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Lookup NU author(s): Professor Sarah Slight
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© The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved.Background Experts suggest that formulary alerts at the time of medication order entry are the most effective form of clinical decision support to automate formulary management.Objective Our objectives were to quantify the frequency of inappropriate nonformulary medication (NFM) alert overrides in the inpatient setting and provide insight on how the design of formulary alerts could be improved.Methods Alert overrides of the top 11 (n = 206) most-utilized and highest-costing NFMs, from January 1 to December 31, 2012, were randomly selected for appropriateness evaluation. Using an empirically developed appropriateness algorithm, appropriateness of NFM alert overrides was assessed by 2 pharmacists via chart review. Appropriateness agreement of overrides was assessed with a Cohen's kappa. We also assessed which types of NFMs were most likely to be inappropriately overridden, the override reasons that were disproportionately provided in the inappropriate overrides, and the specific reasons the overrides were considered inappropriate.Results Approximately 17.2% (n = 35.4/206) of NFM alerts were inappropriately overridden. Non-oral NFM alerts were more likely to be inappropriately overridden compared to orals. Alerts overridden with "blank" reasons were more likely to be inappropriate. The failure to first try a formulary alternative was the most common reason for alerts being overridden inappropriately.Conclusion Approximately 1 in 5 NFM alert overrides are overridden inappropriately. Future research should evaluate the impact of mandating a valid override reason and adding a list of formulary alternatives to each NFM alert; we speculate these NFM alert features may decrease the frequency of inappropriate overrides.
Author(s): Her QL, Amato MG, Seger DL, Beeler PE, Slight SP, Dalleur O, Dykes PC, Gilmore JF, Fanikos J, Fiskio JM, Bates DW
Publication type: Article
Publication status: Published
Journal: Journal of the American Medical Informatics Association
Year: 2016
Volume: 23
Issue: 5
Pages: 924-933
Print publication date: 01/09/2016
Online publication date: 21/03/2016
Acceptance date: 27/10/2015
ISSN (print): 1067-5027
ISSN (electronic): 1527-974X
Publisher: Oxford University Press
URL: https://doi.org/10.1093/jamia/ocv181
DOI: 10.1093/jamia/ocv181
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