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Omada Health pulled of something that was, especially at the time, highly unusual in the ever-burgeoning yet still-fledgling digital health space: In 2016, the company scored federal government reimbursements for its diabetes prevention program. It’s continued to grow since then and shared results from nine different peer-reviewed studies noting significant results for diabetes, cardiovascular disease, and obesity patients—a case study in how at least one company in the sphere is using data to try and fuel real world patient outcomes.
“It’s not about the data itself, it’s how you use it,” Omada co-founder and CEO Sean Duffy told Fortune in an interview earlier this year, echoing many of the chief executives and industry observers we spoke with for our recent feature on big data and AI in medicine. “The types of data that are going to be most useful going forward is the ‘in between’ data—what happens between actual health care visits,” he adds.
That mindset appears to inform the heart Omada’s approach to diabetes and cardiovascular disease prevention. Users get tools such as a digitally-connected scale and access to health coaches who provide them personalized advice and check in on health biometrics like weight, diet, and exercise regimens, at times simply sending friendly reminders of goals and motivations. Day-to-day behavior is a critical part of making such a program effective, Omada says, making the aforementioned “in between” data collection particularly important. For instance, even seemingly basic information like whether or not a user has checked in on their weight can be significant, according to Omada senior vice president of product, Mike Tadlock.
“Stepping on the scale is actually very important to the health outcome, as we learned,” Tadlock tells Fortune. Over the long term, Omada’s data indicated that people who more regularly checked