Travel Distance Between Participants in US Telemedicine Sessions With Estimates of Emissions Savings: Observational Study.

Background: Digital health and telemedicine are potentially important strategies to decrease health care's environmental impact and contribution to climate change by reducing transportation-related air pollution and greenhouse gas emissions. However, we currently lack robust national estimates of emissions savings attributable to telemedicine.
Objective: This study aimed to (1) determine the travel distance between participants in US telemedicine sessions and (2) estimate the net reduction in carbon dioxide (CO ₂ ) emissions attributable to telemedicine in the United States, based on national observational data describing the geographical characteristics of telemedicine session participants.
Methods: We conducted a retrospective observational study of telemedicine sessions in the United States between January 1, 2022, and February 21, 2023, on the doxy.me platform. Using Google Distance Matrix, we determined the median travel distance between participating providers and patients for a proportional sample of sessions. Further, based on the best available public data, we estimated the total annual emissions costs and savings attributable to telemedicine in the United States.
Results: The median round trip travel distance between patients and providers was 49 (IQR 21-145) miles. The median CO ₂ emissions savings per telemedicine session was 20 (IQR 8-59) kg CO ₂ ). Accounting for the energy costs of telemedicine and US transportation patterns, among other factors, we estimate that the use of telemedicine in the United States during the years 2021-2022 resulted in approximate annual CO ₂ emissions savings of 1,443,800 metric tons.
Conclusions: These estimates of travel distance and telemedicine-associated CO ₂ emissions costs and savings, based on national data, indicate that telemedicine may be an important strategy in reducing the health care sector's carbon footprint.
(©Mollie R Cummins, Sukrut Shishupal, Bob Wong, Neng Wan, Jiuying Han, Jace D Johnny, Amy Mhatre-Owens, Ramkiran Gouripeddi, Julia Ivanova, Triton Ong, Hiral Soni, Janelle Barrera, Hattie Wilczewski, Brandon M Welch, Brian E Bunnell. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 15.05.2024.)