Journal Article

Adherence to drug—drug interaction alerts in high-risk patients: a trial of context-enhanced alerting

Jon D Duke, Xiaochun Li and Paul Dexter

in Journal of the American Medical Informatics Association

Published on behalf of American Medical Informatics Association

Volume 20, issue 3, pages 494-498
Published in print May 2013 | ISSN: 1067-5027
Published online November 2012 | e-ISSN: 1527-974X | DOI: https://dx.doi.org/10.1136/amiajnl-2012-001073
Adherence to drug—drug interaction alerts in high-risk patients: a trial of context-enhanced alerting

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  • Medical Statistics and Methodology
  • Bioinformatics and Computational Biology
  • Biomathematics and Statistics

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Abstract

Objective Drug–drug interaction (DDI) alerting is an important form of clinical decision support, yet physicians often fail to attend to critical DDI warnings due to alert fatigue. We previously described a model for highlighting patients at high risk of a DDI by enhancing alerts with relevant laboratory data. We sought to evaluate the effect of this model on alert adherence in high-risk patients.

Methods A 6-month randomized controlled trial involving 1029 outpatient physicians was performed. The target interactions were all DDIs known to cause hyperkalemia. Alerts in the intervention group were enhanced with the patient's most recent potassium and creatinine levels. The control group received unmodified alerts. High -risk patients were those with baseline potassium >5.0 mEq/l and/or creatinine ≥1.5 mg/dl (132 μmol/l).

Results We found no significant difference in alert adherence in high-risk patients between the intervention group (15.3%) and the control group (16.8%) (p=0.71). Adherence in normal risk patients was significantly lower in the intervention group (14.6%) than in the control group (18.6%) (p<0.01). In neither group did physicians increase adherence in patients at high risk.

Conclusions Physicians adhere poorly to hyperkalemia-associated DDI alerts even in patients with risk factors for a clinically significant interaction, and the display of relevant laboratory data in these alerts did not improve adherence levels in the outpatient setting. Further research is necessary to determine optimal strategies for conveying patient-specific DDI risk.

Keywords: Decision Support Systems, Clinical; Drug Interactions; Drug Therapy, Computer Assisted; Medical Order Entry Systems; Reminder Systems

Journal Article.  3562 words.  Illustrated.

Subjects: Medical Statistics and Methodology ; Bioinformatics and Computational Biology ; Biomathematics and Statistics

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