About this Session:
Healthcare systems continue to generate vast amounts of data, yet much of it remains episodic, siloed, and insufficient to explain the day-to-day drivers of patient outcomes. WHOOP captures continuous, objective physiological data outside the clinic, providing longitudinal insight into sleep, recovery, cardiovascular strain, and behavioral patterns that are otherwise invisible in traditional care settings. Advanced analytics and AI are used to interpret these high-frequency signals at scale, detecting patterns, contextualizing variability, and translating raw data into clinically relevant insight. When combined with clinical context, these AI-driven signals can reduce uncertainty, support risk stratification, and inform more personalized, proactive care decisions. This approach demonstrates how continuous physiological monitoring, powered by AI, can complement clinical data to improve outcomes, guide interventions, and advance a more data-driven, behavior-informed model of care