Point-of-Care Cluster Randomized Trial in Stroke Secondary Prevention Using Electronic Health Records

Abstract

Stroke represents a long-term condition that requires ongoing preventive medical care to reduce the risk of recurrence of stroke. During the first 10 years after stroke, there is nearly 40% cumulative risk of recurrence.1 Secondary prevention after stroke should include interventions to manage and monitor vascular risk factors including blood pressure (BP), lipid-lowering drugs, and antithrombotic treatment where appropriate, as well as efforts to control overweight, increase exercise, and reduce alcohol and smoking.2 Audits have revealed major deficiencies in stroke secondary prevention with ≤40% subjects achieving a systolic BP of <140 mm Hg at 6 months poststroke.3 Failure to use effective treatments is associated with considerable morbidity, mortality, and healthcare costs. 4 There is a need for more effective intervention strategies to improve poststroke standards of care for secondary prevention that are relevant to routine clinical practice.Advances in electronic health records (EHRs) offer important opportunities for more efficient implementation of clinical and cluster trials.5 Using EHRs from a large clinical database as a sampling frame, and source of data to evaluate trial outcomes, might offer several potential advantages, enabling the recruitment of participants and assessment of Background and Purpose-The aim of this study was to evaluate whether the remote introduction of electronic decision support tools into family practices improves risk factor control after first stroke. This study also aimed to develop methods to implement cluster randomized trials in stroke using electronic health records. Methods-Family practices were recruited from the UK Clinical Practice Research Datalink and allocated to intervention and control trial arms by minimization. Remotely installed, electronic decision support tools promoted intensified secondary prevention for 12 months with last measure of systolic blood pressure as the primary outcome. Outcome data from electronic health records were analyzed using marginal models.

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