Abstract

Background: Therapy for aortic stenosis (AS) is quickly evolving, with treatment options expanded by transcatheter aortic valve replacement (TAVR). The complexity of information patients need to make value-concordant decisions highlights the need for accessible, acceptable, and unbiased decision aids (DAs) for patients considering AS treatment. Methods: Using a rapid-development process adapted from our team’s earlier work creating DAs for ICD and LVAD candidates, and guided by International Patient Decision Aid Standards (IPDAS), we created decision support materials for AS patients. This process included simultaneous 1) qualitative assessments of decision support needs & experience among TAVR recipients, 2) alpha testing iterative versions of paper DAs with patients to assess for accessibility & bias, and 3) assessment of clinical accuracy and usability of DAs with clinicians through individual feedback and expert panel consensus (Figure 1). Results: Over a 14 month period, we created two paper and two video DAs (corresponding to high or non-operative surgical risk), including input from interviews with 17 patients and 3 caregivers, 6 clinician reviews, and 4 expert panel assessments. Patient/caregiver feedback included DA usability and when it should be introduced into the clinical process. Clinician feedback focused on expected valve durability, procedural risks, and clinical accuracy. While most patients and clinicians expressed enthusiasm about TAVR, they described subpopulations of AS patients for whom the decision of whether to accept TAVR should be weighed within the context of clinical uncertainty about expected benefits (i.e. patients with prohibitive surgical risk and multi-comorbid conditions) or valve durability (i.e. surgery candidates). The DAs are currently available on the American College of Cardiology’s patient-facing CardioSmart website. Conclusion: AS treatment options are technically complex and have patient-centered trade-offs. Developing and adapting patient decision aids for AS can improve the decision making process. This development process offers lessons for improving shared decision making for evolving therapies for other life-threatening disease.

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