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Jason Bhan, co-founder and chief medical officer of Prognos, joins Harry to talk about how machine learning is being used to dig into multi-sourced clinical diagnostic data to improve health by predicting disease early.

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Transcript

Harry Glorikian: Welcome to the Moneyball Medicine podcast, I'm your host Harry Glorikian. This series is all about the data-driven transformation of the healthcare and life sciences landscape. Each episode we dive deep through one-on-one interviews with leaders in the new cost-conscious value-based healthcare economy. We look at the challenges and opportunities they're facing and their predictions for the years to come.

I'd like to welcome our next guest Dr. Jason Bhan, who's the co-founder and chief medical officer of Prognos. He's a family physician and serves as chief medical officer of Prognos. He's regarded as a national expert in the applications of technology and medicine, a topic on which he speaks regularly at institutions and conferences, such as health 2.0, M-health, E-health collaborative and health data palooza.

He's also done extensive strategy consulting with different companies including pharmaceutical companies and others. Welcome to the show Jason a pleasure to have you here.

Dr. Jason Bhan: Thank you.

Harry Glorikian: So, tell me a little bit about Prognos, maybe a little bit about its history and what you guys are really doing.

Dr, Jason Bhan: Sure, so we have an incredibly ambitious vision which is to eradicate disease. And you might look at that and say, alright well that seems pretty incredible how are you gonna get there. And that is you know it's sort of like our 20-year vision out and we've got a mission which is to you know find and predict disease even earlier than it is today. So, when we started the company, probably seven or eight years ago you know it was -, we were trying to figure out how we could take data that was available in the system and use it for improving the lives of patients.

So, we looked at different data sets that were out there, we looked at you know claims data and prescription data. And what we really knew, I would really know from my years of practice was that sitting there in my office seeing you know 30 patients a day and ordering lots of blood tests on them and lab tests on them, and then going back and seeing. You know going back to my bat