Telemedicine Adoption Before, During, and After COVID-19: The Role of Socioeconomic and Built Environment Variables

Term Start:

September 1, 2023

Term End:

May 31, 2024




Covid-19, Longitudinal, Telemedicine

Thrust Area(s):

Equity and Understanding User Needs

University Lead:

The University of Texas at Austin


Chandra Bhat

In this research, we focus our investigation on the telemedicine adoption preferences of patients/consumers. Our comprehensive approach contributes to advancing the existing body of knowledge in five distinct ways. First, we use rigorous multivariate econometric models that accommodate multiple sociodemographic and built environment (BE) variables at once rather than simple bivariate correlations of determinant factors with telemedicine adoption. Second, the framework is structured to discern the shifts in the effects of the factors affecting telemedicine adoption between the before- and after-COVID periods. This helps gain a deeper understanding of how socioeconomic and BE variables influenced telemedicine adoption before the pandemic and how the willingness of different segments of society to engage in telemedicine shifted as a result of the pandemic. Third, proposed multivariate model system recognizes that unobserved individual factors (such as technology savviness) that elevate telemedicine adoption before the pandemic may also affect adoption during the pandemic, and collectively influence an individual’s intention to use telemedicine in the post-pandemic period. Not accounting for such intra-individual correlation effects due to unobserved individual-level factors variables will, in general, provide biased estimates of the evolution pattern of telemedicine adoption over time. In our study, the longitudinal data comprises responses from the same individuals across three specific time periods, offering a unique advantage in quantifying the causal effect of the pandemic on telemedicine use. Fourth, our study explores the reasons for using or not using telemedicine in the after-COVID period from the patient’s viewpoint. We conduct a consumer-focused analysis that provides unique insights into the motivations, preferences, and concerns of different patient segments regarding telemedicine. Specifically, in the after-COVID period, for telemedicine adopters, we jointly model the reasons for adoption using multivariate binary probit models. Similarly, in the after-COVID period, for non-adopters, we use multivariate binary probit models to jointly analyze cited reasons for not adopting telehealth. This can inform healthcare providers, policymakers, and other stakeholders seeking to sustain telemedicine adoption post-COVID. Fifth, our study is the first that we are aware of in the travel behavior literature that focuses on telemedicine adoption. Earlier studies related to virtual participations have investigated tele-adoption in the context of work, grocery shopping, and non-grocery shopping, but have not considered telemedicine adoption. However, telemedicine adoption can also have transportation ramifications, just as virtual participation in other types of activities can (including individuals potentially appropriating the freed-up time for pursuing other activities). In this regard, we hope that our study will open up additional research in studying the travel implications of tele-participation in medical-related activities. This should be of particular interest in the context of medical accessibility for the increasingly aging population of many countries, including the United States.

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