Digital Health and Remote Patient Monitoring: Integrating Wearable Biosensors, Telemedicine, Artificial Intelligence, and Clinical Decision-Support Systems for Chronic Disease Management

Abstract

Chronic diseases such as type 2 diabetes mellitus, hypertension, heart failure, COPD, and chronic kidney disease remain leading drivers of global morbidity, mortality, and healthcare expenditure. Traditional episodic, reactive care models fail to capture transient physiological decompensations, nocturnal hemodynamic shifts, and subclinical glycemic fluctuations, resulting in preventable acute exacerbations and hospitalizations. This review synthesizes current cross-disciplinary evidence on the digital health ecosystem for chronic disease management, focusing on the integration of wearable biosensors, telemedicine architecture, artificial intelligence (AI), and clinical decision-support systems (CDSS). Wearable biosensors including continuous glucose monitors, photoplethysmography, single-lead electrocardiography, and non-invasive biofluid sensors enable high-frequency, longitudinal physiological data acquisition with clinically validated accuracy. A five-layer telecommunication architecture, anchored in HL7 FHIR interoperability standards, supports secure data transmission, normalization, and storage. AI and machine learning methodologies, particularly Long Short-Term Memory recurrent neural networks and gradient-boosted models, analyze time-series telemetry to detect physiological drift and forecast decompensation days before clinical presentation. SMART on FHIR and CDS Hooks frameworks embed actionable recommendations directly within Electronic Health Record workflows, reducing alert fatigue and administrative burden. Real-world evidence reveals a biphasic RPM utilization curve: an initial post-initiation spike in outpatient, emergency, and inpatient encounters, followed by sustained long-term reductions in acute care utilization. Economic evaluations demonstrate favorable cost-effectiveness when RPM is targeted at high-risk, multi-morbid cohorts, though methodological heterogeneity persists. Key implementation challenges include age-related digital literacy disparities, workflow bottlenecks, and ambiguous clinical role allocation. Strategic priorities encompass accessible interface design, cellular-enabled devices, standardized economic reporting, and explicit protocol governance to ensure equitable, sustainable, and clinically effective remote monitoring programs.