Abstract
Transportation disruptions caused by COVID-19 have exacerbated difficulties in health care delivery and access, which may lead to changes in health care use. This study uses mobile device data from SafeGraph to explore the temporal patterns of visits to health care points of interest (POIs) during 2020 and examines how these patterns are associated with socio-demographic and spatial characteristics at the Census Block Group level in North Carolina. Specifically, using the K-medoid time-series clustering method, we identify three distinct types of temporal patterns of visits to health care facilities. Furthermore, by estimating multinomial logit models, we find that Census Block Groups with higher percentages of elderly persons, minorities, low-income individuals, and people without vehicle access are areas most at-risk for decreased health care access during the pandemic and exhibit lower health care access prior to the pandemic. The results suggest that the ability to conduct in-person medical visits during the pandemic has been unequally distributed, which highlights the importance of tailoring policy strategies for specific socio-demographic groups to ensure equitable health care access and delivery.
Highlights
Transportation is widely recognized as a critical factor in health care access (Syed et al, 2013)
The purpose of this study is to assess the impacts of COVID-19 on health care access in North Carolina (NC)
We examine the association between these temporal patterns and the sociodemographic and spatial characteristics of Census Block Groups (CBGs) in NC
Summary
Transportation is widely recognized as a critical factor in health care access (Syed et al, 2013). Hospitals placed restrictions on whether patients could have individuals accom pany them to appointments While these policies reduced access to inperson health care, providers and insurers increased support for tele medicine visits (Chen et al, 2021; Medicare Telemedicine Health Care Provider Fact Sheet, 2020). The COVID-19 pandemic drastically changed peoples’ access to and use of health care services These changes include health insurance loss, health facility closure, and the increasing use of telemedicine (Chen et al, 2021). More than 40 million Americans lost their jobs, which further caused many of them to lose their employer-based health insurance (Blumenthal et al, 2020) As a result, they may have been forced to delay necessary but noncritical treatments (Blumenthal et al, 2020). Minorities and people with low educational attainment and low incomes have experienced disproportionate job loss and delayed care (Kurtzleben, 2020)
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