• R Scott Evans, Kathryn G Kuttler, Kathy J Simpson, Stephen Howe, Peter F Crossno, Kyle V Johnson, Misty N Schreiner, James F Lloyd, William H Tettelbach, Roger K Keddington, Alden Tanner, Chelbi Wilde, and Terry P Clemmer.
• Homer Warner Center for Informatics Research, Intermountain Healthcare, Salt Lake City, Utah, USA Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, Utah, USA.
• J Am Med Inform Assoc. 2015 Mar 1; 22 (2): 350-60.

ObjectiveDevelop and evaluate an automated case detection and response triggering system to monitor patients every 5 min and identify early signs of physiologic deterioration.Materials And MethodsA 2-year prospective, observational study at a large level 1 trauma center. All patients admitted to a 33-bed medical and oncology floor (A) and a 33-bed non-intensive care unit (ICU) surgical trauma floor (B) were monitored. During the intervention year, pager alerts of early physiologic deterioration were automatically sent to charge nurses along with access to a graphical point-of-care web page to facilitate patient evaluation.ResultsNurses reported the positive predictive value of alerts was 91-100% depending on erroneous data presence. Unit A patients were significantly older and had significantly more comorbidities than unit B patients. During the intervention year, unit A patients had a significant increase in length of stay, more transfers to ICU (p = 0.23), and significantly more medical emergency team (MET) calls (p = 0.0008), and significantly fewer died (p = 0.044) compared to the pre-intervention year. No significant differences were found on unit B.ConclusionsWe monitored patients every 5 min and provided automated pages of early physiologic deterioration. This before-after study found a significant increase in MET calls and a significant decrease in mortality only in the unit with older patients with multiple comorbidities, and thus further study is warranted to detect potential confounding. Moreover, nurses reported the graphical alerts provided information needed to quickly evaluate patients, and they felt more confident about their assessment and more comfortable requesting help.© The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

18 keywords...

hide…