Michael Ganz
Adjunct Assistant Professor
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About
Michael Ganz is an Adjunct Assistant Professor at Harvard T.H. Chan School of Public Health in the United States. His research primarily focuses on public health issues related to vaccination disparities, the economic impact of invasive diseases, and treatment methodologies in dermatology. Recent publications include analyses of meningococcal vaccination trends and the cost-effectiveness of treatments for tardive dyskinesia.
Articles (5)
Year:
2025
Year:
2024
Background Electronic health records (EHRs) offer the possibility of using data entry templates to simultaneously document routine clinical care and capture disease-specific measures as discrete data elements that can be used for health services research (HSR). The objective of this study was to determine factors associated with meaningful treatment escalation (MTE) of psoriasis as a pilot study for future real-world HSR studies. Methods We conducted a retrospective, observational cohort study of psoriasis patients by using data collected during routine clinical care from an EHR using EpiCare® SmartForms. The psoriasis SmartForm records psoriasis disease severity measures and descriptive findings to generate visit notes. These data were extracted and analyzed to identify factors associated with MTE, defined as changing or adding, phototherapy, systemic, or biologic therapy. Results 473 psoriasis patients met study criteria; 239 underwent MTE between their first and third observed visits. Patients who experienced MTE had more severe disease at Visit 1—assessed by BSA, pPGA, oPGA, and a patient-reported disease severity measure--than patients who did not experience MTE. Other factors associated with MTE included use of topicals only or no active treatment at Visit 1, palmoplantar disease, and involvement of other difficult-to-treat body areas. Patients who underwent MTE experienced larger improvements in disease severity than those who did not. Conclusions This study highlights how data collected during routine clinical practice can be readily used for real-world retrospective HSR when disease measures are captured as discrete elements. This approach could provide a cost-effective platform to conduct real-world HSR.
Year:
2023
Year:
2021
Year:
2021
Collaborators (3)
Marta Kwiatkowska
University of Oxford
Russel Burge
University of Cincinnati
Kristina C. Duffin
University of Utah
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