{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T17:23:55Z","timestamp":1783704235608,"version":"3.55.0"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T00:00:00Z","timestamp":1639353600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"The National Health and Medical Research Council","award":["1142348"],"award-info":[{"award-number":["1142348"]}]},{"name":"The National Health and Medical Research Council","award":["1177787"],"award-info":[{"award-number":["1177787"]}]},{"DOI":"10.13039\/501100000925","name":"NHMRC","doi-asserted-by":"publisher","award":["1134919"],"award-info":[{"award-number":["1134919"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Accurate identification of self-harm presentations to Emergency Departments (ED) can lead to more timely mental health support, aid in understanding the burden of suicidal intent in a population, and support impact evaluation of public health initiatives related to suicide prevention. Given lack of manual self-harm reporting in ED, we aim to develop an automated system for the detection of self-harm presentations directly from ED triage notes.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and methods<\/jats:title>\n                  <jats:p>We frame this as supervised classification using natural language processing (NLP), utilizing a large data set of 477 627 free-text triage notes from ED presentations in 2012\u20132018 to The Royal Melbourne Hospital, Australia. The data were highly imbalanced, with only 1.4% of triage notes relating to self-harm. We explored various preprocessing techniques, including spelling correction, negation detection, bigram replacement, and clinical concept recognition, and several machine learning methods.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Our results show that machine learning methods dramatically outperform keyword-based methods. We achieved the best results with a calibrated Gradient Boosting model, showing 90% Precision and 90% Recall (PR-AUC 0.87) on blind test data. Prospective validation of the model achieves similar results (88% Precision; 89% Recall).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>ED notes are noisy texts, and simple token-based models work best. Negation detection and concept recognition did not change the results while bigram replacement significantly impaired model performance.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>This first NLP-based classifier for self-harm in ED notes has practical value for identifying patients who would benefit from mental health follow-up in ED, and for supporting surveillance of self-harm and suicide prevention efforts in the population.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocab261","type":"journal-article","created":{"date-parts":[[2021,11,11]],"date-time":"2021-11-11T12:10:45Z","timestamp":1636632645000},"page":"472-480","source":"Crossref","is-referenced-by-count":40,"title":["Detection of self-harm and suicidal ideation in emergency department triage notes"],"prefix":"10.1093","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1032-4650","authenticated-orcid":false,"given":"Vlada","family":"Rozova","sequence":"first","affiliation":[{"name":"School of Computing Technologies, RMIT University, Melbourne, Victoria, Australia"},{"name":"School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katrina","family":"Witt","sequence":"additional","affiliation":[{"name":"Orygen, Melbourne, Victoria, Australia"},{"name":"Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jo","family":"Robinson","sequence":"additional","affiliation":[{"name":"Orygen, Melbourne, Victoria, Australia"},{"name":"Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8661-1544","authenticated-orcid":false,"given":"Karin","family":"Verspoor","sequence":"additional","affiliation":[{"name":"School of Computing Technologies, RMIT University, Melbourne, Victoria, Australia"},{"name":"School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,12,13]]},"reference":[{"issue":"7","key":"2022012920413657900_ocab261-B1","doi-asserted-by":"crossref","DOI":"10.3390\/ijerph15071425","article-title":"Epidemiology of suicide and the psychiatric perspective","volume":"15","author":"Bachmann","year":"2018","journal-title":"Int J Environ Res Public Health"},{"key":"2022012920413657900_ocab261-B2","year":"2019"},{"key":"2022012920413657900_ocab261-B3","year":"2018"},{"key":"2022012920413657900_ocab261-B4","year":"2018"},{"key":"2022012920413657900_ocab261-B5","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1192\/bjp.182.6.537","article-title":"Suicide following