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Leveraging real-world data at Emory Healthcare


Ryan Haumschild, PharmD, MS, MBA: Well, I really want to talk with all of you about the innovative ways we’re leveraging real-world data to support personalized care. And I think personalized care has been a hot topic lately, especially since we’ve been talking about it forever, making sure that we’re inclusive for all types of patient populations and especially for patients who do not respond well to therapy. Over time, we see increased cost of care, poorer outcomes, and reduced patient-reported outcomes and quality of life. And so, that’s something that an integrated delivery network across the country as paying arms, really needs to start considering. It’s something that really hit the peak for us. When we think of a specific disease state like plaque psoriasis, there are a number of agents in space. And sometimes it’s very easy to focus on how the patients are doing, what are the main treatments we want to consider, what should our technical payer coverage be for certain selected agents, and how can we streamline our selection. Because at the end of the day, we always try to do the best on behalf of the patients and the employer group and considering the total cost of care.

One of the things we looked at when we started to dig a little deeper into this is that we found that there is a stronger link between metabolic syndrome and plaque psoriasis. If we look back at some of the primary literature that initiated this hypothesis, it really comes from the United States, but really also from the European world in terms of dermatology, where they saw a strong link in terms of scores and responses dermatological treatments for patients with metabolic syndrome. And they seem to be sort of disparate differences in responses between patient populations. So not only do you want to consider that, but when we look at the paying arm, we also want to consider what the cost of care is. If we have patients, as we talked about earlier in this session, who switch agents, that’s really a unique consideration we want to think about. We’ve talked about some of the downsides of switching, especially in patients with metabolic syndrome, because they may be less likely to go ahead and fill that medication, less likely to be supportive and continue on new drugs. There is also rehabilitation on medication. And all of this plays a role.

I think on top of that, as we start to switch these patients, there’s a period of re-induction that Dr. Lebwohl talked about. Really, when we think about this re-induction period, it also drives up the cost of care on the continuum for this patient population. If we have patients who might be more difficult to treat, with metabolic syndrome, how do we identify a more specific drug early on to make sure we get the best results right away, instead of taking them from maybe 2 to 3 therapies before finally choosing the right choice. One of the ways we really want to analyze that data and dig deeper is how to leverage our electronic medical record data, our specialty pharmacy data to see how patients are doing. I think through this investigation we were able to determine that the cost of care is higher in patients with metabolic syndrome as a comorbidity with plaque psoriasis. This hypothesis is something that we have definitely acknowledged.

We want to dig deeper to think about it, not only do we want to know more, we might have favorite products, but we might look at some drugs that treat metabolic syndrome and plaque psoriasis well that may not be the product favorite overall. And so how do we focus on creating care pathways so that we can get that patient the right medication sooner instead of putting them through different therapies or re-starting multiple different therapies when they fail to ultimately get there ? And I think that’s a key consideration that we’re looking at, especially in this patient population with plaque psoriasis. And we’re looking at some of the resurface data, and we’re looking at tildrakizumab, and we’re looking at some of these different clinical indicators, we’re seeing that there’s data starting to emerge that says, hey, if your patient population is starting this treatment sooner, they will get better overall results. And if they have better overall results, you’ll likely have a decrease in total cost of care, and you won’t have to initiate multiple different drugs throughout the process or biologics that result in a higher cost of care.
When we looked at tildrakizumab, we found that it seemed really appropriate. How do we create a pathway for this drug to see in the real world if we create better access to this drug earlier in therapy, do we see a reduction in care? Are we witnessing a better control of the disease? Are we seeing better control of some of these comorbidities as Dr. Shaw mentioned earlier with some of this quality of life data in terms of arthritis and some of these other things that tend to fill up within of this patient population? So those are the things that we’re trying to think about and how we’re evaluating a single pathway on the payer arm, as well as protocols on the health care side that would align to really improve overall care for the patient population.

So as we see that continue to grow and as we continue to look at some of these unique patient populations in oncology, plaque psoriasis, and rheumatology, that’s kind of where we think the forefront of research and patient treatment goes, and this has more of a personalized approach while considering the cost, but a more personalized approach with qualifying data there, maybe of 2 ICD-10 codes that indicate the metabolic syndrome and plaque psoriasis. And that can be a pre-qualifier for earlier access, earlier treatment, and ultimately more specific, higher-quality patient care.

Transcripts edited for clarity.