Date of Conferral

2021

Degree

Doctor of Healthcare Administration (D.H.A.)

School

Health Services

Advisor

Ronald V. Bucci

Abstract

End-stage renal disease (ESRD) is increasingly a problem in the United States, and factors such as race/ethnicity and gender may not only worsen the risk of the disease but also correspond to worse treatment access. This is significant because ESRD is a heavy economic burden not only on patients, but on caregivers and the health care system, especially as disparities remain between different demographic groups. The purpose of this quantitative nonexperimental, historical, correlational design was to determine the extent to which gender and race/ethnicity predict 30-day readmission rates after hospitalization for ESRD patients. The theoretical framework for the current study was the theory of the determinants of avoidable readmissions in ESRD. The three research questions were to what extent patient gender predicts 30-day hospital readmission rate for ESRD patients, to what extent does patient race/ethnicity predicts 30-day hospital readmission rates, and are there any significant interactions terms in a combined prediction model using gender and race/ethnicity. Data were gathered from Data.gov and the United States Renal Data System. Regression analysis was used to analyze the data. The study found that gender, race, and income can all be predictors of ESRD hospitalization. The results have important implications for improving interventions to reduce ESRD hospitalization, thereby leading to positive social change by reducing both the personal and societal costs associated with the disease

Download

Share

 
COinS