deliberate self-harm: Long-term follow-up of patients who present to a general hospital","volume":"182","author":"Hawton","year":"2003","journal-title":"Br J Psychiatry"},{"issue":"1","key":"2022012920413657900_ocab261-B6","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1192\/bjp.185.1.70","article-title":"Repetition of deliberate self-harm and subsequent suicide risk: Long-term follow-up study of 11 583 patients","volume":"185","author":"Zahl","year":"2004","journal-title":"Br J Psychiatry"},{"issue":"7","key":"2022012920413657900_ocab261-B7","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1007\/s00127-007-0199-7","article-title":"Self-harm in England: a tale of three cities. Multicentre study of self-harm","volume":"42","author":"Hawton","year":"2007","journal-title":"Soc Psychiatry Psychiatr Epidemiol"},{"issue":"2","key":"2022012920413657900_ocab261-B8","doi-asserted-by":"crossref","first-page":"e31663","DOI":"10.1371\/journal.pone.0031663","article-title":"The incidence and repetition of hospital-treated deliberate self harm: findings from the world's first National Registry","volume":"7","author":"Perry","year":"2012","journal-title":"PLoS One"},{"issue":"4","key":"2022012920413657900_ocab261-B9","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1016\/j.jpsychores.2015.01.006","article-title":"General hospital-treated self-poisoning in England and Australia: comparison of presentation rates, clinical characteristics and aftercare based on sentinel unit data","volume":"78","author":"Hiles","year":"2015","journal-title":"J Psychosom Res"},{"key":"2022012920413657900_ocab261-B10"},{"issue":"1","key":"2022012920413657900_ocab261-B11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1027\/0227-5910\/a000583","article-title":"Sentinel surveillance for self-harm: existing challenges and opportunities for the future","volume":"40","author":"Witt","year":"2019","journal-title":"Crisis"},{"issue":"7","key":"2022012920413657900_ocab261-B12","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1007\/s00127-007-0199-7","article-title":"Self-harm in England: a tale of three cities","volume":"42","author":"Hawton","year":"2007","journal-title":"Soc Psychiatry Psychiatric Epidemiol"},{"issue":"6","key":"2022012920413657900_ocab261-B13","doi-asserted-by":"crossref","first-page":"e0157928","DOI":"10.1371\/journal.pone.0157928","article-title":"Prevalence and correlates of self-harm in the German general population","volume":"11","author":"M\u00fcller","year":"2016","journal-title":"PLoS One"},{"key":"2022012920413657900_ocab261-B14","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1002\/pds.2335","article-title":"A systematic review of validated methods for identifying suicide or suicidal ideation using administrative or claims data","volume":"21 Suppl 1","author":"Walkup","year":"2012","journal-title":"Pharmacoepidemiol Drug Saf"},{"key":"2022012920413657900_ocab261-B15","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.jad.2018.01.019","article-title":"Ten-year prediction of suicide death using Cox regression and machine learning in a nationwide retrospective cohort study in South Korea","volume":"231","author":"Choi","year":"2018","journal-title":"J Affect Disord"},{"key":"2022012920413657900_ocab261-B16","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.jbi.2018.10.005","article-title":"Using clinical Natural Language Processing for health outcomes research: overview and actionable suggestions for future advances","volume":"88","author":"Velupillai","year":"2018","journal-title":"J Biomed Inform"},{"issue":"11","key":"2022012920413657900_ocab261-B17","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1007\/s11920-019-1094-0","article-title":"Artificial intelligence for mental health and mental illnesses: an overview","volume":"21","author":"Graham","year":"2019","journal-title":"Curr Psychiatry Rep"},{"issue":"2","key":"2022012920413657900_ocab261-B18","doi-asserted-by":"crossref","first-page":"e0211116","DOI":"10.1371\/journal.pone.0211116","article-title":"Identification of suicidal behavior among psychiatrically hospitalized adolescents using natural language processing and machine learning of electronic health records","volume":"14","author":"Carson","year":"2019","journal-title":"PLoS One"},{"issue":"1","key":"2022012920413657900_ocab261-B19","doi-asserted-by":"crossref","first-page":"7426","DOI":"10.1038\/s41598-018-25773-2","article-title":"Identifying suicide ideation and suicidal attempts in a psychiatric clinical research database using natural language processing","volume":"8","author":"Fernandes","year":"2018","journal-title":"Sci