Key result
Implementation of a clinical decision support algorithm increased the rate of oral anticoagulation prescriptions offered to eligible older adults with AF and prior stroke/TIA from 87% to 100%.
Why the study?
There was an identified underuse of oral anticoagulation among individuals over age 65 with AF, prompting evaluation of prescribing at hospital discharge or post-hospitalization follow-up after CVA or TIA.
Does an evidence-based clinical decision support algorithm improve the prescription rate of oral anticoagulation in patients aged 65 or older with atrial fibrillation and prior stroke or TIA?
Does an evidence-based clinical decision support algorithm improve the prescription rate of oral anticoagulation in patients aged 65 or older with atrial fibrillation and prior stroke or TIA?
Absolute Event Rate: 100% vs 87%
Implementation of a clinical decision support algorithm successfully increased the rate of oral anticoagulation prescription at discharge for older adults with atrial fibrillation and prior stroke or TIA to 100%.
Persistent OAC underuse in older AF patients post-CVA/TIA warrants discharge protocol improvements; leaves open questions on scalable intervention efficacy.
Background and Purpose: There was an identified underuse of oral anticoagulation (OAC) among individuals who are over the age of 65 with atrial fibrillation (AF). The purpose of this DNP project was to identify patients aged 65 or older with a diagnosis of AF and a cerebral vascular accident (CVA) or transient ischemic attack (TIA), not on current OAC to determine if a prescription was provided to them at time of discharge from the hospital or during a post-hospitalization follow up appointment with their primary care or cardiology provider. Method: A retrospective medical record review was used over a three-month period in 2016 to determine clinical practice of providers prescribing OAC to patient ages 65 and older with AF and known stroke or TIA diagnosis. An evidence-based clinical decision support algorithm for the treatment of those with AF who had a CVA or TIA was implemented over a 12-week period at a large, independent hospital using the ACE Star Model of Knowledge Transformation, a framework for putting evidence-based processes into operation. The risk for stroke and bleeding was calculated using the CHA2DS2-VASc score and HAS-BLED tools. Following the implementation period, the same three-month span was selected in 2017 for a retrospective record review to determine the effectiveness of the intervention. Results: A total of 27 patients were included in this project. The number of eligible patients who were offered prescriptions for OAC increased from 87% in 2016 to 100% in 2017. Conclusion: The intervention resulted in the desired change towards evidence-based practice among providers. Following implementation of the project discharging providers not only included neurology’s recommendations in their discharge notes, but also provided prescriptions to eligible patients rather than leaving it to the patient’s primary care provider to initiate.
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Cecily Smith (2019) studied Atrial fibrillation and prior stroke or TIA (n=27). Evidence-based clinical decision support algorithm vs. Pre-implementation standard of care (2016) was evaluated on Eligible patients offered prescriptions for oral anticoagulation. Implementation of a clinical decision support algorithm increased the rate of oral anticoagulation prescriptions offered to eligible older adults with AF and prior stroke/TIA from 87% to 100%.
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