Telemedicine versus in-Person Primary Care: Impact on Visit Completion Rate in a Rural Appalachian Population.

INTRODUCTION: The use of telemedicine increased during the global Coronavirus disease 2019 (COVID-19) pandemic. Rural populations often struggle with adequate access to care while simultaneously experiencing multiple health disparities. Yet, telemedicine use during the COVID-19 pandemic has been understudied on its effect on visit completion in rural populations. The primary purpose of this study is to understand how telemedicine delivery of family medicine care affects patient access and visit completion rates in a rural primary care setting. METHODS: We performed a retrospective cohort study on primary care patient visits at an academic family medicine clinic that serves a largely rural population. We gathered patient demographic and visit type and completion data on all patients seen in the West Virginia University Department of Family Medicine between January 2019 and November 2020. RESULTS: The final sample included 110,999 patient visits, including 13,013 telemedicine visit types. Our results show that telemedicine can increase completion rates by about 20% among a sample of all ages and a sample of adults only. Working-aged persons are more likely to complete telemedicine visits. Older persons with higher risk scores are more likely to complete their visits if they use telemedicine. CONCLUSIONS: Telemedicine can be a tool to improve patient access to primary care in rural populations. Our findings suggest that telemedicine may facilitate access to care for difficult-to-reach patients, such as those in rural areas, as well as those who have rigid work schedules, live longer distances from the clinic, have complex health problems, and are from areas of higher poverty and/or lower education.

Explaining the spatial variation in American life expectancy.

Since 1980, average life expectancy in the United States has increased by roughly five years; however, in recent years it has been declining. At the same time, spatial variation in life expectancy has been growing. To explore reasons for this trend, some researchers have focused on morbidity factors, while others have focused on how mortality trends differ by personal characteristics. However, the effect community characteristics may play in expanding the spatial heterogeneity has not yet been fully explored. Using a spatial Durbin error model, we explore how community and demographic factors influence county-level life expectancy in 2014, controlling for life expectancy in 1980 and migration over time, and analyzing men and women separately. We find that community characteristics are important in determining life expectancy and that there may be a role for policy makers in addressing factors that are associated with lower life expectancy in some regions.