Defining the Current Landscape, Attitudes, and Perceived Barriers of Virtual Medicine in Underserved Populations

Abstract

PURPOSE: Virtual medicine (VM) use increased during the COVID-19 pandemic as it represented a safe alternative to traditional face-to-face health care delivery. This prospective cross-sectional study aimed to characterize preferences and perceived barriers to VM on the basis of language and specific sociodemographic variables while also identifying particular subpopulations at risk of dissatisfaction regarding VM. METHODS: An institutional review board–approved, 23-item questionnaire was offered in English and Spanish. Examined variables included demographic information, preferences, and perceived barriers regarding VM. Multivariable analysis was performed to determine the association between demographic variables and participants' preferences and perceived barriers. RESULTS: Fewer Hispanic and underserved patients (N = 241) had received oncological care through VM (28.9% v 30.8%) despite comparable preferences and levels of satisfaction regarding the incorporation of VM in health care delivery (21.6% v 25.4%; 68.7% v 82.1%), respectively, with no significant difference by age, level of education, marital status, or Hispanic ethnicity, although Spanish as primary language was statistically significant ( P = .001). Although Hispanic and underserved rely more on social media to receive health information (26.5% v 24.7%), they have more technical barriers. They were up to 2.9 times more likely not to have a phone/iPad/similar or access broadband connectivity. CONCLUSION: Given the shift toward outpatient and home-based care, an aging population, and cultural appropriations, VM excitedly allows the reincorporation of family/caregiver in medical engagement. Hispanic patients are equally interested and satisfied in receiving oncological care through VM, but fewer are currently using it. Barriers are predominantly technical and targetable with appropriate policies to help overcome technological barriers on the basis of language, ethnic, locoregional, and sociodemographic variables.