Technology in Diabetes Care: From Prevention to Disease Management - Episode 6
Dennis P. Scanlon, PhD: As a payer, there’s no shortage of technologies, or devices, or therapies that people are asking to be paid for. How do you handle that? How do you make the decisions regarding what makes sense from a payment perspective, given all these various factors?
Kenneth Snow, MD, MBA: There are a number of things that are looked at. Cleary, data that has been published and well-reviewed is key—the data that shows that whether it’s the technology, the tool, whatever, actually does what it says it does and that it adds benefit and that there’s a positive outcome. Is there an acceptance that this tool or technology is going to help our member in some way (preferably in terms of either driving down cost, improving health, improving A1C (glycated hemoglobin), or just being more adherent and attentive to the disease state)? What specialty societies say carries weight.
Each technology (in a way) is unique in and of itself, unlike medication, where there’s a chemical formula. If you make metformin, it better be metformin regardless of which factory is making it. But, from a technology platform, there are little tweaks and differences between them, and those little tweaks and differences can result in either success or failure. Each one has to be reviewed on its own, and one of the things you have to look at is, what are the unique properties to the tool or technology that yields the outcome? And, does the next device or tool carry the same properties with it?
Robert Gabbay, MD, PhD, FACP: I think one of the other challenges for devices is that pathway of making iterative changes makes sense, and each thing is regulated and reviewed. But in these digital platforms (there are very few studies with, them but when they are done), usually the process of development is so rapid that in whatever they tested 2 years ago, they’ve got a completely different version—version 5.0. And so, our clinical trial system can’t do the studies fast enough for the iterative changes in digital technology.
Kenneth Snow, MD, MBA: That’s absolutely true, and oftentimes, those trials will then have a population of folks who, of course, are engaged. They wanted to be in the trial. They wanted to use the technology. Are they doing better than it appears because of the technology, or are they doing better because those are the folks who just do better and they would do better even if they didn’t have good technology? They would riddle it out even in the absence of technology. It is one place where big data—data that’s collected, accepted by a payer looking at outcomes—can really be mined and understood. Can we show outcomes and do studies in ways that really aren’t practical, as you said, in the traditional blinded controlled study system?