A Personalized Approach to Disease Management in Psoriasis - Episode 13
Dr Groves discusses the impact of population health knowledge in patients with metabolic syndrome.
Ryan Haumschild, PharmD, MS, MBA: When we look at metabolic syndrome, it makes me think about the greater picture. Many of us, integrated delivery networks and payers, are really focusing on population health too. I think one of the biggest things that makes up population health is metabolic syndrome, we talked about that earlier. Dr Groves, you gave an excellent overview of metabolic syndrome, the things that lead to it, the things that we care about. Thus, what are some of the population health implications of a subpopulation of patients with metabolic syndrome, like those with plaque psoriasis, who may have poor outcomes, higher cost of care, and it’s related to metabolic syndrome and some of those immune-related diseases like plaque psoriasis? Do you have any considerations when you’re looking at a population health perspective that you really care to control this patient population because it feeds into some of those key metrics across patient populations with metabolic syndrome? I’m just curious how this subpopulation would pull into some of those measures of success.
Robert Groves, MD: I personally see this, again, as a knowledge management issue. When it is obvious that a certain strategy is better than another, we would be foolish not to advocate for that strategy. Now of course, the caveat there is that it may be obvious to somebody who is immersed in the research and does it on a day-to-day basis, but the evidence does not yet convince others that that’s the case. And we could go on and on about that dichotomy, but what we know is that there tends to be bias in human beings. Thus, again, caution is part of the approach. But what I would tell you is that I’m very excited about the advances in pharmacogenomics. Melanoma is a great one, not only in diagnosis now, but also in the chances that it will spread. There are great strides being made in that area, but we have the opportunity in knowledge management.
I want you to think about prior authorization; all it is, is a knowledge management tool. It’s making it easy to do what the insurance company believes is the right thing, whether that is the right thing or not. Obviously, it doesn’t work in so many cases, and that’s part of the problem, but it’s a knowledge management tool. It’s saying of all of these choices, we believe that this is the most efficient way and therefore the best for society. Now, when we’re wrong, it’s because we don’t have the nuances that you’re talking about. Thus, getting the evidence at that level with the nuances can certainly inform decisions about prior authorization. Prior authorization would not exist if every physician practiced efficient evidence-based medicine with every patient, and I say that without apology. But what I also know is true, having practiced as a physician, is that it would be impossible for me to wrap my arms around all of the knowledge that’s out there with regard to the breadth of a specialty practice, much less a generalized practice. Thus, until we have those tools in place, it’s going to be difficult.
One of the things that we’re working on at Banner Aetna is an automated process for prior authorization. What that means is instead of a doctor prescribing a drug and then finding out 2 weeks later that it’s not approved, and then waiting another 2 weeks to get it approved, and having to take time out of their schedule to have a discussion with a doctor who’s possibly not even of that same specialty about why it ought to be done. Instead of that, in real time, using AI [artificial intelligence] strategies by payer, by plan, on his computer screen, the doctor can see what the caveats are for that particular patient in terms of what will be allowed and not allowed. If all the criteria are met, then an instant authorization is delivered at the time the patient is in the room. If they are not met, then the physician knows exactly why and can formulate their approach to either change what they’re thinking of doing first, or to make a case to the insurance physician that another path is warranted. That in and of itself would strip out a lot of the pain of prior authorization. Thus, it’s an imperfect and cost-focused knowledge management tool that needs to get much better at looking at individual patient outcomes, much better at keeping up with all of the knowledge that’s out there, and much better at automating the process.
Ryan Haumschild, PharmD, MS, MBA: That’s such an interesting concept because what it allows is unique considerations of certain patient populations. And if you’re using automated intelligence, artificial intelligence, you can go ahead and build in some of those considerations, like metabolic disease and psoriasis. It can help lead and be a pre-qualifier to a recommended treatment. Thus, instead of taking plaque psoriasis as a whole and saying here are the preferred options, it could start to take into consideration some of those unique subsets and produce maybe different treatments. I think that’s one of the things that’s so interesting.
This transcript has been edited for clarity.