Abstract 17246: Using Alerts vs Automated Tools to Better Document CHADS2-VASc Scores in Patients Hospitalized With Atrial Fibrillation

Abstract

Introduction: Atrial fibrillation (Afib) is the most common cardiac arrhythmia in the United States and a significant burden on our healthcare system. Currently as many as six million people in the United States carry a diagnosis of Afib, with that number likely increasing as our population ages and our methods of detection improve. Accurate diagnosis and risk stratification are imperative as these patients may have stroke rates as high as 20% annually. Comprehensive documentation of the CHADS2-VASc score can better determine the need for Anticoagulation for patients hospitalized with Afib Hypothesis: What is the rate of recording of CHADS2-VASc scores in patients admitted to House Staff and Hospitalist teams and what interventions would lead to better data gathering: a best practice alert or an automated diagnosis tool in the Electronic Medical Record (EMR). Methods: At The University of Chicago Medical Center, attendings on the cardiology service and hospitalists documented CHADS2-VASc without intervention. Then the response rate was measured after implementing a best practice alert, or soft stop dialog box in the EMR. Later for Hospital Medicine teams, an auto diagnosis tool, a hard stop auto-generated in the note, was added to the EMR. Results: Over the course of three years (January 2018 to December 2021) CHADS2-VASc score was charted an average of 1% of the time for hospitalists and 7% of the time for House Staff Cardiology. After implementing the EMR Best practice alert (January 2022 to January 2023 for House Staff and January 2022 to November 2022 for Hospitalists) these rates increased to 19% (p <0.0001) for the hospitalist team and 54% for the House Staff Cardiology team (p<0.00001). With the Auto diagnosis tool (November 2022 to January 2023) the rate increased from 19% to 56% (p <1x10 -7 ) Conclusions: As our data shows, CHADS2-VASc scores recording rates remained low among both cardiology and medicine attendings. However, an EMR generated alert increased responses while an auto diagnosis tool increased documentation even more. This demonstrates the effectiveness of EMR tools. This improvement in adherence should also lead to better rates of prescribing Anticoagulation to patients with higher risk.