{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T01:23:40Z","timestamp":1773278620799,"version":"3.50.1"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"2","funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"crossref","award":["1054146"],"award-info":[{"award-number":["1054146"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,3,1]]},"abstract":"<jats:p>Quantifying alert override has been the focus of much research in health informatics, with override rate traditionally viewed as a surrogate inverse indicator for alert effectiveness. However, relying on alert override to assess computerized alerts assumes that alerts are being read and determined to be irrelevant by users. Our research suggests that this is unlikely to be the case when users are experiencing alert overload. We propose that over time, alert override becomes habitual. The override response is activated by environmental cues and repeated automatically, with limited conscious intention. In this paper we outline this new perspective on understanding alert override. We present evidence consistent with the notion of alert override as a habitual behavior and discuss implications of this novel perspective for future research on alert override, a common and persistent problem accompanying decision support system implementation.<\/jats:p>","DOI":"10.1093\/jamia\/ocw072","type":"journal-article","created":{"date-parts":[[2016,6,7]],"date-time":"2016-06-07T02:34:40Z","timestamp":1465266880000},"page":"409-412","source":"Crossref","is-referenced-by-count":63,"title":["Alert override as a habitual behavior \u2013 a new perspective on a persistent problem"],"prefix":"10.1093","volume":"24","author":[{"given":"Melissa T","family":"Baysari","sequence":"first","affiliation":[{"name":"Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Australia"},{"name":"St Vincent\u2019s Clinical School, UNSW Australia"}]},{"given":"Amina","family":"Tariq","sequence":"additional","affiliation":[{"name":"Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Australia"}]},{"given":"Richard O","family":"Day","sequence":"additional","affiliation":[{"name":"St Vincent\u2019s Clinical School, UNSW Australia"},{"name":"Department of Clinical Pharmacology and Toxicology, St Vincent\u2019s Hospital, Sydney, Australia"}]},{"given":"Johanna I","family":"Westbrook","sequence":"additional","affiliation":[{"name":"Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Australia"}]}],"member":"286","published-online":{"date-parts":[[2016,6,6]]},"reference":[{"issue":"5","key":"2020110612374570600_ocw072-B1","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1016\/j.ergon.2014.08.001","article-title":"All at sea: an ergonomic analysis of oil production platform control rooms","volume":"44","author":"Walker","year":"2014","journal-title":"Int J Ind Ergon"},{"issue":"6","key":"2020110612374570600_ocw072-B2","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1016\/j.jprocont.2013.03.010","article-title":"A combined analysis of plant connectivity and alarm logs to reduce the number of alerts in an automation system","volume":"23","author":"Schleburg","year":"2013","journal-title":"J Process Control"},{"issue":"3","key":"2020110612374570600_ocw072-B3","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1093\/ajhp\/26.3.140","article-title":"Computer applications in the hospital medication system","volume":"26","author":"Gouveia","year":"1969","journal-title":"Am J Health Syst Pharm"},{"key":"2020110612374570600_ocw072-B4","first-page":"26","article-title":"Some Unintended Consequences of Clinical Decision Support Systems","volume":"2007","author":"Ash","year":"2007","journal-title":"AMIA Annual Symp Proc"},{"issue":"6","key":"2020110612374570600_ocw072-B5","doi-asserted-by":"crossref","first-page":"e1948","DOI":"10.1542\/peds.2013-0864","article-title":"Time for Alert-ology or RE-sensitization?","volume":"131","author":"Lawless","year":"2013","journal-title":"Pediatrics"},{"issue":"e1","key":"2020110612374570600_ocw072-B6","doi-asserted-by":"crossref","first-page":"e145","DOI":"10.1136\/amiajnl-2011-000743","article-title":"Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study","volume":"19","author":"Embi","year":"2012","journal-title":"J Am Med Inform Assoc"},{"issue":"2","key":"2020110612374570600_ocw072-B7","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1197\/jamia.M1809","article-title":"Overriding of drug safety alerts in computerized physician order entry","volume":"13","author":"van der Sijs","year":"2006","journal-title":"J Am Med Inform Assoc"},{"issue":"3","key":"2020110612374570600_ocw072-B8","doi-asserted-by":"crossref","first-page":"802","DOI":"10.4338\/ACI-2013-12-RA-0103","article-title":"Drug interaction alert override rates in the Meaningful Use era. 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