The Atrial Fibrillation Health Literacy Information Technology Trial: Pilot Trial of a Mobile Health App for Atrial Fibrillation.

BACKGROUND: Atrial fibrillation (AF) is a common arrhythmia that adversely affects health-related quality of life (HRQoL). We conducted a pilot trial of individuals with AF using a smartphone to provide a relational agent as well as rhythm monitoring. We employed our pilot to measure acceptability and adherence and to assess its effectiveness in improving HRQoL and adherence. OBJECTIVE: This study aims to measure acceptability and adherence and to assess its effectiveness to improve HRQoL and adherence. METHODS: Participants were recruited from ambulatory clinics and randomized to a 30-day intervention or usual care. We collected baseline characteristics and conducted baseline and 30-day assessments of HRQoL using the Atrial Fibrillation Effect on Quality of Life (AFEQT) measure and self-reported adherence to anticoagulation. The intervention consisted of a smartphone-based relational agent, which simulates face-to-face counseling and delivered content on AF education, adherence, and symptom monitoring with prompted rhythm monitoring. We compared differences in AFEQT and adherence at 30 days, adjusted for baseline values. We quantified participants' use and acceptability of the intervention. RESULTS: A total of 120 participants were recruited and randomized (59 to control and 61 to intervention) to the pilot trial (mean age 72.1 years, SD 9.10; 62/120, 51.7% women). The control group had a 95% follow-up, and the intervention group had a 93% follow-up. The intervention group demonstrated significantly higher improvement in total AFEQT scores (adjusted mean difference 4.5; 95% CI 0.6-8.3; P=.03) and in daily activity (adjusted mean difference 7.1; 95% CI 1.8-12.4; P=.009) compared with the control between baseline and 30 days. The intervention group showed significantly improved self-reported adherence to anticoagulation therapy at 30 days (intervention 3.5%; control 23.2%; adjusted difference 16.6%; 95% CI 2.8%-30.4%; P<.001). Qualitative assessments of acceptability identified that participants found the relational agent useful, informative, and trustworthy. CONCLUSIONS: Individuals randomized to a 30-day smartphone intervention with a relational agent and rhythm monitoring showed significant improvement in HRQoL and adherence. Participants had favorable acceptability of the intervention with both objective use and qualitative assessments of acceptability.

Mind the gap: Deficits in fundamental disease-specific knowledge in atrial fibrillation.

BACKGROUND: Patient success with atrial fibrillation (AF) requires adequate health literacy to understand the disease and rationale for treatment. We hypothesized that individuals receiving treatment for AF would have increased knowledge about AF and that such knowledge would be modified by education and income. METHODS: We enrolled adults with AF receiving anticoagulation at ambulatory clinic sites. Participants responded to survey items encompassing the definitions of AF and stroke, the rationale for anticoagulation, and an estimation of their annual stroke risk. We examined responses in relation to household income and education in multivariable-adjusted models. RESULTS: We enrolled 339 individuals (age 72.0 ±â€¯10.1; 43% women) with predominantly lower annual income ($20-49,999, n = 99, 29.2%) and a range of educational attainment (high school or vocational, n = 117, 34.5%). Participants demonstrated moderate AF knowledge (1.7 ±â€¯0.6; range 0-2) but limited knowledge about anticoagulation (1.3 ±â€¯0.7; range 0-3) or stroke (1.5 ±â€¯0.8; range 0-3). Income was not associated with improvement in AF (P = 0.32 for trend), anticoagulation (P = 0.27) or stroke knowledge (P = 0.26). Individuals with bachelor or graduate degree had greater AF (1.8 ±â€¯0.5) and stroke (1.6 ±â€¯0.8) knowledge relative to those with high school or vocational training (1.4 ±â€¯0.7 and 1.2 ±â€¯0.9; P ≪ 0.01, both estimates). Education was not associated with understanding the rationale for anticoagulation. Most participants (230, 68%) estimated their annual stroke risk as ≥15%. CONCLUSIONS: We identified consistent, fundamental gaps in disease-specific knowledge in a cohort of adults receiving treatment for non-valvular AF. Improved patient understanding of this complex and chronic disease may enhance shared decision making, patient engagement, anticoagulation adherence, and clinical outcomes in AF.

Association of income and health-related quality of life in atrial fibrillation.

Objective: Health-related quality of life (HRQoL) is a patient-centred benchmark promoted by clinical guidelines in atrial fibrillation (AF). Income is associated with health outcomes, but how income effects HRQoL in AF has limited investigation. Methods: We enrolled a convenience cohort with AF receiving care at a regional healthcare system and assessed demographics, medical history, AF treatment, income, education and health literacy. We defined income as a categorical variable (<$20 000; $20 000-$49 999; $50 000-$99 999; >$100 000). We used two complementary HRQoL measures: (1) the atrial fibrillation effect on quality of life (AFEQT), measuring composite and domain scores (daily activity, symptoms, treatment concerns, treatment satisfaction; range 0-100); (2) the 12-item Short Form Survey (SF-12), measuring general HRQoL with physical and mental health domains (range 0-100). We related income to HRQoL and adjusted for relevant covariates. Results: In 295 individuals with AF (age 71±10, 40% women), we observed significant differences in HRQoL by income. Higher mean composite AFEQT scores were observed for higher income groups: participants with income <$20 000 had the lowest HRQoL (n=35, 68.2±21.4), and those with income >$100 000 had the highest HRQoL (n=64, 81.9±17.0; p=0.04). We also observed a significant difference by income in the AFEQT daily activity domain (p=0.02). Lower income was also associated with lower HRQoL in the mental health composite score of the SF-12 (59.7±21.5, income <$20 000 vs 79.3±16.3, income >$100 000; p<0.01). Conclusion: We determined that income was associated with HRQoL in a cohort with prevalent AF. Given the marked differences, we consider income as essential for understanding patient-centred outcomes in AF.