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Title:Geospatial analysis of preventable emergency department visits in Chicago, IL
Author(s):Fishman, Jamie Andrew
Department / Program:Geography & Geographic InfoSci
Discipline:Geography
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Geographic Information System (GIS)
health care geography
Abstract:The use of hospital emergency departments (EDs) for conditions considered treatable in a primary care setting (PCED conditions) has become an increasingly prevalent health care inefficiency in the United States, leading to suboptimal primary care, significant ED overcrowding, and substantially increased costs to both payer and provider. Previous studies have attempted to untangle the various contributing factors to such misuse, including sociodemographic, health, and insurance status variables. While a few studies have integrated geographically-informed components into their analyses such as urban vs. rural distinction of hospital, no studies of misuse of EDs for PCED conditions were identified that utilized geographic information systems (GIS) to understand the locations of residents who are prone to this misuse as well to understand the contributions of spatially-derived health care accessibility indexes toward this misuse. Therefore, to determine the contribution of both spatial and non-spatial variables to PCED utilization, a multilevel logit regression was fit to over 750,000 ED diagnoses from four academic hospitals in Chicago. This research found strong geographic clustering of PCED utilization in the Chicago study area. Additionally, results showed that individual-level variables such as gender, race, ethnicity, insurance status, and age were associated with PCED utilization, as were area-level variables such as living in areas with low access to primary care clinics and areas of medical underservice. Overall, this research points to the importance of including geography alongside individual sociodemographic attributes into a multilevel study of PCED utilization and demonstrates the utility of using GIS to analyze clinical data for population health research in an urban setting.
Issue Date:2015-04-27
Type:Thesis
URI:http://hdl.handle.net/2142/78400
Rights Information:Copyright 2015 Jamie Fishman
Date Available in IDEALS:2015-07-22
Date Deposited:May 2015


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