Patient Satisfaction With Telehealth and Experiences During the COVID-19 Pandemic Among Uninsured Free Clinic Patients.

The COVID-19 pandemic is a significant public health issue especially for underserved populations. Little is known about patient satisfaction with telehealth among free clinic patients or other underserved populations. The purpose of this study is to examine factors associated with patient satisfaction with in-person services and telehealth during the pandemic and describe the experiences during the pandemic among free clinic patients. Data were collected from 628 uninsured English- and Spanish-speaking patients of a free clinic using an online survey from June to August in 2020. Free clinic patients are satisfied both with in-person services and telehealth. Factors associated with satisfaction were slightly different for in-person services and telehealth. The major experiences during the pandemic were related to food/diet and physical inactivity. This study examined a new trend in patient satisfaction and is important because telehealth may be a stepping-stone on how to handle future doctor visits for underserved populations. Furthermore, as the pandemic rapidly develops and changes daily life experiences, the uninsured population faces imminent impacts in various aspects of their life experiences.

Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases.

The spread of COVID-19 is not evenly distributed. Neighborhood environments may structure risks and resources that produce COVID-19 disparities. Neighborhood built environments that allow greater flow of people into an area or impede social distancing practices may increase residents' risk for contracting the virus. We leveraged Google Street View (GSV) images and computer vision to detect built environment features (presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires). We utilized Poisson regression models to determine associations of built environment characteristics with COVID-19 cases. Indicators of mixed land use (non-single family home), walkability (sidewalks), and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were connected with fewer COVID-19 cases. Percent black and percent with less than a high school education were associated with more COVID-19 cases. Our findings suggest that built environment characteristics can help characterize community-level COVID-19 risk. Sociodemographic disparities also highlight differential COVID-19 risk across groups of people. Computer vision and big data image sources make national studies of built environment effects on COVID-19 risk possible, to inform local area decision-making.