Key result
The CARATV2.0 decision support tool significantly increased the proportion of patients with atrial fibrillation receiving antithrombotic therapy from 77.2% at admission to 89.2% at discharge.
Why the study?
Does a computerised decision support tool (CARATV2.0) improve antithrombotic prescribing rates in patients aged ≥ 65 years with atrial fibrillation?
Cohort (n=251)
No
Does a computerised decision support tool (CARATV2.0) improve antithrombotic prescribing rates in patients aged ≥ 65 years with atrial fibrillation?
Absolute Event Rate: 89.2% vs 77.2%
p-value: p=<0.001
A computerised decision support tool significantly increased the proportion of elderly patients with atrial fibrillation receiving appropriate antithrombotic therapy at hospital discharge.
May enhance antithrombotic prescribing in elderly AF inpatients; leaves open need for randomized confirmation before practice change.
BACKGROUND: The decision-making process for stroke prevention in atrial fibrillation (AF) requires a comprehensive assessment of risk vs. benefit and an appropriate selection of antithrombotic agents (e.g., warfarin, non-vitamin K antagonist oral anticoagulants [NOACs]). The aim of this pilot-test was to examine the impact of a customised decision support tool - the Computerised Antithrombotic Risk Assessment Tool (CARATV2.0) using antithrombotic therapy on a cohort of patients with AF. METHODS: In this prospective interventional study, 251 patients with AF aged ≥ 65 years, admitted to a teaching hospital in Australia were recruited. CARATV2.0 generated treatment recommendations based on patient medical information. Recommendations were provided to prescribers for consideration. RESULTS: At baseline (admission), 30.3% of patients were prescribed warfarin, 26.7% an antiplatelet, 8.4% apixaban, 8.0% rivaroxaban, 3.6% dabigatran. CARATV2.0 recommended a change of therapy for 153 (61.0%) patients. Through recommendations of CARATV2.0, at discharge, 40.2% of patients were prescribed warfarin, 17.7% antiplatelet, 14.3% apixaban, 10.4% rivaroxaban, 5.6% dabigatran. Overall, the proportion of patients receiving an antithrombotic on discharge increased significantly from baseline (admission) (baseline 77.2% vs. 89.2%; p < 0.001). Prescribers moderately agreed with CARATV2.0's recommendations (kappa = 0.275, p < 0.001). Practical medication safety issues were cited as major reasons for not accepting a desire to continue therapy with CARATV2.0's recommendations. Factors predicting the prescription of antiplatelets rather than anticoagulants included higher bleeding risk and high risk of falls. An inter-speciality difference in therapy selection was detected. CONCLUSIONS: This decision support tool can help optimise the use of antithrombotic therapy in patients with AF by considering risk versus benefit profiles and rationalising treatment selection. (Cardiol J 2017; 24, 2: 176-187).
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Wang et al. (2017) conducted a cohort in Atrial fibrillation (n=251). Computerised Antithrombotic Risk Assessment Tool Version 2 (CARATV2.0) vs. Baseline (pre-intervention) therapy was evaluated on Proportion of patients receiving an antithrombotic on discharge (p=<0.001). The CARATV2.0 decision support tool significantly increased the proportion of patients with atrial fibrillation receiving antithrombotic therapy from 77.2% at admission to 89.2% at discharge.
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