The Paradigmatic Shift in Chronic Disease Management: A Longitudinal Analysis of Sensor-Based Monitoring, IoMT Architecture, and Clinical Outcomes

The global healthcare infrastructure is currently undergoing a transformative redirection, transitioningfrom a reactive, episodic model of care toward a proactive, continuous, and data-driven paradigm. Thisevolution is necessitated by the burgeoning epidemiological burden of chronic conditions—specificallydiabetes mellitus, congestive heart failure, and chronic obstructive pulmonary disease (COPD)—whichhistorically have been managed through infrequent clinical consultations and retrospective patient self-reporting.1 Such traditional methodologies often fail to capture the transient physiological fluctuationsthat herald acute exacerbations, leading to suboptimal therapeutic adjustments and increased hospitalreadmission rates. The emergence of sensor-based monitoring, underpinned by the Internet of MedicalThings (IoMT), provides a resolution to these information gaps by enabling the real-time acquisition andanalysis of high-fidelity physiological data.1