Bobby Green: Artificial Intelligence, Machine Learning Critical to Growth in Effective Healthcare

Utilizing, and expanding upon, available technology in medical practices can efficiently improve healthcare, said Bobby Green, MD, chief medical officer at Flatiron.

Utilizing, and expanding upon, available technology in medical practices can efficiently improve healthcare, said Bobby Green, MD, chief medical officer at Flatiron.


How is Flatiron working to expand beyond the EHR to optimize clinical workflow?

So, 1 of the areas that I think is really exciting and where there’s been a lot of early work at flatiron—we’ve started to see some direct applications—is around artificial intelligence and machine learning. These are things that are in some ways sort of buzzwords in our field. I think they get used a lot very loosely and they seem as sort of a cure-all to a lot of things, and we’re sort of learning more and more that’s not going to be the case; but there are some really interesting early applications for them. So, we have an ML [machine learning] team at Flatiron that really does a lot of really basic development work and is trying to explore what can you actually do within medicine—within the electronic health record [EHR]—to try to improve care.

One of the things that we’ve found out is that you can actually use machine learning, looking at all the aggregated data in a patient’s chart, to predict whether patients have metastatic cancer or non-metastatic cancer. It turns out that has a lot of really interesting use cases for clinical care. So, 1 of the areas that we’ve actually rolled out, and are doing now, is for our clinical trials matching software, OncoTrials, using actual machine learning to identify patients who are metastatic or not metastatic, and to use that to enhance, and make more efficient, clinical trial matching.

Outside of what can be implemented right now, what are some areas of technology that we might see further in the future not currently being used?

Maybe we’d go back to artificial intelligence machine learning—that genre of things. I think a lot of people have felt there’s been a little bit of a disappointment so far that we really haven’t moved the needle in a lot of ways. That being said, I think there are a ton of opportunities in that space, we just need to figure out a way to do it that’s good for patients, safe for patients, and doesn’t introduce bias into our care. I think there’s a whole lot of opportunities there and we’re going to really see an explosion of this.

I also think the other area I’m really excited about—sort of 2 other areas of technology—that I think are going to be exciting are: first, how we think about patient engagement. Patient portals are out there, they’re relatively ubiquitous along EHR, but I still think we haven’t really solved the problem of, how do we engage patients and how do we make them really become an important part of their own care. So, that’s 1 area. Telemedicine is a way that we’re going to see a lot of advancement in the future and a lot of excitement in that realm as well. The technology’s there—just like a lot of things, we need to figure out how to make it work most efficiently.

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