney, Australia"}]}],"member":"286","published-online":{"date-parts":[[2022,11,14]]},"reference":[{"issue":"25","key":"2023011811023147800_ocac220-B1","doi-asserted-by":"crossref","first-page":"2526","DOI":"10.1056\/NEJMsa020847","article-title":"Improving safety with information technology","volume":"348","author":"Bates","year":"2003","journal-title":"N Engl J Med"},{"key":"2023011811023147800_ocac220-B2","first-page":"20","article-title":"The safety and quality of decision support systems","volume":"45","author":"Coiera","year":"2006","journal-title":"Yearb Med Inform"},{"issue":"18","key":"2023011811023147800_ocac220-B3","doi-asserted-by":"crossref","first-page":"2741","DOI":"10.1001\/archinte.160.18.2741","article-title":"Effects of computerized physician order entry on prescribing practices","volume":"160","author":"Teich","year":"2000","journal-title":"Arch Intern Med"},{"issue":"5","key":"2023011811023147800_ocac220-B4","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1197\/jamia.M2667","article-title":"The effect of electronic prescribing on medication errors and adverse drug events: a systematic review","volume":"15","author":"Ammenwerth","year":"2008","journal-title":"J Am Med Inform Assoc"},{"issue":"4","key":"2023011811023147800_ocac220-B5","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1136\/jamia.2001.0080299","article-title":"Reducing the frequency of errors in medicine using information technology","volume":"8","author":"Bates","year":"2001","journal-title":"J Am Med Inform Assoc"},{"issue":"2\u20133","key":"2023011811023147800_ocac220-B6","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/S1386-5056(98)00152-X","article-title":"Using information systems to measure and improve quality","volume":"53","author":"Bates","year":"1999","journal-title":"Int J Med Inf"},{"issue":"2","key":"2023011811023147800_ocac220-B7","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1197\/jamia.M1471","article-title":"Some unintended consequences of information technology in health care: the nature of patient care information system-related errors","volume":"11","author":"Ash","year":"2004","journal-title":"J Am Med Inform Assoc"},{"issue":"2","key":"2023011811023147800_ocac220-B8","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1093\/jamia\/ocw154","article-title":"Problems with health information technology and their effects on care delivery and patient outcomes: a systematic review","volume":"24","author":"Kim","year":"2017","journal-title":"J Am Med Inform Assoc"},{"issue":"14","key":"2023011811023147800_ocac220-B9","doi-asserted-by":"crossref","first-page":"1281","DOI":"10.1001\/archinternmed.2011.327","article-title":"Defining health information technology-related errors: new developments since to err is human","volume":"171","author":"Sittig","year":"2011","journal-title":"Arch Intern Med"},{"issue":"3","key":"2023011811023147800_ocac220-B10","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.ijmedinf.2014.12.003","article-title":"Clinical safety of England\u2019s national programme for IT: a retrospective analysis of all reported safety events 2005 to 2011","volume":"84","author":"Magrabi","year":"2015","journal-title":"Int J Med Inform"},{"issue":"1","key":"2023011811023147800_ocac220-B11","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1177\/1460458218814893","article-title":"Current challenges in health information technology\u2013related patient safety","volume":"26","author":"Sittig","year":"2020","journal-title":"Health Informatics J"},{"key":"2023011811023147800_ocac220-B12","volume-title":"Health IT and Patient Safety: Building Safer Systems for Better Care","author":"Institute of Medicine","year":"2012"},{"key":"2023011811023147800_ocac220-B13","first-page":"94","author":"Campbell"},{"key":"2023011811023147800_ocac220-B14","first-page":"2866","author":"Baliga","year":"2006"},{"key":"2023011811023147800_ocac220-B15","doi-asserted-by":"crossref","DOI":"10.1201\/b13617","volume-title":"Guide to Health Informatics","author":"Coiera","year":"2015","edition":"3rd ed"},{"issue":"5","key":"2023011811023147800_ocac220-B16","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1006\/cbmr.1993.1032","article-title":"Monitoring the monitor: automated statistical tracking of a clinical event monitor","volume":"26","author":"Hripcsak","year":"1993","journal-title":"Comput Biomed