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Optimization of drugdrug interaction alert rules in a pediatric hospital's electronic health record system using a visual analytics dashboard

Optimization of drugdrug interaction alert rules in a pediatric hospital's electronic health... Objective To develop and evaluate an electronic dashboard of hospital-wide electronic health record medication alerts for an alert fatigue reduction quality improvement project.Methods We used visual analytics software to develop the dashboard. We collaborated with the hospital-wide Clinical Decision Support committee to perform three interventions successively deactivating clinically irrelevant drugdrug interaction (DDI) alert rules. We analyzed the impact of the interventions on care providers’ and pharmacists’ alert and override rates using an interrupted time series framework with piecewise regression.Results We evaluated 2 391 880 medication alerts between January 31, 2011 and January 26, 2014. For pharmacists, the median alert rate prior to the first DDI deactivation was 58.74 alerts/100 orders (IQR 54.9860.48) and 25.11 alerts/100 orders (IQR 23.4526.57) following the three interventions (p<0.001). For providers, baseline median alert rate prior to the first round of DDI deactivation was 19.73 alerts/100 orders (IQR 18.6620.24) and 15.11 alerts/100 orders (IQR 14.4415.49) following the three interventions (p<0.001). In a subgroup analysis, we observed a decrease in pharmacists’ override rates for DDI alerts that were not modified in the system from a median of 93.06 overrides/100 alerts (IQR 91.9694.33) to 85.68 overrides/100 alerts (IQR 84.2987.15, p<0.001). The medication serious safety event rate decreased during the study period, and there were no serious safety events reported in association with the deactivated alert rules.Conclusions An alert dashboard facilitated safe rapid-cycle reductions in alert burden that were temporally associated with lower pharmacist override rates in a subgroup of DDIs not directly affected by the interventions; meanwhile, the pharmacists’ frequency of selecting the ‘cancel’ option increased. We hypothesize that reducing the alert burden enabled pharmacists to devote more attention to clinically relevant alerts. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the American Medical Informatics Association Oxford University Press

Optimization of drugdrug interaction alert rules in a pediatric hospital's electronic health record system using a visual analytics dashboard

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References (24)

Publisher
Oxford University Press
Copyright
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
ISSN
1067-5027
eISSN
1527-974X
DOI
10.1136/amiajnl-2013-002538
pmid
25318641
Publisher site
See Article on Publisher Site

Abstract

Objective To develop and evaluate an electronic dashboard of hospital-wide electronic health record medication alerts for an alert fatigue reduction quality improvement project.Methods We used visual analytics software to develop the dashboard. We collaborated with the hospital-wide Clinical Decision Support committee to perform three interventions successively deactivating clinically irrelevant drugdrug interaction (DDI) alert rules. We analyzed the impact of the interventions on care providers’ and pharmacists’ alert and override rates using an interrupted time series framework with piecewise regression.Results We evaluated 2 391 880 medication alerts between January 31, 2011 and January 26, 2014. For pharmacists, the median alert rate prior to the first DDI deactivation was 58.74 alerts/100 orders (IQR 54.9860.48) and 25.11 alerts/100 orders (IQR 23.4526.57) following the three interventions (p<0.001). For providers, baseline median alert rate prior to the first round of DDI deactivation was 19.73 alerts/100 orders (IQR 18.6620.24) and 15.11 alerts/100 orders (IQR 14.4415.49) following the three interventions (p<0.001). In a subgroup analysis, we observed a decrease in pharmacists’ override rates for DDI alerts that were not modified in the system from a median of 93.06 overrides/100 alerts (IQR 91.9694.33) to 85.68 overrides/100 alerts (IQR 84.2987.15, p<0.001). The medication serious safety event rate decreased during the study period, and there were no serious safety events reported in association with the deactivated alert rules.Conclusions An alert dashboard facilitated safe rapid-cycle reductions in alert burden that were temporally associated with lower pharmacist override rates in a subgroup of DDIs not directly affected by the interventions; meanwhile, the pharmacists’ frequency of selecting the ‘cancel’ option increased. We hypothesize that reducing the alert burden enabled pharmacists to devote more attention to clinically relevant alerts.

Journal

Journal of the American Medical Informatics Association – Oxford University Press

Published: Mar 15, 2015

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