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Sociology Colloquium, 3/31/2021

Small in Size, Selective in Location, Limited on Healthcare Access Improvement: Exploring the Accessibility of Micro-Hospitals in Texas Through Demographic Spatial Modeling

Jingqiu Ren, Ryan Earl, and Dr. Ernesto Amaral, Texas A&M UniversityMicro Hospital Colloquium

Micro-hospitals are a new form of for-profit healthcare facility with rapid expansion in some parts of the country. Micro-hospitals in Texas continue to grow without specific regulatory schemes, public understanding, or policy guidance on their commercial outcomes versus their social accountability. Our project aims to define and delineate hospital service areas based on driving distances from micro- and regular hospitals, as well as examine how their population characteristics may be associated with the location choices of micro-hospitals in Texas. Specifically, we 1) estimated hospital service areas (catchment areas) with a spatial model based on advanced Geographic Information System (GIS) methods using a proprietary ESRI traffic network; 2) assigned population socioeconomic measures to these catchment areas from the 2014–2018 American Community Survey 5-Year Estimates, weighted with an empirically tested Gaussian distribution; 3) used two-tailed t-tests to compare population characteristics means between micro hospital and regular hospital catchment areas, and 4) conducted logistic regressions to examine relationships between selected population variables and the odds of micro-hospitals locating in their neighborhoods. Population socioeconomic characteristics have long been associated with healthcare inequality. We found micro hospitals in Texas tend to serve a population less stressed in healthcare access compared to those who are more in need as measured by various dimensions of disadvantages. We hope our analysis will help foster regulatory and structural policy decisions that balance growing healthcare delivery innovations and their social accountability.

Micro Hospital Colloquium

March 31, 2021
Wednesday, 12–1:30pm
Zoom session
Meeting ID: 929 0510 2934
Passcode: 006910

If you cannot join with video, you can connect to the Zoom session via phone: 1–346–248–7799