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Text
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URL Address
<a href="http://doi.org/10.1016/j.jemermed.2016.05.058" target="_blank" rel="noreferrer noopener">http://doi.org/10.1016/j.jemermed.2016.05.058</a>
Pages
466–470
Issue
4
Volume
51
Dublin Core
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Title
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Patient Insurance Profiles: A Tertiary Care Compared to Three Freestanding Emergency Departments.
Publisher
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The Journal of emergency medicine
Date
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2016
2016-10
Subject
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Emergency Service; Emergency Service – Statistics and Numerical Data; freestanding emergency department; Health – Statistics and Numerical Data; Health – Trends; Health/*statistics & numerical data/trends; Hospital/*statistics & numerical data; Hospitals; Human; Humans; insurance; Insurance; Medicaid – Statistics and Numerical Data; Medicaid/statistics & numerical data; Medically Uninsured – Statistics and Numerical Data; Medically Uninsured/statistics & numerical data; Medicare – Statistics and Numerical Data; Medicare/statistics & numerical data; Retrospective Design; Retrospective Studies; Special – Statistics and Numerical Data; Tertiary Care Centers/statistics & numerical data; United States; Urban – Statistics and Numerical Data; Urban/*statistics & numerical data
Creator
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Simon Erin L; Griffin Gregory; Orlik Kseniya; Jia Zhenyu; Hayslip Dave; Kobe Daniel; Jouriles Nicholas
Description
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BACKGROUND: It has been speculated that freestanding emergency departments (FEDs) draw more affluent, better-insured patients away from urban hospital EDs. It is believed that this leaves urban hospital-based EDs less financially secure. OBJECTIVE: We examined whether the distribution of patients with four types of insurance (self-pay, Medicaid, Medicare, and private) at the main ED changed after opening three affiliated FEDs, and whether the insurance type distribution was different between main ED and FEDs and between individual FEDs. METHODS: A retrospective analysis of insurance status of all patients presenting to our EDs from July 2006 through August 2013. Insurance was divided into self-pay, Medicare, Medicaid, and private insurance across three time periods, which reflect the sequential opening of each FED. Insurance types for each facility were compared for individual time periods and across time periods. chi(2) was used to analyze the data. RESULTS: In the three studied time frames (periods B, C, and D), there were less privately insured patients and more self-pay, Medicaid, and Medicare patients at the main than at each FED (p \textless 0.001). Insurance types were significantly different between each of the three FEDs and the main ED (p \textless 0.001) and between each of the three FEDs (p \textless 0.001). CONCLUSIONS: There were less privately insured patients and more self-pay, Medicaid, and Medicare patients at the main ED compared to the FEDs. Privately insured patients decreased at both the FEDs and main ED during the study. Insurance distribution was significantly different between the main ED, and three FEDs, and between individual FEDs.
Identifier
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<a href="http://doi.org/10.1016/j.jemermed.2016.05.058" target="_blank" rel="noreferrer noopener">10.1016/j.jemermed.2016.05.058</a>
Rights
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Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
2016
Department of Emergency Medicine
Emergency Service
Emergency Service – Statistics and Numerical Data
Freestanding emergency department
Griffin Gregory
Hayslip Dave
Health – Statistics and Numerical Data
Health – Trends
Health/*statistics & numerical data/trends
Hospital/*statistics & numerical data
Hospitals
Human
Humans
Insurance
Jia Zhenyu
Jouriles Nicholas
Kobe Daniel
Medicaid – Statistics and Numerical Data
Medicaid/statistics & numerical data
Medically Uninsured – Statistics and Numerical Data
Medically Uninsured/statistics & numerical data
Medicare – Statistics and Numerical Data
Medicare/statistics & numerical data
NEOMED College of Medicine
Orlik Kseniya
Retrospective Design
Retrospective Studies
Simon Erin L
Special – Statistics and Numerical Data
Tertiary Care Centers/statistics & numerical data
The Journal of emergency medicine
United States
Urban – Statistics and Numerical Data
Urban/*statistics & numerical data