Factors Affecting Telehealth Use Among US Adults During the COVID-19 Pandemic: A Cross-sectional Analysis
Abstract
Background
Tele visits reduce the risk of infections in communities, allow individuals to access primary or specialty care consultations without in-person contacts, and enhance follow-up care among patients with chronic conditions. COVID-19 pandemic created significant barriers to in-person healthcare utilization and saw introduction of waivers and flexibilities to encourage telehealth use. Analysis of telehealth utilization during this period can identify individual-level enabling factors and barriers when need for telehealth was high.
Research Question
What are the individual-related factors that affected telehealth use in the USA during COVID-19 pandemic?
Methods
Using Anderson Behavioral Model for Healthcare Utilization as the conceptual framework, potential factors affecting telehealth use were identified. For empirical analysis, 2021 National Health Interview Survey (NHIS) data were used. Telehealth use was defined as having an appointment with a doctor, nurse, or other health professionals by video or telephone. Several predisposing (age, gender, race), enabling (education, income, insurance, location), and need for healthcare service (high blood pressure, diabetes, COVID-19) related factors were analyzed using STATA 17.0.
Results
Out of 29,217 adults in NHIS, 11,384 (38.96%) used telehealth during COVID pandemic. Telehealth use rate was lower in younger adults (27.84% vs. 43.15% for older), in men (31.72% vs. 41.97%), in Hispanic group (32.76%; 33.08% for non-Hispanic Blacks; vs. 39.16% for non-Hispanic Whites), in individuals with less than high school education (28.71% vs. 46.56%), in poverty group (33.27% for below poverty vs. 40.57%), among those without health insurance coverage (13.90% vs. 39.67%), and in rural areas (29.43% vs. 40.33%). Poor health status, presence of chronic conditions, and diagnosis of COVID during the year also affected telehealth use.
Conclusion
The individual factors affecting telehealth use identify specific disadvantaged target groups when in-person healthcare utilization becomes difficult. Reimbursing providers for telehealth is important but many other factors adversely affect its effective utilization.
Keywords
Telehealth; Anderson Behavioral Model for Healthcare Utilization; National Health Interview Survey (NHIS).
Factors Affecting Telehealth Use Among US Adults During the COVID-19 Pandemic: A Cross-sectional Analysis
Background
Tele visits reduce the risk of infections in communities, allow individuals to access primary or specialty care consultations without in-person contacts, and enhance follow-up care among patients with chronic conditions. COVID-19 pandemic created significant barriers to in-person healthcare utilization and saw introduction of waivers and flexibilities to encourage telehealth use. Analysis of telehealth utilization during this period can identify individual-level enabling factors and barriers when need for telehealth was high.
Research Question
What are the individual-related factors that affected telehealth use in the USA during COVID-19 pandemic?
Methods
Using Anderson Behavioral Model for Healthcare Utilization as the conceptual framework, potential factors affecting telehealth use were identified. For empirical analysis, 2021 National Health Interview Survey (NHIS) data were used. Telehealth use was defined as having an appointment with a doctor, nurse, or other health professionals by video or telephone. Several predisposing (age, gender, race), enabling (education, income, insurance, location), and need for healthcare service (high blood pressure, diabetes, COVID-19) related factors were analyzed using STATA 17.0.
Results
Out of 29,217 adults in NHIS, 11,384 (38.96%) used telehealth during COVID pandemic. Telehealth use rate was lower in younger adults (27.84% vs. 43.15% for older), in men (31.72% vs. 41.97%), in Hispanic group (32.76%; 33.08% for non-Hispanic Blacks; vs. 39.16% for non-Hispanic Whites), in individuals with less than high school education (28.71% vs. 46.56%), in poverty group (33.27% for below poverty vs. 40.57%), among those without health insurance coverage (13.90% vs. 39.67%), and in rural areas (29.43% vs. 40.33%). Poor health status, presence of chronic conditions, and diagnosis of COVID during the year also affected telehealth use.
Conclusion
The individual factors affecting telehealth use identify specific disadvantaged target groups when in-person healthcare utilization becomes difficult. Reimbursing providers for telehealth is important but many other factors adversely affect its effective utilization.
