American Journal of Managed Care
Speakers at the American Academy of Dermatology 2023 Annual Meeting highlighted the potential of DataDerm to tell the story of dermatological care in the United States, but some also cautioned that the registry only reflects those who have access to care in the first place.
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Speakers at the American Academy of Dermatology (AAD) 2023 Annual Meeting highlighted the potential of DataDerm to tell the story of dermatological care in the United States, but some also cautioned that the registry only reflects those who have access to care in the first place.
As introduced by Marta Jane Van Beek, MD, MPH, of the University of Iowa, DataDerm is AAD’s clinical data registry that was launched in 2016 and was “developed by dermatologists for dermatologists.” It boasts a rich tapestry of data on patients, care, and real-world outcomes pulled from 25 different electronic health record (EHR) platforms, and it contains information on patients with all types of insurance.
The aim is to allow dermatologists to tell their story of how patients are being treated in the real world, from practice-level insights to bolstering arguments against prior authorization requirements in congressional hearings.
Such a data repository was necessary due to the nature of dermatology practice, Van Beek explained: “Dermatology is a little bit limited on what we can use for outcomes because we lack labs for disease process….Unlike other specialties or even general medicine, we don’t have fixed fields to denote outcomes and so the free text in the clinical notes is very valuable to know more about the patient journey.”
She cautioned that the demographics within DataDerm don’t mirror the US population, because the data represent only those who have access to medical care and are seen in practices, but the information contained in it can still be used to tell compelling stories about improvement in symptoms over time and receipt of systemic agents across practice types.
This introduction was followed by a talk from Stefan C. Weiss, MD, of OM1, one of the partners that AAD relies upon to take the deidentified data from DataDerm, link them to other data sets, review the information that comes out, and make generalizable conclusions at the macro level.
He highlighted the capability to stratify receipt of treatments for atopic dermatitis by race, income, and education, but he also called upon dermatologists to record information on disease severity so the field can better understand where disparities are emanating from and how to address them. Dermatologists will need to be armed with such evidence to make effective policy arguments, Weiss said, as “the more we capture, the better the story we can tell on behalf of our patients, and in the end that benefits all of us, because that’s the information that we can use to drive different responses in Washington to allow us to avoid step edits and prior authorizations.”
Furthermore, by using real-world data to understand drug safety implications in different cross-sections of patients, “we begin to be able to bridge the gap to personalized medicine…to make sure that we get the right drug to the right patient at the right time, and collecting data into DataDerm will allow us to do that,” Weiss concluded.
Despite the clear advantages of drawing from real-world data to address disparities and improve care, collecting those data in the first place can be more difficult than it seems, according to the next speaker, Melissa Piliang, MD, of Cleveland Clinic, who is the cochair of the DataDerm Hair Data Elements Working Group. The group is leading the charge to standardize data fields related to hair disease for inclusion in the DataDerm registry.
This complex task involved gathering input from a committee and then streamlining the suggestions into a list of top 10 data elements to be added to DataDerm. The group continues to vote and finalize the list, which is currently split between patient-reported outcomes (eg, quality of life, symptoms) and clinician-assessed measures (eg, percentage of hair loss, scalp changes).
An additional challenge is the inadequacy of the current coding system to accurately capture patients’ diagnoses, Piliang added, citing the lack of codes for frontal fibrosing alopecia or central centrifugal cicatricial alopecia. Updating classification systems to include these codes would benefit research, coding accuracy, and billing.
A key lesson learned from the working group’s efforts is that DataDerm must strike a balance between collecting highly detailed data but also creating “data elements that are targeted toward the busy private practice where they see a lot of patients a day and they’ve got to be able to do this quickly, and we don’t want to be burdensome,” Piliang said.
In an example of data gleaned from private practice, the next speaker, Ramiro Rodriguez, MD, a fellow at the University of Colorado, presented his team’s findings on how age, gender, race, ethnicity, and insurance are associated with a patient’s likelihood of receiving dupilumab, a newly FDA-approved therapy for atopic dermatitis.
Rodriguez outlined the takeaways of this retrospective, observational cohort study, including that more than two-thirds of prescriptions were given to patients aged 18 to 59 years who had private insurance. However, he also emphasized the limitations of the study, chief among them that it was conducted in a private practice.
To improve the generalizability, he suggested going into areas of the United States that have a lower number of dermatologists. “Another approach to improve the database could be to engage safety-net hospital systems,” he said. “That way, we’re able to represent a different group of people who do not have private insurance.”
Finally, Robert Swerlick, MD, of Emory University School of Medicine, spoke of the potential for more robust data capture to help the dermatology community measure and close gaps in care. He called for delegating much of the provision of the data to patients, because they know their history and goals best, and also because their participation will be key to scaling up the process of data collection.
Data from his practice’s implementation of patient questionnaires revealed how the emotional burden of skin disease could be tracked over time on the individual and aggregate levels. Because clinicians treat people, not diseases, they must understand their patients’ concerns and goals in order to measure success.
“You’re never going to pick this up if you’re just looking at their skin,” Swerlick emphasized, “and if you don’t ask people about it, you’re not going to know about the emotional burden.”
Understanding the impact of disease and disparities requires having the tools to measure these impacts, he concluded, “and the take-home message is we’ve got to have enhanced data collection.”