Implementation of an Algorithm- and Multi-professional Team-supported Strategy to Improve Lipid Management of Patients With Atherosclerotic Cardiovascular Disease

This is a randomized, controlled, collaborative, multicenter, pilot implementation science study evaluating the hypothesis that algorithm- and multi-professional team-supported lipid management reduces low density lipoprotein-cholesterol (LDL-C) compared with usual care in patients with atherosclerotic cardiovascular disease (ASCVD).

OPTIMIZE-ASCVD is a randomized, controlled, collaborative, open-label, multicenter pilot implementation science study evaluating the hypothesis that algorithm- (Appendix A) and multi-professional team-supported lipid management reduces LDL-C compared with usual care in patients with ASCVD. Approximately 100 participants will be randomized (1:1). * Participant preference for injectable vs oral lipid therapy will be recorded at baseline. * Participants allocated to algorithm-and multi-professional team-supported lipid management will be evaluated by a physician and prescribed lipid therapy which aims to achieve LDL-C target without titration. Participants will be contacted by a pharmacist to provide education about the medication and support any access issues. * Participants allocated to usual care will be referred for management by their usual care provider who will receive a summary of guideline recommendations The study will include decentralized clinical trial features including use of local, Clinical Laboratory Improvement Amendments (CLIA)-certified laboratories for blood tests, use of data extracted from the electronic medical record (EMR), electronic collection of patient-reported outcomes (PRO) and remote conduct of study activities. As an open label study with both strategy groups receiving GDMT, no Data and Safety Monitoring Committee will be convened. Study leadership will monitor aggregate data during the trial and may modify the sample size and/or cap enrollment of subgroups to ensure consistency with design assumptions.