Identifying Factors Associated with Asynchronous and Synchronous Telehealth Use Across Age Groups in the Post-Pandemic Era: A Retrospective Analysis of the Health Information National Trends Survey (Preprint)

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Abstract
BACKGROUND Since the COVID-19 pandemic, telehealth has become a core component of modern healthcare, encompassing both synchronous (real-time video/phone) and asynchronous (patient portal) services. However, older adults often face more barriers to using these technologies compared to younger populations, potentially widening gaps in healthcare access. OBJECTIVE This study comprehensively examines factors influencing the adoption of asynchronous and synchronous telehealth in the post-pandemic era. It compares the two modalities and highlights distinct usage patterns across age groups, offering insights to inform more targeted telehealth strategies. METHODS We analyzed data from the 2022 and 2024 Health Information National Trends Survey (HINTS) 6 and 7, focusing on three outcomes over the past 12 months: 1) frequency of asynchronous telehealth use (continuous), 2) use of synchronous telehealth (binary), and 3) no engagement with any telehealth services (binary). Key variables included demographics, socio-economic status, technology familiarity, and healthcare behaviors. Age groups were categorized as young (18–49), middle-aged (50–64), and older adults (65+). Interaction terms between age and other variables were included to uncover age-specific patterns. We employed penalized linear and logistic regression models using the least absolute shrinkage and selection operator (LASSO) to address multicollinearity and bootstrapping to assess the variability of the estimated coefficients. RESULTS Of the 12,865 respondents, 36.1% (4,638) were aged 65 or older. Asynchronous and synchronous telehealth were used by 65.2% and 61.6% of participants, respectively. While age group alone was not a significant predictor, older adults exhibited distinct patterns. For example, older patients who used one telehealth modality were less likely to use the other (Odds Ratio [OR]=0.91, 95% Confidence Interval [CI]=[0.85,0.98], P=.008 for asynchronous predicting synchronous use; coefficient [coef]=-0.12, 95% CI=[-0.23, -0.02], P=.019 for the reverse), despite strongly positive associations in the general population. Older adults who frequently received care were less likely to use asynchronous telehealth (coef=-0.07, 95% CI=[-0.10, -0.04], P<.001), which is contrary to trends in other age groups. Additionally, the following associations stood out relative to the overall population: tech-savvy older adults were more likely to use asynchronous telehealth (coef=0.28, 95% CI=[0.17, 0.39], P<.001), while those in non-metropolitan areas were less likely to use synchronous telehealth (OR=0.74, 95% CI=[0.56, 1.00], P=.048). Finally, older Black or African American patients were less likely to use asynchronous telehealth (coef=-0.21, 95% CI=[-0.35, -0.07], P=.004), which is not observed in the broader population. CONCLUSIONS This study reveals nuanced differences in telehealth usage among older adults, emphasizing the need for age-specific strategies. These insights can guide more effective implementation of both asynchronous and synchronous telehealth services, particularly for older populations.

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