DIGITAL HEALTH SOLUTIONS IN ATRIAL FIBRILLATION MANAGEMENT: ENHANCING DETECTION, MONITORING, AND PATIENT OUTCOMES
Abstract
Introduction and Objective: Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with significant morbidity and mortality. Rapid advances in artificial intelligence (AI), wearable devices, and mobile health (mHealth) technologies hold promise to improve AF risk prediction, diagnosis, and patient management. This narrative review aims to synthesize current evidence on the integration of these innovative tools in AF care, with a focus on technological capabilities, patient engagement, and public health implications.
Review Methods: A narrative review was conducted, analyzing peer-reviewed articles, clinical trials, and authoritative reports published between 2014 and 2023. Sources were identified through comprehensive database searches using keywords related to AF, AI, digital health, and health equity. The review integrates interdisciplinary insights from cardiology, digital technology, and public health literature.
State of Knowledge: Recent studies demonstrate that AI algorithms applied to electrocardiograms (ECGs) and wearable sensor data can enhance early detection and risk stratification of AF. Mobile health tools foster patient engagement and improve self-management through real-time monitoring and education. However, challenges remain related to data privacy, algorithmic bias, and equitable access to these technologies. Public health strategies must consider social determinants of health to maximize benefits and reduce disparities in AF outcomes.
Conclusion: Innovative digital technologies offer transformative potential in AF management and public health. Future research should address existing gaps, focusing on validation in diverse populations, ethical implementation, and strategies to ensure health equity. Multidisciplinary collaboration is essential to harness these tools effectively and improve cardiovascular health outcomes globally.
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