Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Aug 9, 2020
Open Peer Review Period: Aug 9, 2020 - Aug 16, 2020
Date Accepted: Oct 21, 2020
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Alert Override Patterns with a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study
ABSTRACT
Background:
Physicians’ alert overriding behavior is known for a most important factor that leads a computerized provider order entry (CPOE) combined with clinical decision support system (CDSS) failure to achieve its potential adverse drug events prevention effect. Previous studies on this subject have focused on specific diseases and/or alert types for well-defined targets as well as specific settings. An emergency department (ED) is an optimal environment to examine physicians’ alert overriding behaviors from a broad perspective because patients have a wider range of severity, and many receive interdisciplinary care in this environment. However, less than one-tenth of the studies targeted the physicians’ behavior in an ED
Objective:
The objective of this study was to describe alert override patterns with a commercial medication CDSS in an academic ED.
Methods:
This study was conducted at a tertiary urban academic hospital in an ED with an annual census of 80,000 visits. We analyzed data about the patients who visited the ED during an 18-month period, the medical staff who treated them, and the prescription and computerized provider order entry alert log. We also performed descriptive analysis and logistic regression for assessing the risk factors for alert overrides.
Results:
During the study period, 611 physicians cared for 71,546 patients with 101,186 visits. The ED physicians encountered 13.75 alerts during every 100 orders entered. Of the total 102,887 alerts, almost two-thirds (63.8%) were overridden. The univariate and multivariate logistic regression analysis identified 21 statistically significant risk factors for ED physicians’ alert override behavior.
Conclusions:
In this retrospective study, we assessed the alert override patterns with a medication CDSS in an academic ED and assessed their contributing factors including physicians’ designation and patient severity.
Citation
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