Matthew Michela: Because data is so hard to get even in this new world of statistical evaluation in front of us, the data that you use is still inadequate. What data is easily accessible? Claims data or data out of an EHR?
That’s real world because I can tell you what I paid for two weeks ago or yesterday. I can pull data out of an EHR that happened yesterday or five days ago. That’s a payment evaluation. EHR has been built, principally, from the foundation of how do I keep track of things so I can bill and get reimbursed. It doesn’t have a lot of clinical information.
I can see from an EHR that an MIR occurred, but I absolutely don’t have any idea what that MRI was ordered for. I know how much I paid for that, but they don’t know if I’m looking at a disc, a nerve, or a tissue. Those are very hard to get and don’t make their way into the EHR unless a human being can read them and review them.
In our work and our ecosystem partners, we have access to the data underneath. The clinical information about what actually happened to the patient is unstructured. While this is novel, you will see over the course of the next three to four years a complete transformation of the way trials are done by pulling all of these novel data sources in.
In our case, we can give them imaging. We’re the only one on the planet that can give them imaging in that regard. You can find AI companies who can pull out genomics or who can pull out different information out of voice. You’re going to find data that sits out in the consumer applications and in the things that drive some of the socio-economic factors of healthcare.
Pulling that out and normalizing that over the next decade is going to create entirely new ways of evaluating medical treatments and medical devices. That’s going to transform how trials are done and how quickly they’re done here. It all comes back to data that’s interoperable.
Sramana Mitra: I have a few questions based on all the things that you’ve said. You’re talking about using patient’s data and supplying them to your clients who are trying to find patients for clinical trials. What are the privacy concerns in that?
Matthew Michela: Being a very mature healthcare and information company with very large clients including government, state entities, or the largest hospitals in the world, we have rigorous requirements for security. We meet all of those.
For decades, we’ve obviously paid a lot of attention and do everything within the proper consent requirements. We would never do anything for data that didn’t have the proper consent. In trials, patients would have to consent in order to do that. There’s a lot of ways to generate consent in the healthcare system.
If we don’t have that consent, obviously that information doesn’t move anywhere. Since we sit in the clinical transactional model where doctors have access to that information, it gives us the opportunity to ask more patients for consent so that information can be de-identified as it needs to be.
There are two parts to that question. One is the technology answer of do we do the right things? Do we pay very careful attention? Do we have a big, broad network that watches and supervises us? The answer to that is yes. We invest tremendously in technology.
On the other regulatory side, consent is going to come from patients. Patient may give that consent to a third party like a device company or a doctor. We would rely on that.
This segment is part 4 in the series : Thought Leaders in Healthcare IT: Life Image CEO Matthew Michela
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