Primary Submission Category: Aging
Resilience of Non-Corporate Assisted Living Facilities During the COVID-19 Pandemic
Authors: Nia Washington, Lindsey Smith, Kali Thomas, Momotazur Rahman, Eric Jutkowitz, Cassandra L. Hua, Sean Huang,
Presenting Author: Nia Washington*
BACKGROUND:
The COVID-19 pandemic has had a profound impact on the healthcare sector, particularly on assisted living (AL) communities, which provide residential care and assistance with activities of daily living to older adults. Previous research has documented the shift towards more corporate chain operated ALs following the financial stressors COVID-19 posed. While much research has focused on facility closures and their effects on communities, there is a gap in understanding the characteristics of non-chain, independent ALs that demonstrated resilience by remaining operational throughout the pandemic. This study aims to identify the community-level factors associated with the resilience of standalone ALs during the COVID-19 pandemic.
RESEARCH QUESTION:
What community-level socioeconomic and demographic factors are associated with the resilience of non-chain assisted living facilities during the COVID-19 pandemic?
METHODS:
This study utilizes data from the 2019 American Community Survey (ACS) with a national directory list of assisted living facilities (ALs) that were operational from 2019-2023, and a novel database created by our team describing chain membership, as determined using business listings and corporate hierarchies. We excluded corporate chain operated ALs and those not operational over the entire study period. Descriptive statistics are used to characterize the communities where the ALs are located, including socioeconomic and demographic variables such as median household income, poverty rates, population density, and the proportion of the population age 65 and older by capacity to identify any size-related trends in resilience. ACS and AL datasets are joined by location. COVID-19 incidence rates at the county level, obtained from the CDC, are included to control for local pandemic severity. Statistical tests, such as t-tests and chi-square tests, are used to compare community characteristics of resilient ALs with those that closed during the pandemic. Regression analysis is conducted to assess the relationship between community factors and AL resilience, controlling for regional differences and local COVID-19 incidence rates.
Preliminary Results:
We identified 616 large non-chain ALs (25+ capacity) and 14,389 small non-chain (25> capacity) ALs. Among non-chain ALs, those that remained operational during the pandemic were located in communities with significantly higher median household incomes (M = 68,420, SD = 20,350) compared to those that closed (M = 54,110, SD = 19,780; p < 0.001). Preliminary results indicate that resilient ALs, those that remained operational throughout the pandemic, were more likely to be located in communities with higher median incomes (p < 0.001), lower poverty rates (p < 0.01), and higher population densities (p < 0.05), compared to non-chain ALs that closed during the study period. Regression analysis revealed that higher median income and lower poverty rates were significantly associated with AL resilience (p < 0.05), even after controlling for regional differences and local COVID-19 incidence rates. Additionally, ALs in urban areas were more likely to remain operational compared to those in rural areas (p < 0.01).