Amae Health Partners With Google Health to Integrate Wearables Data Into Serious Mental Illness Care
The collaboration will enable clinicians to access patient-approved data on sleep, physical activity, and heart rate variability to better monitor disease progression and identify early signs of clinical deterioration.
Amae Health has partnered with Google Health Enterprise to integrate Fitbit wearable data into its precision psychiatry model, aiming to improve care for patients with serious mental illness (SMI). The collaboration will enable clinicians to access patient-approved data on sleep, physical activity, and heart rate variability to better monitor disease progression and identify early signs of clinical deterioration.
The behavioral health provider, which treats conditions including schizophrenia and bipolar disorder, will provide Fitbit devices to patients enrolled in its treatment programs. Patients who consent to data sharing will allow clinicians to receive regular summaries of wearable-derived health metrics as part of their ongoing care.
Amae said the initiative is part of its long-term strategy to build an AI-powered predictive model that combines wearable data with other clinical information to assess disease state, monitor treatment response and detect potential relapse before symptoms become severe.
The company plans to integrate multiple data sources, including electronic medical records, laboratory results, medication history, electroencephalogram (EEG) data, voice analysis and patient-reported outcome questionnaires. Using machine learning and artificial intelligence, Amae aims to develop a composite mental health score that supports more personalized treatment decisions.
According to Scott Fears, MD, PhD, chief medical officer at Amae Health and professor of psychiatry at the University of California, Los Angeles, psychiatry has historically lacked scalable, objective tools to measure disease progression and treatment response. While biomarkers have long been studied in psychiatric disorders, identifying meaningful signals requires aggregating multiple small biomarkers rather than relying on a single indicator.
Amae envisions a future care model in which biomarker analysis helps guide diagnosis and treatment at intake, evaluates whether interventions are working within days, monitors patient stability over time, and alerts clinicians when data suggests an increased risk of clinical decline.
The company also said it plans to publish research findings from the initiative as part of its broader effort to validate its approach through peer-reviewed studies.
Amae currently operates seven clinics and maintains clinical partnerships with Cedars-Sinai, Mass General Brigham and New York-Presbyterian. The provider offers partial hospitalization, intensive outpatient and maintenance therapy services, working with commercial insurers and selected Medicaid plans across California, New York and North Carolina.
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