The role of telemetry monitoring: From diagnosing arrhythmia to predictive models of patient instability

Abstract

Over the past sixty years, telemetry monitoring has become integral to hospital care, offering critical insights into patient health by tracking key indicators like heart rate, respiratory rate, blood pressure, and oxygen saturation. Its primary application, continuous electrocardiographic (ECG) monitoring, is essential in diverse settings such as emergency departments, step-down units, general wards, and intensive care units for the early detection of cardiac rhythms signaling acute clinical deterioration. Recent advancements in data analytics and machine learning have expanded telemetry's role from observation to prognostication, enabling predictive models that forecast inhospital events indicative of patient instability. This short communication reviews the current applications and benefits of telemetry monitoring, including its vital role in identifying arrhythmias and predicting conditions like sepsis and cardiac arrest, while also addressing challenges such as alarm fatigue and the economic impact on health systems. It further explores opportunities for developing algorithms to enhance the practical use of telemetry data in clinical settings.