Date of Conferral

5-22-2025

Date of Award

May 2025

Degree

Ph.D.

School

Health Services

Advisor

Diana Naser

Abstract

Nursing facilities experienced heightened unfavorable outcomes related to quality of care and staffing patterns during the COVID-19 pandemic. The purpose of this quantitative, quasi-experimental, retrospective study was to determine if there was a relationship between nursing home administrator turnover, total nurse staffing (i.e., LPN, RN, and nurse aides) hours per resident per day, and the quality of care as measured by the Long Stay Quality Measure (LSQM) rating in Texas after the COVID-19 pandemic in 2023. The Donabedian model, using the elements of structure, process, and outcomes, served as the theoretical framework for this study. Structure was represented by the nursing home; process included staff hours and administrator turnover; and outcome referred to the quality of care, as measured by LSQM ratings in nursing homes. Using 2023 data from the Center for Medicare and Medicaid Services secondary data sets for nursing homes in Texas counties, an ordinal logistic regression analysis was conducted. The results demonstrated that low administrator turnover was associated with significantly increased odds of achieving higher LSQM ratings (b = −0.33, p = .005) and increased nurse staffing hours correlated with lower odds of higher LSQM ratings (b = −0.382, p < .001). The findings of this study have the potential to promote positive social change by providing knowledge of the relationships between administrator turnover and total nurse staffing (i.e., LPN, RN, and nurse aides) hours per resident per day on quality of care provided in nursing homes. These results may also reveal how quality of care in nursing homes continues to evolve in the post-COVID-19 pandemic era.

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