AI-Enabled Remote Patient Monitoring for Heart Disease: A Conceptual Framework for Clinical Integration

Remote patient monitoring (RPM) has become an important approach for managing patients with heart disease. This paper reviews current evidence on RPM and its impact on outcomes such as mortality and hospitalization. While RPM improves early detection and intervention, challenges remain, including data overload and integration into clinical workflows. To address these issues, this paper proposes an AI-enabled framework that integrates data collection, intelligent analysis, and clinical decision support. The framework aims to support earlier detection of risk and more effective clinical responses. Key considerations related to ethics, data privacy, and implementation within national digital health initiatives are also discussed. Overall, integrating AI into RPM offers a practical path toward more proactive and patient-centered care.