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The frequency of inappropriate nonformulary medication alert overrides in the inpatient setting

Lookup NU author(s): Professor Sarah SlightORCiD


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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.

Publication metadata

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


DOI: 10.1093/jamia/ocv181


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