{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:23:17Z","timestamp":1740201797481,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"abstract":"<jats:p>The increasing adoption of electronic medical record (EMR) systems including nursing documentation worldwide provides opportunities for improving patient safety by the automatic prediction of adverse events using EMR data. An inpatient fall is a preventable adverse event that can be managed more effectively and efficiently through a data-driven predictive approach. This study implemented a new approach and explored its effects in neurologic inpatient units. The results suggest that integrating an automatic fall prediction system with the EMR system could reduce inpatient falls.<\/jats:p>","DOI":"10.3233\/978-1-61499-658-3-828","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T08:25:19Z","timestamp":1740126319000},"source":"Crossref","is-referenced-by-count":0,"title":["Effect of Automatic Inpatient Fall Prediction Using Routinely Captured EMR Data: Preliminary Results"],"prefix":"10.3233","author":[{"family":"Cho Insook","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Chung Eunja","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Nursing Informatics 2016"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T09:06:01Z","timestamp":1740128761000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-657-6&spage=828&doi=10.3233\/978-1-61499-658-3-828"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-658-3-828","relation":{},"ISSN":["0926-9630"],"issn-type":[{"value":"0926-9630","type":"print"}],"subject":[],"published":{"date-parts":[[2016]]}}}