Using Data Science to Design Effective Precision Preventative Behavioral Medicine
Ryan Quan Omada Health
There is widespread agreement that lifestyle focused preventative approaches are the most effective way to combat conditions like diabetes and heart disease. But behavior change is hard, and to date, even the most effective in-person programs include little (or no) personalization.
The data science team at Omada is changing that. We’ll discuss how we’ve built machine learning and experimentation directly into our product – leveraging vast amounts of behavioral data to create a system that continually improves in maximizing participant outcomes.
From creating a culture of data-driven product development to specific analytical techniques used to design and deploy a precision behavioral intervention, in this talk we’ll outline the path toward targeting the right individual, at the right time in the most effective way.