LAUSR

Introduction In addition to a large body of research that shows decision aids (DA) are associated with better patient experiences for many health decisions, a multi-site randomized controlled trial that compared a DA for left ventricular assist device (LVAD) placement with standard LVAD education found that the DA significantly increased patient knowledge and satisfaction with life after implant. However, little evidence exists regarding best practices for implementation of a DA in real-world cardiovascular care. This project evaluated DA implementation at eight U.S. hospitals with a focus on increasing shared decision-making (SDM) and DA use. Methods Participating received a tailored implementation plan and SDM training. To understand the extent to which SDM enhanced behaviors were implemented, LVAD coordinators completed a 10-item Implementation Fidelity Checklist (score 0-10) for each patient. The primary outcome, reach to patients, is calculated by dividing the number of checklists received by the total number of patients receiving pre-LVAD education during evaluation. DA fidelity is calculated using LVAD coordinator self-report of the patient encounter on the Fidelity Checklist. Results Across sites, 607 patients received a DA from September 2018-December 2019. Reach ranged from 29.3%-87.9% of patients across sites with an overall reach of 58.2% and average Fidelity Checklist score of 8.4 (range 6.0-10.0). Over one-third (37.5%) of sites achieved overall reach > 80% indicating a high level of implementation success. Almost half of patients reviewed the DA with a caregiver (48.7%). Clinician users of the decision aid believed additional language translations of the DA and inclusion of institution-specific and personalized risk profiles would promote long-term sustainability of the DA at their institution. Conclusion Findings demonstrate that DAs and SDM can be implemented into diverse cardiovascular care settings with sustained use by clinicians, patients, and caregivers. Future work will evaluate implementation of new DA features requested by clinicians.