RAPID: Availability and Utilization of Key Healthcare Resources during the COVID-19 Pandemic in Rural Texas

Texas State University - San Marcos, San Marcos TX

Investigators

Abstract

The COVID-19 pandemic has affected urban and rural populations quite differently. Because of the high degree of community transmission, large, densely populated urban centers have experienced the vast majority of casualties in the early phases of the pandemic, but rural hospitals have also been affected as the pandemic spreads across the country. This Rapid Response Research (RAPID) grant will support the collection of time-sensitive data to document preparedness levels at rural hospitals over the course of the pandemic. Through a collaboration with the Texas Department of State Health Services (DSHS), this project will collect and archive data from four trauma regions (two rural, two urban) to identify unique challenges and opportunities faced by rural hospitals. COVID-19 is expected to eventually reach rural communities before an effective vaccine is available and the project has the potential to provide decision support to public health administrators to better manage critical resources during a pandemic or other mass casualty event. Working with the Center for Health Statistics of the Texas DSHS, this project will collect longitudinal data regarding COVID-19 testing, case reports, staffed hospital and ICU beds, deidentified admission and discharge data, and outpatient procedures for hospitals in four regions of the state of Texas. The project will also collect valuable subjective data by interviewing hospital decision-makers about their operational decisions. By collecting these data from regions supporting both rural and urban healthcare systems, the project will provide useful information on differences in urban and rural healthcare system response to the COVID-19 pandemic. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.