Res"},{"issue":"2","key":"2023011811023147800_ocac220-B17","doi-asserted-by":"crossref","first-page":"e10264","DOI":"10.2196\/10264","article-title":"Health information technology in healthcare quality and patient safety: literature review","volume":"6","author":"Feldman","year":"2018","journal-title":"JMIR Med Inform"},{"issue":"7","key":"2023011811023147800_ocac220-B18","doi-asserted-by":"crossref","first-page":"467","DOI":"10.7326\/M18-0850","article-title":"PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation","volume":"169","author":"Tricco","year":"2018","journal-title":"Ann Intern Med"},{"issue":"1","key":"2023011811023147800_ocac220-B19","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1080\/1364557032000119616","article-title":"Scoping studies: towards a methodological framework","volume":"8","author":"Arksey","year":"2005","journal-title":"Int J Soc Res Methodol"},{"issue":"4","key":"2023011811023147800_ocac220-B20","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1002\/jrsm.1123","article-title":"A scoping review of scoping reviews: advancing the approach and enhancing the consistency","volume":"5","author":"Pham","year":"2014","journal-title":"Res Synth Methods"},{"issue":"1","key":"2023011811023147800_ocac220-B21","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/2190-8532-1-5","article-title":"Specializing network analysis to detect anomalous insider actions","volume":"1","author":"Chen","year":"2012","journal-title":"Secur Inform"},{"key":"2023011811023147800_ocac220-B22","first-page":"1","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"Witten","year":"2017","edition":"4th ed."},{"key":"2023011811023147800_ocac220-B23","first-page":"1","volume-title":"Practical Text Mining and Statistical Analysis for Non-Structured Text Data Applications","author":"Miner","year":"2012"},{"issue":"3","key":"2023011811023147800_ocac220-B24","first-page":"249","article-title":"Supervised machine learning: a review of classification techniques","volume":"31","author":"Kotsiantis","year":"2007","journal-title":"Informatica"},{"key":"2023011811023147800_ocac220-B25","doi-asserted-by":"crossref","DOI":"10.1007\/3-540-32446-1","volume-title":"Logical Foundations for Rule-Based Systems","author":"Ligeza","year":"2006"},{"key":"2023011811023147800_ocac220-B26","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1007\/978-3-642-21004-4_7","volume-title":"Rule-Based Expert Systems. Intelligent Systems","author":"Grosan","year":"2011"},{"issue":"4","key":"2023011811023147800_ocac220-B27","doi-asserted-by":"publisher","first-page":"588","DOI":"10.1002\/bimj.201300226","article-title":"Machine learning versus statistical modeling","volume":"56","author":"Boulesteix","year":"2014","journal-title":"Biom J"},{"issue":"3","key":"2023011811023147800_ocac220-B28","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1111\/insr.12176","article-title":"Statistical inference, learning and models in big data","volume":"84","author":"Franke","year":"2016","journal-title":"Int Stat Rev"},{"key":"2023011811023147800_ocac220-B29","first-page":"1","volume-title":"Introduction to Machine Learning","author":"Alpaydin","year":"2014","edition":"3rd ed"},{"issue":"4","key":"2023011811023147800_ocac220-B30","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1136\/amiajnl-2011-000217","article-title":"Using statistical and machine learning to help institutions detect suspicious access to electronic health records","volume":"18","author":"Boxwala","year":"2011","journal-title":"J Am Med Inform Assoc"},{"issue":"1","key":"2023011811023147800_ocac220-B31","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s10994-013-5376-1","article-title":"Detecting inappropriate access to electronic health records using collaborative filtering","volume":"95","author":"Menon","year":"2014","journal-title":"Mach Learn"},{"key":"2023011811023147800_ocac220-B32","author":"Hussain","year":"25\u201328, 2016; ,"},{"key":"2023011811023147800_ocac220-B33","author":"D\u2019hondt","year":"2016"},{"key":"2023011811023147800_ocac220-B34","first-page":"143","article-title":"Unsupervised context-sensitive spelling correction of clinical free-text with word and character n-gram embeddings","author":"Fivez","year":"2017","journal-title":"BioNLP."