{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:06:29Z","timestamp":1740157589937,"version":"3.37.3"},"reference-count":0,"publisher":"Georg Thieme Verlag KG","issue":"02","funder":[{"DOI":"10.13039\/100000133","name":"Agency for Healthcare Research and Quality","doi-asserted-by":"crossref","award":["R21HS025443"],"award-info":[{"award-number":["R21HS025443"]}],"id":[{"id":"10.13039\/100000133","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2020,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>\n          Objectives\u2003Newborns are often assigned temporary names at birth. Temporary newborn names\u2014often a combination of the mother's last name and the newborn's gender\u2014are vulnerable to patient misidentification due to similarities with other newborns or between a mother and her newborn. We developed and implemented an alternative distinct naming strategy, and then compared its effectiveness on reducing the number of wrong-patient orders with the standard distinct naming strategy.<\/jats:p><jats:p>\n          Methods\u2003This study was conducted over a 14-month period in the newborn nursery and neonatal intensive care units of three hospitals that were part of the same health care system. We used a quasi-experimental study design using interrupted time series analysis to compare the differences in wrong-patient orders (an indicator of patient misidentification) before and after the implementation of the alternative distinct naming strategy.<\/jats:p><jats:p>\n          Results\u2003Overall, there were 25 wrong-patient errors per 10,000 orders during entire study period (36.8 per 10,000 before and 19.6 per 10,000 after). However, there was no statistically significant change in the rate of wrong-patient ordering errors after the transition from the distinct to the alternative distinct naming strategy (\u03b2\u2009=\u20090.832, 95% confidence interval [CI]\u2009=\u2009\u22120.83 to 2.49, p\u2009=\u20090.326). We also found that, overall, 1.7% of the clinicians contributed to 62% of the wrong-patient errors.<\/jats:p><jats:p>\n          Conclusion\u2003Although we did not find statistically significant differences in wrong-patient errors, the alternative distinct naming approach provides pragmatic advantages over its predecessors. In addition, the localization of wrong-patient errors within a small set of clinicians highlights the potential for developing strategies for delivering training to clinicians.<\/jats:p>","DOI":"10.1055\/s-0040-1705175","type":"journal-article","created":{"date-parts":[[2020,4,2]],"date-time":"2020-04-02T13:39:51Z","timestamp":1585834791000},"page":"235-241","source":"Crossref","is-referenced-by-count":2,"title":["Effect of an Alternative Newborn Naming Strategy on Wrong-Patient Errors: A Quasi-Experimental Study"],"prefix":"10.1055","volume":"11","author":[{"given":"Ethan","family":"Pfeifer","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri, United States"},{"name":"Institute for Informatics, Washington University School of Medicine, St Louis, Missouri, United States"}]},{"given":"Margaret","family":"Lozovatsky","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Washington University School of Medicine, St Louis, Missouri, United States"}]},{"given":"Joanna","family":"Abraham","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri, United States"},{"name":"Institute for Informatics, Washington University School of Medicine, St Louis, Missouri, United States"}]},{"given":"Thomas","family":"Kannampallil","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri, United States"},{"name":"Institute for Informatics, Washington University School of Medicine, St Louis, Missouri, United States"}]}],"member":"194","published-online":{"date-parts":[[2020,4,1]]},"container-title":["Applied Clinical Informatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/s-0040-1705175.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,5]],"date-time":"2020-05-05T13:18:53Z","timestamp":1588684733000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/s-0040-1705175"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3]]},"references-count":0,"journal-issue":{"issue":"02","published-online":{"date-parts":[[2020,3,18]]},"published-print":{"date-parts":[[2020,3]]}},"URL":"https:\/\/doi.org\/10.1055\/s-0040-1705175","relation":{},"ISSN":["1869-0327"],"issn-type":[{"type":"electronic","value":"1869-0327"}],"subject":[],"published":{"date-parts":[[2020,3]]}}}