S6 Ep6: The Reading Room Podcast: Assessing the Current Landscape of AI and Reimbursement in Radiology, Part 2

One priority we've set as a professional association with the American College of Radiology is to drive physician education and maturity of their knowledge and understanding of not just the tech itself, but how to safely implement the tech in practice.

So we have just adopted a practice parameter for AI and imaging, which makes it very concrete and very specific for physician practices, what to do, what are the steps that are required.

So it demystifies implementation and drives better understanding as to how to responsibly use this technology.

The second thing that we're really leaning into is the post-deployment monitoring.

So in the current regulatory approach, a lot of the onus is on a manufacturer to demonstrate the performance in the somewhat artificial pre-market scenario.

which does not answer the question as to how generalizable it is, as I said earlier.

So we're actually leaning into the post-deployment monitoring, enabling practices to do that.

And I think the long-term promise there, if that's successful, imagine for a moment, the whole country would be on a network that is facilitating post-deployment monitoring.

That would actually make it a lot easier for the FDA, theoretically, to pass these things out into practice because we would have a post-market signal that might indicate when something is not working as intended.

So that de-risks the release of technology into the healthcare space, theoretically, once we reach a critical mass.

So we feel that that is a very important building block for future more rapid technology adoption.