},{"issue":"1","key":"2023011811023147800_ocac220-B35","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1186\/s12911-019-0852-6","article-title":"A clustering approach for detecting implausible observation values in electronic health records data","volume":"19","author":"Estiri","year":"2019","journal-title":"BMC Med Inform Decis Mak"},{"key":"2023011811023147800_ocac220-B36","doi-asserted-by":"crossref","first-page":"104830","DOI":"10.1016\/j.cmpb.2019.01.002","article-title":"Semi-supervised encoding for outlier detection in clinical observation data","volume":"181","author":"Estiri","year":"2019","journal-title":"Comput Methods Programs Biomed"},{"issue":"2","key":"2023011811023147800_ocac220-B37","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1109\/JBHI.2018.2828028","article-title":"DDC-outlier: preventing medication errors using unsupervised learning","volume":"23","author":"Santos","year":"2019","journal-title":"IEEE J Biomed Health Inform"},{"issue":"1","key":"2023011811023147800_ocac220-B38","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1093\/jamia\/ocy139","article-title":"Cranky comments: detecting clinical decision support malfunctions through free-text override reasons","volume":"26","author":"Aaron","year":"2019","journal-title":"J Am Med Inform Assoc"},{"issue":"3","key":"2023011811023147800_ocac220-B39","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1007\/s10278-019-00296-y","article-title":"Automated misspelling detection and correction in Persian clinical text","volume":"33","author":"Yazdani","year":"2020","journal-title":"J Digit Imaging"},{"issue":"3","key":"2023011811023147800_ocac220-B40","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.artmed.2011.08.003","article-title":"Statistical semantic and clinician confidence analysis for correcting abbreviations and spelling errors in clinical progress notes","volume":"53","author":"Wong","year":"2011","journal-title":"Artif Intell Med"},{"key":"2023011811023147800_ocac220-B41","first-page":"723","article-title":"Anomaly and signature filtering improve classifier performance for detection of suspicious access to EHRs","volume":"2011","author":"Kim","year":"2011","journal-title":"AMIA Annu Symp Proc"},{"key":"2023011811023147800_ocac220-B42","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.jbi.2015.04.008","article-title":"Automated misspelling detection and correction in clinical free-text records","volume":"55","author":"Lai","year":"2015","journal-title":"J Biomed Inform"},{"key":"2023011811023147800_ocac220-B43","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.csl.2014.09.001","article-title":"Context-aware correction of spelling errors in Hungarian medical documents","volume":"35","author":"Sikl\u00f3si","year":"2016","journal-title":"Computer Speech Lang"},{"key":"2023011811023147800_ocac220-B44","author":"Ray","year":"2016"},{"key":"2023011811023147800_ocac220-B45","first-page":"102","article-title":"Reducing clinical noise for body mass index measures due to unit and transcription errors in the electronic health record","volume":"2017","author":"Goodloe","year":"2017","journal-title":"AMIA Jt Summits Transl Sci Proc"},{"issue":"3","key":"2023011811023147800_ocac220-B46","doi-asserted-by":"crossref","first-page":"910","DOI":"10.4338\/ACI-2017-01-RA-0006","article-title":"Clinical decisions support malfunctions in a commercial electronic health record","volume":"8","author":"Kassakian","year":"2017","journal-title":"Appl Clin Inform"},{"key":"2023011811023147800_ocac220-B47","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.artmed.2018.06.003","article-title":"Change-point detection method for clinical decision support system rule monitoring","volume":"91","author":"Liu","year":"2018","journal-title":"Artif Intell Med"},{"issue":"7","key":"2023011811023147800_ocac220-B48","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1093\/jamia\/ocy041","article-title":"Using statistical anomaly detection models to find clinical decision support malfunctions","volume":"25","author":"Ray","year":"2018","journal-title":"J Am Med Inform Assoc"},{"issue":"3","key":"2023011811023147800_ocac220-B49","doi-asserted-by":"crossref","first-page":"100","DOI":"10.4018\/IJISP.2018070106","article-title":"Misuse of \u201cBreak-the-Glass\u201d policies in hospitals: detecting unauthorized access to sensitive patient health data","volume":"12","author":"Gewald","year":"2018","journal-title":"Int J Inf Secur Priv"},{"key":"2023011811023147800_ocac220-B50","doi-asserted-by":"crossref","first-page":"40285","DOI":"10.1109\/ACCESS.2019.2906503","article-title":"Density-based