Abstract 10918: Use of Mobile Health Technology in the Assessment of Statin-Associated Muscle Symptoms (SAMS)

Abstract

Background: Statins are the cornerstone pharmacotherapy for lowering LDL-C and reducing risk of ASCVD. However, statin initiation and adherence are limited by statin-associated muscle symptoms (SAMS), posing significant clinical and public health dilemmas. Mobile health (mHealth) tools offer novel ways to assess real-time symptom data and share them back with patients to facilitate shared decision-making. Objective: To assess the feasibility and usability of an automated, text-message-based SAMS symptom-tracking platform to longitudinally track SAMS in patients who previously experienced muscle symptoms while on statin therapy. Methods: We enrolled 19 patients from 2 clinics at a single health system (Johns Hopkins; Baltimore, MD) and recorded baseline demographics, statin history and indication, perceptions of SAMS, and technology use via an online survey. Quantitative SAMS scores were gathered via daily text messages, and qualitative symptom data were collected in weekly text messages. Monthly symptom reports were sent to select participants via email on study days 30, 60 and 90. Upon study completion, participants reported perceptions of the study, the mHealth platform, and study measures via an online exit survey. Results: A total of 18 patients (aged 59.3 [SD 14.5] years, 67% women) collected data, and 15 patients completed the 90-day study protocol. Overall response rate to text messages was 91.5% (92.2% for daily SAMS messages, 86.0% for weekly muscle symptom prompts). Patients reported a statin adherence of 70%. Nine patients reported intolerable muscle symptoms at least once during the study, and intolerable symptom scores represented 3% of all reported symptom scores. Patients reported overall satisfaction with the study and found the SAMS scores helpful. Conclusions: Patients with previously reported SAMS successfully engaged with a text-message-based symptom-tracking platform with high interactivity and acceptability. This study demonstrates the feasibility and usability of an automated mHealth platform for longitudinally tracking SAMS in patients on statin therapy, and may provide a means for improving shared decision making to tailor statin therapy and improve adherence.