Incentivizing Patient Use of Digital Health Tools

EP: 1.Prevalence and Incidence of Psoriasis

EP: 2.The Impact of Psoriasis on the Quality of Life

EP: 3.The Benefits and Limitations of the PASI Score

EP: 4.Health Inequities Impacting Optimal Treatment for Patients With Psoriasis

EP: 5.Factors to Evaluate When Initiating Psoriasis Treatment

EP: 6.Improving Treatment for Psoriasis Across All Skin Phenotypes

EP: 7.Valuable Quality of Life Assessments in Psoriasis

EP: 8.Costs and Burdens of Psoriasis

EP: 9.Financial Burden on Psoriasis Patients

EP: 10.Educating Providers and Improving Early Diagnosis

EP: 11.Ensuring Equal Face-to-Face Provider-Interaction Time Among Patients

EP: 12.Challenges Across Skin Phenotypes

EP: 13.Addressing Disparities in Care for Psoriasis

EP: 14.Psorcast: A Digital Health Tool for Patients

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EP: 15.Incentivizing Patient Use of Digital Health Tools

EP: 16.Health Equity Across All Skin Phototypes

EP: 17.Final Thoughts on Psoriasis Across Skin Types

Ryan Haumschild, PharmD, MS, MBA: Dr Lopes, I’m curious, from your perspective as a managed care executive, how do payers incentivize patients to utilize digital health tools like the Psorcast [app] that we talked about to monitor the success or failure? And do we feel like the data from the apps like Psorcast can help accurately report the prevalence of psoriasis in the skin of color and different ethnic backgrounds?

Maria Lopes, MD, MS: I think that’s probably still a real-world question that hasn’t been answered. What’s the utility we can receive from these apps in terms of, is it meaningful, is it actionable? How do you structure the information so that it’s meaningful to the patient, but also to who’s on the receiving end? Maybe it can be a specialty pharmacy or it can be a clinician, like Dr McMichael, or even the PCP [primary care physican]. If they know what the algorithm of care looks like, how can this information be meaningful and actionable, and perhaps lead to an intervention, even between office visits? That hopefully is part of shared decision-making, so if we see patients aren’t taking their medication, maybe they’re getting worse, maybe having a conversation before their next office visit when they’re much worse, that hopefully can change the course and the expectation for that patient. I think a really interesting area is the predictive ability of some of this information. Because from AI [artificial intelligence]—and I think we’re seeing it in other areas like RA [rheumatoid arthritis], IBD [inflammatory bowel disease], maybe COPD [chronic obstructive pulmonary disease] as well—can this information, through an AI algorithm, actually predict when you’re going to experience a flare?

Then payers, obviously, are very interested in that because that gets back to how do we reduce costs? How do we improve quality, how do we improve outreach, how do we improve care coordination? How do we get at the root cause of perhaps a symptom that may turn into a bigger problem, and what we can do to alter that course and reduce total cost? As well as, is the medication working? If someone is on a high-cost biologic, and is taking the medication and we can track this, yet the symptoms aren’t improved or they’re not doing better, is it time for a conversation earlier rather than later? Perhaps [this is] even in conjunction with a clinician about how we can change the treatment, because biologics are all expensive, and the most expensive drug is the one that is either not being taken or not working. So I think it brings together important data that hopefully are meaningful but also actionable.

Ryan Haumschild, PharmD, MS, MBA: Real-world evidence is important, to your point, and how can we keep extracting that in different areas because we know we want to improve the diversity of clinical trials? That’s a goal we all [have], but we know sometimes those randomized controlled clinical trials might take 6 years to come to fruition. How do we leverage data now to help aid our decision-making and make impactful change? So I appreciate that conversation. Dr McMichael, when we think about you in the clinic working with your patients, what educational tools are you using for diagnosing patients across the skin phototypes? And as we talked about earlier with primary care, how can providers educate other providers on the importance of early referrals to dermatologists for timely intervention?

Amy McMichael, MD: That’s a good question. I’m an old dermatologist, so I use mostly my eyes and ears to diagnose patients. I don’t have to use a lot of tools to diagnose psoriasis right now because I’ve seen so much of it over the years, and I have a particular interest in skin of color, but it doesn’t always translate. So how do I teach my residents? How do I teach other physicians? I think that becomes an important question. I recommend to the folks I teach to think about other differentials. In the talks I give nationally and internationally, I show pictures of patients with atypical appearance of psoriasis, it’s not classic. I tell the story around that patient. For example, an African-American woman about 60 years old who had been admitted for “vasculitis,” but what she had was a hypertrophic form of psoriasis. I tell the story of another patient of mine who I misdiagnosed with prurigo nodularis for about 4 or 5 months, and recognized he wasn’t responding to treatment and noticed a bit of symmetry about his lesions, and then ended up biopsying him to then come to the diagnosis.

I talk about treatment algorithms. I talk about giving patients time to improve. If they don’t improve, then move to biopsy. I talk about things that look like other things, so that the folks who listen to me and hear my stories and see my photos can come to a better understanding of what they might be missing. None of us are perfect as clinicians. We’re never going to get to the point where we do everything correctly, but we can get closer and closer to where we get that right diagnosis earlier. I think that’s what the goal is.

Transcript edited for clarity.