outlier detection for safeguarding electronic patient record systems","volume":"7","author":"Boddy","year":"2019","journal-title":"IEEE Access"},{"key":"2023011811023147800_ocac220-B51","first-page":"2","author":"Patrick","year":"2010"},{"issue":"2","key":"2023011811023147800_ocac220-B52","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1136\/amiajnl-2012-001055","article-title":"Understanding and preventing wrong-patient electronic orders: a randomized controlled trial","volume":"20","author":"Adelman","year":"2013","journal-title":"J Am Med Inform Assoc"},{"key":"2023011811023147800_ocac220-B53","author":"Uddin","year":"2014"},{"issue":"4","key":"2023011811023147800_ocac220-B54","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1007\/s10278-015-9781-9","article-title":"Improving radiology report quality by rapidly notifying radiologist of report errors","volume":"28","author":"Minn","year":"2015","journal-title":"J Digit Imaging"},{"issue":"7","key":"2023011811023147800_ocac220-B55","doi-asserted-by":"crossref","first-page":"521","DOI":"10.2146\/ajhp150690","article-title":"Automated detection of look-alike\/sound-alike medication errors","volume":"74","author":"Rash-Foanio","year":"2017","journal-title":"Am J Health Syst Pharm"},{"issue":"11","key":"2023011811023147800_ocac220-B56","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1136\/bmjqs-2019-009420","article-title":"Automated detection of wrong-drug prescribing errors","volume":"28","author":"Lambert","year":"2019","journal-title":"BMJ Qual Saf"},{"key":"2023011811023147800_ocac220-B57","first-page":"1716","author":"Zhao","year":"2019"},{"key":"2023011811023147800_ocac220-B58","first-page":"43","article-title":"Automated spelling correction for clinical text mining in Russian","volume":"270","author":"Balabaeva","year":"2020","journal-title":"Stud Health Technol Inform"},{"issue":"7","key":"2023011811023147800_ocac220-B59","doi-asserted-by":"crossref","first-page":"2107","DOI":"10.1109\/JBHI.2019.2956973","article-title":"Automated surgical term clustering: a text mining approach for unstructured textual surgery descriptions","volume":"24","author":"Khaleghi","year":"2020","journal-title":"IEEE J Biomed Health Inform"},{"issue":"2","key":"2023011811023147800_ocac220-B60","doi-asserted-by":"crossref","first-page":"e25530","DOI":"10.2196\/25530","article-title":"Similarity-based unsupervised spelling correction using BioWordVec: development and usability study of bacterial culture and antimicrobial susceptibility reports","volume":"9","author":"Kim","year":"2021","journal-title":"JMIR Med Inform"},{"issue":"1","key":"2023011811023147800_ocac220-B61","doi-asserted-by":"crossref","first-page":"10164","DOI":"10.1038\/s41598-020-66925-7","article-title":"Automated data cleaning of paediatric anthropometric data from longitudinal electronic health records: protocol and application to a large patient cohort","volume":"10","author":"Phan","year":"2020","journal-title":"Sci Rep"},{"key":"2023011811023147800_ocac220-B62","first-page":"63","article-title":"Detection of anomalous insiders in collaborative environments via relational analysis of access logs","volume":"2011","author":"Chen","year":"2011","journal-title":"CODASPY"},{"key":"2023011811023147800_ocac220-B63","first-page":"119","article-title":"Leveraging social networks to detect anomalous insider actions in collaborative environments","volume":"2011","author":"Chen","year":"2011","journal-title":"ISI"},{"issue":"3","key":"2023011811023147800_ocac220-B64","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1109\/TDSC.2012.11","article-title":"Detecting anomalous insiders in collaborative information systems","volume":"9","author":"Chen","year":"2012","journal-title":"IEEE Trans Dependable Secure Comput"},{"issue":"3","key":"2023011811023147800_ocac220-B65","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1515\/cclm-2019-0534","article-title":"Highly accurate and explainable detection of specimen mix-up using a machine learning model","volume":"58","author":"Mitani","year":"2020","journal-title":"Clin Chem Lab Med"},{"issue":"11","key":"2023011811023147800_ocac220-B66","doi-asserted-by":"crossref","first-page":"233","DOI":"10.21037\/atm.2018.08.11","article-title":"Detecting insertion, substitution, and deletion errors in radiology reports using neural