Cluster-randomized, controlled trial of computer-based decision support for selecting long-term anti-thrombotic therapy after acute ischaemic stroke

Background: Identifying the appropriate long-term anti-thrombotic therapy following acute ischaemic stroke is a challenging area in which computer-based decision support may provide assistance. Aim: To evaluate the influence on prescribing practice of a computer-based decision support system (CDSS) that provided patient-specific estimates of the expected ischaemic and haemorrhagic vascular event rates under each potential anti-thrombotic therapy. Design: Cluster-randomized controlled trial. Methods: We recruited patients who presented for a first investigation of ischaemic stroke or TIA symptoms, excluding those with a poor prognosis or major contra indication to anticoagulation. After observation of routine prescribing practice (6 months) in each hospital, centres were randomized for 6 months to either control (routine practice observed) or intervention (practice observed while the CDSS provided patient-specific information). We compared, between control and intervention centres, the risk reduction (estimated by the CDSS) in ischaemic and haemorrhagic vascular events achieved by long-term anti-thrombotic therapy, and the proportions of subjects prescribed the optimal therapy identified by the CDSS. Results: Sixteen hospitals recruited 1952 subjects. When the CDSS provided information, the mean relative risk reduction attained by prescribing increased by 2.7 percentage units (95%CI -0.3 to 5.7) and the odds ratio for the optimal therapy being prescribed was 1.32 (0.83 to 1.80). Some 55% (5/9) of clinicians believed the CDSS had influenced their prescribing. Conclusions: Cluster-randomized trials provide excellent frameworks for evaluating novel clinical management methods. Our CDSS was feasible to implement and acceptable to clinicians, but did not substantially influence prescribing practice for anti-thrombotic drugs after acute ischaemic stroke.