Analyzing Health Lifestyle Data in the Cloud to Personalize Patient Care

Approximately 30.3 million individuals in the United States have a Type II Diabetes (T2D), and more than 84 million, or 1 in 3, have pre-diabetes. In addition, between 60% and 75% of these individuals are likely to have Hypertension (HTN)1, which makes management of these conditions, complex and difficult. Studies have shown, however, that adjunctive therapies such as healthy lifestyle behaviors, including sleep, diet, exercise, and stress reduction, can help to prevent and manage, and even prevent T2D and HTN.

NYU Langone partnered with Google Cloud and Maven Wave to create a technology platform that gathers real-time sleep, nutrition, and physical activity data from connected mobile devices. The data enables NYU Langone to provide deep insights to its clinicians and personalized messages for its patients to optimize adherence to sleep, diet, and physical activity.

In this webinar you will hear from NYU Langone’s Dr. Azizi Seixas, Assistant Professor in the Department of Population Health and Department of Psychiatry, and others on how to:

• Apply insights from a virtualized pragmatic trial
• Capture health data from IoT devices through home-monitoring and in-clinic, and translate that data into meaningful insights
• Leverage patient-generated data to triage patients affected by T2D, HTN
• Deliver personalized push-based reminders to promote adherence

• Patrick Crotty, Senior Principal at Maven Wave
• Azizi Seixas, PhD, Assistant Professor, Department of Population Health and Department of Psychiatry, NYU Langone Health
• Rafa Barroso, Enterprise Customer Engineer, Google Cloud

1. Colosia, A. D., Palencia, R., & Khan, S. (2013). Prevalence of hypertension and obesity in patients with type 2 diabetes mellitus in observational studies: a systematic literature review. Diabetes, Metabolic Syndrome and Obesity:Targets and Therapy, 6, 327–38.


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