TY - JOUR
T1 - Characteristics of telehealth users in NYC for COVID-related care during the coronavirus pandemic
AU - Weber, Ellerie
AU - Miller, Sarah J.
AU - Astha, Varuna
AU - Janevic, Teresa
AU - Benn, Emma
N1 - Publisher Copyright:
© The Author(s) 2020.
PY - 2020/12/1
Y1 - 2020/12/1
N2 - Objective: To explore whether racial/ethnic differences in telehealth use existed during the peak pandemic period among NYC patients seeking care for COVID-19 related symptoms. Materials and Methods: This study used data from a large health system in NYC – the epicenter of the US crisis – to describe characteristics of patients seeking COVID-related care via telehealth, ER, or office encounters during the peak pandemic period. Using multinomial logistic regression, we estimated the magnitude of the relationship between patient characteristics and the odds of having a first encounter via telehealth versus ER or office visit, and then used regression parameter estimates to predict patients’ probabilities of using different encounter types given their characteristics. Results: Demographic factors, including race/ethnicity and age, were significantly predictive of telehealth use. As compared to Whites, Blacks had higher adjusted odds of using both the ER versus telehealth (OR: 4.3, 95% CI: 4.0-4.6) and office visits versus telehealth (OR: 1.4, 95% CI: 1.3-1.5). For Hispanics versus Whites, the analogous ORs were 2.5 (95% CI: 2.3-2.7) and 1.2 (95% CI: 1.1-1.3). Compared to any age groups, patients 65þ had significantly higher odds of using either ER or office visits versus telehealth. Conclusions: The response to COVID-19 has involved an unprecedented expansion in telehealth. While older Americans and minority populations among others are known to be disadvantaged by the digital divide, few studies have examined disparities in telehealth specifically, and none during COVID-19. Additional research into sociodemographic heterogeneity in telehealth use is needed to prevent potentially further exacerbating health disparities overall.
AB - Objective: To explore whether racial/ethnic differences in telehealth use existed during the peak pandemic period among NYC patients seeking care for COVID-19 related symptoms. Materials and Methods: This study used data from a large health system in NYC – the epicenter of the US crisis – to describe characteristics of patients seeking COVID-related care via telehealth, ER, or office encounters during the peak pandemic period. Using multinomial logistic regression, we estimated the magnitude of the relationship between patient characteristics and the odds of having a first encounter via telehealth versus ER or office visit, and then used regression parameter estimates to predict patients’ probabilities of using different encounter types given their characteristics. Results: Demographic factors, including race/ethnicity and age, were significantly predictive of telehealth use. As compared to Whites, Blacks had higher adjusted odds of using both the ER versus telehealth (OR: 4.3, 95% CI: 4.0-4.6) and office visits versus telehealth (OR: 1.4, 95% CI: 1.3-1.5). For Hispanics versus Whites, the analogous ORs were 2.5 (95% CI: 2.3-2.7) and 1.2 (95% CI: 1.1-1.3). Compared to any age groups, patients 65þ had significantly higher odds of using either ER or office visits versus telehealth. Conclusions: The response to COVID-19 has involved an unprecedented expansion in telehealth. While older Americans and minority populations among others are known to be disadvantaged by the digital divide, few studies have examined disparities in telehealth specifically, and none during COVID-19. Additional research into sociodemographic heterogeneity in telehealth use is needed to prevent potentially further exacerbating health disparities overall.
KW - Healthcare delivery
KW - Healthcare disparities
KW - Telehealth
KW - Telemedicine
UR - http://www.scopus.com/inward/record.url?scp=85098462837&partnerID=8YFLogxK
U2 - 10.1093/jamia/ocaa216
DO - 10.1093/jamia/ocaa216
M3 - Article
C2 - 32866249
AN - SCOPUS:85098462837
VL - 27
SP - 1949
EP - 1954
JO - Journal of the American Medical Informatics Association : JAMIA
JF - Journal of the American Medical Informatics Association : JAMIA
SN - 1067-5027
IS - 12
ER -