Oliver T Nguyen1,2, Amelia K Watson1,3, Kartik Motwani1,4, Chloe Warpinski1, Katelin McDilda1,5, Carlos Leon1,6, Neel Khanna1,5, Ryan W Nall1,7, Kea Turner8,9. 1. Department of Community Health and Family Medicine, University of Florida, Gainesville, Florida, USA. 2. Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, USA. 3. Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina, USA. 4. Department of Neurosurgery, University of Florida, Gainesville, Florida, USA. 5. College of Public Health and Health Professions, University of Florida, Gainesville, Florida, USA. 6. Department of Psychology, University of Florida, Gainesville, Florida, USA. 7. Division of General Internal Medicine, University of Florida, Gainesville, Florida, United States. 8. Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, Florida, USA. 9. Department of Oncological Sciences, University of South Florida, Tampa, Florida, USA.
Abstract
Background: Disparities in telemedicine use by race, age, and income have been consistently documented. To date, research has focused on telemedicine use among patients with adequate insurance coverage. To address this gap, this study identifies patient-level factors associated with telemedicine use during the coronavirus (COVID-19) pandemic among one free clinic network's patients who are underinsured or uninsured. Methods: Electronic health record data were reviewed for patient-level data on patients seen from March 2020 to September 2020. Patients were grouped by telemedicine use history. We controlled for sociodemographic factors (e.g., age, race/ethnicity) and comorbidities. Logistic regression analyses were conducted. Results: Across 198 adult patients, 56.6% received telemedicine care. Of these, 99.1% elected for audio-only telemedicine instead of video telemedicine. Telemedicine use was more likely among those living within 15 miles of their clinic (adjusted odds ratio [aOR] = 4.43, 95% confidence interval [CI] 1.70-11.53). It was less likely to be used by older patients (aOR = 0.97, 95% CI 0.94-1.00), patients of male sex (aOR = 0.85, 95% CI 0.18-0.92), and those establishing care as a new patient (aOR = 0.01, 95% CI 0.00-0.07). Conclusion: The moderate usage of telemedicine suggests that its implementation in free clinics may be feasible. Solutions specific to patients with smartphone-only internet access are needed to improve the use of video telemedicine as smartphone-specific factors (e.g., data use limits) may influence the ability for underserved patients to receive video telemedicine.
Background: Disparities in telemedicine use by race, age, and income have been consistently documented. To date, research has focused on telemedicine use among patients with adequate insurance coverage. To address this gap, this study identifies patient-level factors associated with telemedicine use during the coronavirus (COVID-19) pandemic among one free clinic network's patients who are underinsured or uninsured. Methods: Electronic health record data were reviewed for patient-level data on patients seen from March 2020 to September 2020. Patients were grouped by telemedicine use history. We controlled for sociodemographic factors (e.g., age, race/ethnicity) and comorbidities. Logistic regression analyses were conducted. Results: Across 198 adult patients, 56.6% received telemedicine care. Of these, 99.1% elected for audio-only telemedicine instead of video telemedicine. Telemedicine use was more likely among those living within 15 miles of their clinic (adjusted odds ratio [aOR] = 4.43, 95% confidence interval [CI] 1.70-11.53). It was less likely to be used by older patients (aOR = 0.97, 95% CI 0.94-1.00), patients of male sex (aOR = 0.85, 95% CI 0.18-0.92), and those establishing care as a new patient (aOR = 0.01, 95% CI 0.00-0.07). Conclusion: The moderate usage of telemedicine suggests that its implementation in free clinics may be feasible. Solutions specific to patients with smartphone-only internet access are needed to improve the use of video telemedicine as smartphone-specific factors (e.g., data use limits) may influence the ability for underserved patients to receive video telemedicine.
Entities:
Keywords:
digital divide; safety-net; telemedicine
Authors: Eli M Cahan; Jay Maturi; Paige Bailey; Susan Fernandes; Ananta Addala; Sara Kibrom; Jill R Krissberg; Stephanie M Smith; Sejal Shah; Ewen Wang; Olga Saynina; Paul H Wise; Lisa J Chamberlain Journal: Acad Pediatr Date: 2022-03-19 Impact factor: 2.993