sequence-to-sequence models","volume":"7","author":"Zech","year":"2019","journal-title":"Ann Transl Med"},{"issue":"1","key":"2023011811023147800_ocac220-B67","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1136\/amiajnl-2012-001018","article-title":"Explaining accesses to electronic medical records using diagnosis information","volume":"20","author":"Fabbri","year":"2013","journal-title":"J Am Med Inform Assoc"},{"issue":"4","key":"2023011811023147800_ocac220-B68","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1515\/cclm-2012-0752","article-title":"A novel weighted cumulative delta-check method for highly sensitive detection of specimen mix-up in the clinical laboratory","volume":"51","author":"Yamashita","year":"2013","journal-title":"Clin Chem Lab Med"},{"issue":"3","key":"2023011811023147800_ocac220-B69","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1136\/amiajnl-2012-001144","article-title":"Syndromic surveillance for health information system failures: a feasibility study","volume":"20","author":"Ong","year":"2013","journal-title":"J Am Med Inform Assoc"},{"key":"2023011811023147800_ocac220-B70","first-page":"8180","author":"Watson","year":"2021"},{"key":"2023011811023147800_ocac220-B71","author":"Tong","year":"21\u201324, 2020;"},{"issue":"6","key":"2023011811023147800_ocac220-B72","doi-asserted-by":"crossref","first-page":"6199","DOI":"10.1007\/s12652-020-02189-3","article-title":"SybilWatch: a novel approach to detect Sybil attack in IoT based smart health care","volume":"12","author":"Vaishnavi","year":"2021","journal-title":"J Ambient Intell Human Comput"},{"key":"2023011811023147800_ocac220-B73","first-page":"569","article-title":"Change-point detection for monitoring clinical decision support systems with a Multi-Process Dynamic Linear Model","volume":"2017","author":"Liu","year":"2017","journal-title":"Proceedings (IEEE Int Conf Bioinformatics Biomed)"},{"key":"2023011811023147800_ocac220-B74","author":"Zhang","year":"12\u201315, 2016; ,"},{"issue":"1","key":"2023011811023147800_ocac220-B75","doi-asserted-by":"crossref","first-page":"16","DOI":"10.4258\/hir.2022.28.1.16","article-title":"Protected health information recognition by fine-tuning a pre-training transformer model","volume":"28","author":"Oh","year":"2022","journal-title":"Healthc Inform Res"},{"key":"2023011811023147800_ocac220-B76","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.neunet.2019.08.032","article-title":"Named entity recognition in electronic health records using transfer learning bootstrapped neural networks","volume":"121","author":"Luka","year":"2020","journal-title":"Neural Netw"},{"key":"2023011811023147800_ocac220-B77","first-page":"574","article-title":"Observational health data sciences and informatics (OHDSI): opportunities for observational researchers","volume":"216","author":"Hripcsak","year":"2015","journal-title":"Stud Health Technol Inform"},{"issue":"1","key":"2023011811023147800_ocac220-B78","doi-asserted-by":"crossref","first-page":"24070","DOI":"10.1038\/s41598-021-03332-6","article-title":"Preliminary feasibility assessment of CDM-based active surveillance using current status of medical device data in medical records and OMOP-CDM","volume":"11","author":"Choi","year":"2021","journal-title":"Sci Rep"},{"key":"2023011811023147800_ocac220-B79","first-page":"95","article-title":"The usage of OHDSI OMOP \u2013 a scoping review","volume":"283","author":"Reinecke","year":"2021","journal-title":"Stud Health Technol Inform"}],"container-title":["Journal of the American Medical Informatics Association"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/30\/2\/382\/48754792\/ocac220.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/30\/2\/382\/48754792\/ocac220.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,18]],"date-time":"2023-01-18T11:03:36Z","timestamp":1674039816000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jamia\/article\/30\/2\/382\/6827298"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,14]]},"references-count":79,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,11,14]]},"published-print":{"date-parts":[[2023,1,18]]}},"URL":"https:\/\/doi.org\/10.1093\/jamia\/ocac220","relation":{},"ISSN":["1067-5027","1527-974X"],"issn-type":[{"value":"1067-5027","type":"print"},{"value":"1527-974X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,2,1]]},"published":{"date-parts":[[2022,11,14]]}}}