Development and Validation of a QTc-Prolongation Risk Score to Optimize
Interruptive Medication Alerts
Abstract
Introduction: Drug-drug interaction (DDI) warnings are employed in many
institutions when more than one QTc-prolonging medication is prescribed;
however, this leads to alert fatigue where alerts are frequently
overridden by clinicians due to patient non-specificity or low risk.
This study aimed at reducing alert fatigue through developing a custom
alert triggered by a patient-specific QTc-prolongation risk score, and
validating it against database-driven DDI warnings for QTc prolongation.
Methods and Results: Between November 23, 2019 and January 31, 2020,
inpatients with a baseline and a follow-up 12-lead ECG reading within 14
days were identified. Each time a QTc-prolonging medication order was
signed or verified, the QTc-prolongation risk score was calculated in
the electronic health record (EHR), triggering a custom alert in the
background. Follow-up 12-lead ECG readings were used to calculate
sensitivity and specificity for both the custom alert and the DDI
warning. A total of 100 patients had a risk score calculation and were
included in our analysis, representing 521 custom alerts and 449 DDI
warnings. The preliminary QTc-prolongation risk score did not achieve a
reduction in false positive alerts with a cutoff of 10 points. A
multiple logistic regression was performed to re-arrange the components
and optimize the risk score. Conclusion: Our adjusted QTc-prolongation
risk score, with a cutoff of 5 points, achieved a specificity of 66%
and a negative predictive value of 83%. These results will allow us to
integrate the risk score into the EHR as a guidance tool to predict
QTc-prolongation.