Characteristic Distinctions Between Pre-/Post-COVID-19 Teledermatology Adoptees: A Cross-Sectional United States-based Analysis and the Implications for Dermatologic Healthcare Equity

January 2023 | Volume 22 | Issue 1 | 101 | Copyright © January 2023


Published online December 28, 2022

Justin W. Marson MDa, Maham Ahmad BAb, Graham H. Litchman DO MSc, Danny Zakria MD MBAd, Sara Perkins MDb, Darrell S. Rigel MD MSe

aDepartment of Dermatology, SUNY Downstate Health Sciences University, Brooklyn, NY
bDepartment of Dermatology, Yale University School of Medicine, New Haven, CT
cDepartment of Dermatology, St. John's Episcopal Hospital, Far Rockaway, NY
dNational Society for Cutaneous Medicine, New York, NY
eDepartment of Dermatology, Mt. Sinai Icahn School of Medicine, New York, NY

IRB approval status: Reviewed and granted exempt status by Advarra IRB; approval #Pro00060440

Abstract
Background: Studies suggest potential heterogeneity in telemedicine adoption with potential to exacerbate healthcare access inequity.
Methods:
A pre-validated survey was electronically sent to a proprietary listserv of practicing US-based dermatologists. Results were stratified by when teledermatology was adopted. Chi-square and odds ratios (OR) with 95% confidence intervals (95%CI) were used to analyze categorical data while single-factor ANOVA with posthoc Tukey-Kramer was used for continuous data.
Results: 338 practicing US-based dermatologists completed the questionnaire. Academic/Government dermatologists were 4-times more likely (OR 4.08, 95%CI 2.37-7.03) to adopt teledermatology pre-COVID than private-practice dermatologists. Dermatologists with ≤10 years of experience were 1.8-times (OR 1.8, 95%CI 1.01-3.18) and 2.82-times more likely (OR 2.82, 95%CI 0.78-10.25) to adopt teledermatology pre-COVID-19 or at all, respectively, compared to dermatologists with ≥20 years of experience. Teledermatology adopters practiced more medical-dermatology (P<.0001) than non-adopters, who reported practicing more dermatologic surgery (P=.003; Tukey-Kramer α<.05) and dermatopathology (P<.0001; Tukey-Kramer α<.05). Pre-COVID-19 adopters were 4-times more likely (OR 4.69, 95%CI 1.46-15.07) to switch/incorporate live-interactive-only teledermatology (LI) post-COVID-19. Post-COVID-19 adopters were 6-times more likely (OR 6.09, 95%CI 3.36-11.06) to utilize LI than Pre-COVID-19 adopters. Pre-COVID-19 adopters use teledermatology for a larger proportion of patient visits than Post-COVID-19 adopters (19.6% v 10.4%, P<.0001), but also are 3.43-times more likely (OR 3.43, 95%CI 1.82-6.46) to report future decreases in usage.
Limitations: Cross-sectional retrospective survey and potential response bias.
Conclusion: Current teledermatology usage may be a suitable tool for medical-dermatology-focused practices. Material hurdles still exist for procedurally-oriented practices and future studies should investigate these barriers to maximize equitable access to dermatological care.

J Drugs Dermatol. 2023;21(1):101-104. doi:10.36849/JDD.7169

Citation: Marson J, Ahmad M, Litchman G, et al. Characteristic distinctions between pre-/post-covid-19 teledermatology adoptees: A cross-sectional united states-based analysis and the implications for dermatologic healthcare equity. J Drugs Dermatol. 2023;22(1):101-104. doi: 10.36849/JDD.7169

INTRODUCTION

The COVID-19 pandemic prompted many dermatologists to adopt teledermatology to continue patient care.1 Studies have since raised concerns regarding potential heterogeneity in telemedicine adoption and healthcare inequity exacerbation.1-3 The purpose of this study was to identify factors associated with teledermatology adoption and their potential effect on (virtual) dermatologic access. A pre-validated anonymous survey was emailed to a purchased proprietary listserv of actively-practicing US-based dermatologists. Completed results were stratified by teledermatology-adoption timepoint (TAT). Data analysis was performed using chi-square and odds ratios (OR) with 95% confidence intervals (95%CI) for categorical data and single-factor ANOVA with post-hoc Tukey-Kramer for continuous data.