Prognos is a healthcare technology company using artificial intelligence and advanced analytics for early disease detection. More than 7 Billion data points, 135 million patient files, and 500 proprietary algorithms put into play to drive early detection of chronic and ID-delayed diseases. Merck is onboard with investment…Cigna has rolled it out to plan members…and I recently met with their CMO Dr. Jason Bhan on the show.
Dr. Jason Bhan – the Chief Medical Officer of Prognos. The company has a powerful A.I. platform adding time and better accuracy to sufferers of 35 different diseases.
In this Red Hot Healthcare episode, Dr. Steve and Dr. Bhan discuss:
- The power of Prognos’ AI platform and risk-assessment engine
- Prognos vs. IBM’s Watson
- A wide reach into life science, payer, and diagnostics industries
- The bold new approach into early disease detection
Below is a short clip from the audio podcast interview:
DR. STEVE: “We spoke off air, and you mentioned that your A.I. platform is really a risk assessment engine; and it uses clinical diagnostic data – not claims data, right?”
DR. BHAN: “Absolutely. Medical claims data is considered transactional, as is prescription claims data. You know what’s happened AFTER it’s happened. But you really don’t know much detail behind that, so digging into clinical data really helps you understand where they are in their healthcare journey. From that type of information, you can derive all types of powerful predictions.
DR. STEVE: “You’re not just going after a specific segment of healthcare clients – you’re really going wide with your offering here. Life sciences, biotech, payers, providers…take us through that.”
DR. BHAN: “So as you mentioned, the underlying premise of the technology is about assessing risk and predict risk. One you can do stratify an individual’s risk; you really can apply it to many solutions. This goes to payers and how they choose to intervene with their members, plus where they should be capturing more revenue from the government or their self-pay clients when they begin getting deeper into managing riskier cases.
And for the pharma side, it really is about finding pockets of patients who are at risk for failing of given therapy, or for being diagnosed with a particular disease, matching up with drug portfolios. This leads into better physician and patient education.
DR. STEVE: “You [Prognos] hit about thirty different disease areas maybe a little more than that. Are those mostly rare diseases that often go missed, or whose clinical presentation can be confusing, and be difficult to diagnose…or is it common diseases, and just identifying some of their key facets a bit differently?
DR. BHAN: “Yeah, that’s a great question. So we try to go where there’s the biggest impact; and that falls on both sides of the spectrum. There are rare diseases, which take years to diagnose. We take in, and identify the patterns of testing and data as it comes in – so they can be diagnosed faster. This decreases cost, and increases longevity.
We also look at more chronic diseases and conditions such as diabetes or high cholesterol, where there’s just large volumes that incrementally are very small cost…but overall the cost burden is very high.
So we do play on both sides – predictive analytics are much more impactful on the rare disease or oncology side. That’s because no one really seems to have enough resources to deploy case managers against hundreds of thousands of people who may be getting sicker with their diabetes…versus two or three people who may not be diagnosed with a severe disease yet – and we can intervene there.