Rep"},{"issue":"7","key":"2022012920413657900_ocab261-B20","doi-asserted-by":"crossref","first-page":"e17784","DOI":"10.2196\/17784","article-title":"Identifying and predicting intentional self-harm in electronic health record clinical notes: deep learning approach","volume":"8","author":"Obeid","year":"2020","journal-title":"JMIR Med Inform"},{"issue":"4","key":"2022012920413657900_ocab261-B21","doi-asserted-by":"crossref","first-page":"e0174708","DOI":"10.1371\/journal.pone.0174708","article-title":"Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning","volume":"12","author":"Horng","year":"2017","journal-title":"PLoS One"},{"key":"2022012920413657900_ocab261-B22","author":"Gligorijevic","journal-title":"Deep Attention Model for Triage of Emergency Department Patients"},{"key":"2022012920413657900_ocab261-B23","first-page":"319","volume-title":"ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing","author":"Neumann","year":"2019"},{"issue":"1","key":"2022012920413657900_ocab261-B24","doi-asserted-by":"crossref","first-page":"160035","DOI":"10.1038\/sdata.2016.35","article-title":"MIMIC-III, a freely accessible critical care database","volume":"3","author":"Johnson","year":"2016","journal-title":"Sci Data"},{"key":"2022012920413657900_ocab261-B25","author":"Kormilitzin"},{"key":"2022012920413657900_ocab261-B26"},{"key":"2022012920413657900_ocab261-B27","author":"Ribeiro"},{"key":"2022012920413657900_ocab261-B28","doi-asserted-by":"crossref","first-page":"g7594","DOI":"10.1136\/bmj.g7594","article-title":"Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement","volume":"350","author":"Collins","year":"2015","journal-title":"BMJ"},{"issue":"1","key":"2022012920413657900_ocab261-B29","doi-asserted-by":"crossref","first-page":"65","DOI":"10.3122\/jabfm.2015.01.140181","article-title":"Monitoring suicidal patients in primary care using electronic health records","volume":"28","author":"Anderson","year":"2015","journal-title":"J Am Board Fam Med"},{"key":"2022012920413657900_ocab261-B30","year":"2016"},{"issue":"108","key":"2022012920413657900_ocab261-B31","first-page":"1","article-title":"Issues in developing a surveillance case definition for nonfatal suicide attempt and intentional self-harm using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coded data","author":"Hedegaard","year":"2018","journal-title":"Natl Health Stat Report"},{"key":"2022012920413657900_ocab261-B32","article-title":"Using the \u2018presenting problem\u2019 field in emergency department data improves the enumeration of intentional self-harm in NSW hospital settings","author":"Sperandei","year":"2020","journal-title":"Aust N Z J Psychiatry"},{"key":"2022012920413657900_ocab261-B33","first-page":"100012","article-title":"Data mining of hospital suicidal and self-harm presentation records using a tailored evolutionary algorithm","volume":"3","author":"Stapelberg","year":"2021","journal-title":"Mach Learn Appl"},{"key":"2022012920413657900_ocab261-B34","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J Artif Intell Res"},{"issue":"1","key":"2022012920413657900_ocab261-B35","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1186\/1471-2105-14-106","article-title":"SMOTE for high-dimensional class-imbalanced data","volume":"14","author":"Blagus","year":"2013","journal-title":"BMC Bioinformatics"},{"issue":"24","key":"2022012920413657900_ocab261-B36","doi-asserted-by":"crossref","first-page":"9385","DOI":"10.3390\/ijerph17249385","article-title":"Development of a self-harm monitoring system for Victoria","volume":"17","author":"Robinson","year":"2020","journal-title":"Int J Environ Res Public Health"}],"container-title":["Journal of the American Medical Informatics Association"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/29\/3\/472\/42333266\/ocab261.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/29\/3\/472\/42333266\/ocab261.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,29]],"date-time":"2022-01-29T20:42:11Z","timestamp":1643488931000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jamia\/article\/29\/3\/472\/6460149"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,13]]},"references-count":36,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2021,12,13]]},"published-print":{"date-parts":[[2022,1,29]]}},"URL":"https:\/\/doi.org\/10.1093\/jamia\/ocab261","relation":{},"ISSN":["1067-5027","1527-974X"],"issn-type":[{"value":"1067-5027","type":"print"},{"value":"1527-974X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,3,1]]},"published":{"date-parts":[[2021,12,13]]}}}