An automated clinical alert system for newly-diagnosed atrial fibrillation

Objective Clinical decision support systems that notify providers of abnormal test results have produced mixed results. We sought to develop, implement, and evaluate the impact of a com-puter-based clinical alert system intended to improve atrial fibrillation stroke prophylaxis, and identify reasons providers do not implement a guideline-concordant response. Materials and Methods We conducted a cohort study with historical controls among patients at a tertiary care hospital. We developed a decision rule to identify newly-diagnosed atrial fibrillation, automatically notify providers, and direct them to online evidence-based management guidelines.We tracked all notifications from December 2009 to February 2010 (notification period) and applied the same decision rule to all patients from December 2008 to February 2009 (control period). Primary outcomes were accuracy of notification (confirmed through chart review) and prescription of warfarin within 30 days. Results During the notification period 604 notifications were triggered, of which 268 (44%) were confirmed as newly-diagnosed atrial fibrillation. The notifications not confirmed as newly-diagnosed involved patients with no recent electrocardiogram at our institution. Thirty-four of 125 high-risk patients (27%) received warfarin in the notification period, compared with 34 of 94 (36%) in the control period (odds ratio, 0.66 [95% CI, 0.37-1.17]; p = 0.16). Common reasons to not prescribe warfarin (identified from chart review of 151 patients) included upcoming surgical procedure, choice to use aspirin, and discrepancy between clinical notes and the medication record. Conclusions An automated system to identify newly-diagnosed atrial fibrillation, notify providers, and encourage access to management guidelines did not change provider behaviors.