Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Master of Science

Program

Epidemiology and Biostatistics

Supervisor

Garg, Pallav

2nd Supervisor

Ali, Shehzad

Co-Supervisor

Abstract

Social determinants of health play a crucial role in explaining the variation of potentially avoidable hospitalizations (PAH) due to Ambulatory Care Sensitive Conditions (ACSCs). Utilizing data from the National Inpatient Sample from 2018 to 2020 in the United States, this study conducted retrospective cohort analyses to explore the relationships between sociodemographic factors, specifically income, race, geography, age, and sex and PAH. Our approach used multilevel logistic regression models to adjust for potential confounders and account for clustering of admissions within hospitals. Of the 17,629,891 hospital admissions examined in this study, 1,868,609 (10.6%) were attributable to ACSCs. Our results indicate that individuals of black or Hispanic ethnicity, lower income groups, and people living in the southern region had higher admissions due to ACSCs. These associations were consistent when evaluating individual ACSCs, being more pronounced for chronic conditions. This study highlights the need for focused policy interventions and healthcare strategies aimed at reducing these disparities.

Summary for Lay Audience

The trend of increasing healthcare expenditures in the United States is a growing concern. A significant part of these costs is attributed to avoidable hospital stays due to Ambulatory Care Sensitive Conditions (ACSCs). These are cases where appropriate and timely outpatient primary care could prevent the need for hospital admissions. Research has shown that social determinants of health (SDH) significantly influence variations in these hospital admissions. These disparities are linked to various factors, including poverty, unemployment, education levels, and health insurance access. However, the limited breadth of representation in these studies highlights a crucial gap, necessitating further investigation with more inclusive and diverse data sets to fully understand and address these health inequities.

Our current study addresses these gaps by utilizing a nationally representative database to investigate how race, income, geography, age, and sex correlate with potentially avoidable hospitalizations (PAH) due to ACSCs among hospitalized patients in the US from 2018 to 2020. Employing comprehensive biostatistical methods, we analyzed these relationships, taking into account the influence of various individual-level and hospital-level characteristics. We found that Black and Hispanic patients, those with lower socioeconomic status, and individuals residing in the South were more likely to have in-hospital admissions due to ACSCs. This pattern persisted across individual ACSCs and their relationship with SDH. By examining the link between SDH and PAH, we gain insights into the distribution of adverse health outcomes across different demographic groups in the US. Our findings provide valuable guidance for the development of targeted policy interventions and healthcare strategies aimed at addressing these disparities and advancing health equity.

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