Xella Health has incorporated Oura wearable data into its women’s health platform, enabling members to share sleep patterns, heart rate variations, and other biometric readings directly with healthcare providers alongside laboratory findings. This integration seeks to close the gap between continuous health monitoring and clinical diagnostics, allowing practitioners to connect physiological changes with symptoms or treatment effectiveness.
Users can choose to share Oura’s metrics, such as resting heart rate, recovery metrics, temperature trends, and menstrual-cycle information, with Xella’s system. Clinicians then evaluate these trends in tandem with the platform’s multiomic testing, which analyzes hormonal and metabolic health, inflammation, nutritional status, reproductive health, and cardiometabolic risk. The combined data helps physicians tailor care plans, monitor progress, and modify interventions as needed.
Kelly Lacob, CEO and cofounder of Xella Health, said that wearables detect changes in the body but cannot explain why they occur or what actions to take next. By linking Oura’s real-time monitoring with Xella’s diagnostic tools and physician-guided telehealth care, the platform helps women understand how specific health concerns are impacting their biometrics, and vice versa, how their daily habits are impacting their overall health and specific conditions or life stages they are handling. The integration also tracks how relevant vitals and biometrics respond to specific interventions or treatment plans, enabling more efficient care optimization.
The collaboration builds on Oura’s existing efforts in women’s health, including partnerships with Mira for hormone monitoring and the development of an AI tool for menstrual and menopause analysis. Unlike those initiatives, Xella’s integration embeds wearable data within a full care system, where physician-led adjustments are informed by both lab results and symptom reports.
Healthcare providers will analyze Oura’s biometric trends in relation to each member’s specific health objectives, such as improving fertility or managing perimenopausal transitions. The system tracks how treatments influence biometric readings, allowing for evidence-based refinements.
