Development and Validation of a QTc-Prolongation Risk Score to Optimize Interruptive Medication Alerts

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.