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Lookup NU author(s): Professor Sarah SlightORCiD
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Background: Electronic prescribing is increasingly used, in part because of government incentives for its use. Many of its benefits come from clinical decision support (CDS), but often too many alerts are displayed, resulting in alert fatigue. Objective: To characterize the override rates for medication-related CDS alerts in the outpatient setting, the reasons cited for overrides at the time of prescribing, and the appropriateness of overrides. Methods: We measured CDS alert override rates and the coded reasons for overrides cited by providers at the time of prescribing. Our primary outcome was the rate of CDS alert overrides; our secondary outcomes were the rate of overrides by alert type, reasons cited for overrides at the time of prescribing, and override appropriateness for a subset of 600 alert overrides. Through detailed chart reviews of alert override cases, and selective literature review, we developed appropriateness criteria for each alert type, which were modified iteratively as necessary until consensus was reached on all criteria. Results: We reviewed 157 483 CDS alerts (7.9% alert rate) on 2 004 069 medication orders during the study period. 82 889 (52.6%) of alerts were overridden. The most common alerts were duplicate drug (33.1%), patient allergy (16.8%), and drug-drug interactions (15.8%). The most likely alerts to be overridden were formulary substitutions (85.0%), age-based recommendations (79.0%), renal recommendations (78.0%), and patient allergies (77.4%). An average of 53% of overrides were classified as appropriate, and rates of appropriateness varied by alert type (p<0.0001) from 12% for renal recommendations to 92% for patient allergies. Discussion: About half of CDS alerts were overridden by providers and about half of the overrides were classified as appropriate, but the likelihood of overriding an alert varied widely by alert type. Refinement of these alerts has the potential to improve the relevance of alerts and reduce alert fatigue.
Author(s): Nanji KC, Slight SP, Seger DL, Cho I, Fiskio JM, Redden LM, Volk LA, Bates DW
Publication type: Article
Publication status: Published
Journal: Journal of the American Medical Informatics Association
Print publication date: 01/05/2014
Online publication date: 28/10/2013
Acceptance date: 08/10/2013
ISSN (print): 1067-5027
ISSN (electronic): 1527-974X
Publisher: BMJ Publishing Group
PubMed id: 24166725
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