Using the DataDerm database has uncovered disparities in prescription patterns, but it’s still early in the process of understanding why those disparities might exist, said Robert Dellavalle, MD, PhD, MSPH, and Ramiro Rodriguez, MD, both of University of Colorado School of Medicine.
Using the DataDerm database has uncovered disparities in prescription patterns, but it’s still early in the process of understanding why those disparities might exist, said Robert Dellavalle, MD, PhD, MSPH, professor, Department of Dermatology, Department of Epidemiology, University of Colorado School of Medicine, and chief of Dermatology, Rocky Mountain Regional VA Medical Center, and Ramiro Rodriguez, MD, postdoctoral fellow, Department of Dermatology, University of Colorado School of Medicine.
During an interview with The American Journal of Managed Care® (AJMC®), Dellavalle and Rodriguez discussed the analysis of the DataDerm database and utilizing collected data to address disparities and other issues that are identified.
They presented analyses of DataDerm at the annual meeting of the American Academy of Dermatology (AAD).
AJMC: Collecting data has been crucial in order to understand disparities and social determinants of health. How well are we using that data to come up with solutions?
Dellavalle: I think we're at the beginning of an era of looking at big data with a little bit more of a critical eye or a lens that looks at diversity and equity and inclusion issues in the big data. The one that we've been focused on, in our research, has been looking at prescription patterns to see if expensive medications in dermatology are being prescribed equitably across all of the people who have these diseases that could use the expensive medications. And if certain groups are getting these medications more than others, why might that be? It's sort of a hypothesis-generating exercise right now.
Rodriguez: We're definitely at a starting point, where we're starting to get more information and finding ways to explore that data itself. I do have to say that, because it's starting off, it really depends on what population we have within the data to see which patterns we can evaluate.
I am pretty excited for the future to see how we can best kind of figure out what patterns to evaluate. And [we talked at the AAD annual meeting] about kind of prescription patterns for dupilumab, which is one of different biologic medications. It's pretty difficult to get them approved for insurance purposes.
AJMC: The 2021 report of the DataDerm database found an initial challenge that the majority of patients with known race/ethnicity data were White. Why do you think that was the case, and how do we increase diverse populations being captured in the database?
Rodriguez: I will say that a big part of dermatology is the geographic distribution of dermatologists. Before offering DataDerm to dermatologists, if we do have a geographic maldistribution in just the population of dermatologists already serve, there's a possibility that it could be some skewing of that data.
I can say also that there's different things that we can do to kind of increase the access to kind of safety net hospitals; that would be another approach that we can start incorporating into DataDerm.
Dellavalle: That's one of the things we're trying in Denver: to get some of our safety net hospitals enrolled in DataDerm. They might not benefit as much from enrollment as the private practitioners who happen to see more of the White patients in our nation.
AJMC: Circling back to the dupilumab prescriptions: The DataDerm Database analysis found that Black patients and Asian patients received 58% and 86% fewer prescriptions for dupilumab to treat atopic dermatitis compared with White patients. What do you attribute this difference to?
Rodriguez: I can tell you, whenever we evaluate prescription patterns, there's a lot of things that we need to consider. I think a big factor could be insurance status, based on what we've seen in our database. There's an overrepresentation of people with private insurance. And if those populations are skewed, by any chance, which they tend to be, that can kind of address the disparity that we're seeing. So before we reach any conclusion yet, we need to kind of be certain that our population itself can be a bit more representative.
Dellavalle: We've had some studies which show surprising results. At our University of Colorado hospital system, our preliminary data has shown that Black patients receive dupilumab more frequently than other groups. So, we're trying to figure out why that's the case there. We certainly have hypotheses about what we're going to find, but what the data actually tells us and why can be different from our hypotheses.
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