Publication Date

2023

Document Type

Dissertation/Thesis

First Advisor

LUO, WEI

Degree Name

Ph.D. (Doctor of Philosophy)

Legacy Department

Department of the Earth, Atmosphere and Environment (EAE)

Abstract

Health disparity has been a persistent concern in the United States, and the COVID-19 pandemic has brought more attention to this ongoing challenge. Improving access to healthcare is a crucial step toward achieving health equity and starts with accurately measuring and portraying the existing landscape of access to healthcare. Even though numerous spatial accessibility models have been proposed to measure the spatial accessibility to healthcare, many gaps still exist. The main purpose of this dissertation is to develop novel models and leverage recently available datasets for a more accurate portrayal of true spatial accessibility. Three models were developed to address related but different aspects of spatial accessibility to healthcare. First, a Supply-Demand Adjusted Two-step Floating Catchment Area (SDA-2SFCA) model was introduced as an enhancement of the 2SFCA by incorporating aspatial factors such as insurance status, age, and gender to more precisely capture different demands. Second, to better measure access to telehealth, the Enhanced Two-step Virtual Catchment (E2SVCA) model was developed by utilizing the FCC broadband dataset and a stepwise weight function. Different representation of broadband speed at the Census Block level was also investigated. Third, geospatial big data based on real-world foot traffic from anonymized mobile devices was leveraged to explore revealed spatial accessibility, which was then compared to potential spatial accessibility. The findings suggest that integrating aspatial social demographic data in SDA-2SFCA model dramatically enhances the portrayal of spatial accessibility. The use of a stepwise weight function in E2SVCA is shown to significantly improve telehealth accessibility measurement compared to the binary function in the 2SVCA model. Finally, past potential spatial accessibility measures tend to consistently overestimate the true spatial accessibility, which is more closely reflected by the revealed spatial accessibility based on the real-world SafeGraph data. The SafeGraph-based revealed spatial accessibility is a better option for healthcare decision-makers in formulating policies aimed at achieving healthcare equity in the United States.

Extent

152 pages

Language

en

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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