Lauren E Elson1, Alina A Luke1, Abigail R Barker1,2, Timothy D McBride1,2, Karen E Joynt Maddox1,3. 1. Cardiovascular Division, Department of Medicine, School of Medicine, Washington University, St. Louis, Missouri. 2. Brown School, Washington University, St. Louis, Missouri. 3. Center for Health Economics and Policy, Institute for Public Health, Washington University, St. Louis, Missouri.
Abstract
PURPOSE: Rural-urban health disparities have received increasing scrutiny as rural individuals continue to have worse health outcomes. However, little is known about how insurance status contributes to urban-rural disparities. This study characterizes how rural uninsured patients compare to the urban uninsured, determines whether rurality among the uninsured is associated with worse clinical outcomes, and examines how clinical outcomes based on rurality have changed over time. METHODS: We conducted a retrospective cohort study of the 2012-2016 National Inpatient Sample hospital discharge data including 1,478,613 uninsured patients, of which 233,816 were rural. Admissions were broken into 6 rurality categories. Logistic regression models were used to determine the independent association between rurality and hospital mortality. FINDINGS: Demographic and clinical characteristics differed significantly between rural and urban uninsured patients: rural patients were more often white, lived in places with lower median household income, and were more often admitted electively and transferred. Rurality was associated with significantly higher in-hospital mortality rates (1.44% vs 1.89%, OR 1.32, P < .001). This association strengthened after adjusting for medical comorbidities and hospital characteristics. Further, disparities between urban and rural mortality were found to be growing, with the gap almost doubling between 2012 and 2016. CONCLUSIONS: Rural and urban uninsured patients differed significantly, specifically in terms of race and median income. Among the uninsured, rurality was associated with higher in-hospital mortality, and the gap between urban and rural in-hospital mortality was widening. Our findings suggest the rural uninsured are a vulnerable population in need of informed, tailored policies to reduce these disparities.
PURPOSE: Rural-urban health disparities have received increasing scrutiny as rural individuals continue to have worse health outcomes. However, little is known about how insurance status contributes to urban-rural disparities. This study characterizes how rural uninsured patients compare to the urban uninsured, determines whether rurality among the uninsured is associated with worse clinical outcomes, and examines how clinical outcomes based on rurality have changed over time. METHODS: We conducted a retrospective cohort study of the 2012-2016 National Inpatient Sample hospital discharge data including 1,478,613 uninsured patients, of which 233,816 were rural. Admissions were broken into 6 rurality categories. Logistic regression models were used to determine the independent association between rurality and hospital mortality. FINDINGS: Demographic and clinical characteristics differed significantly between rural and urban uninsured patients: rural patients were more often white, lived in places with lower median household income, and were more often admitted electively and transferred. Rurality was associated with significantly higher in-hospital mortality rates (1.44% vs 1.89%, OR 1.32, P < .001). This association strengthened after adjusting for medical comorbidities and hospital characteristics. Further, disparities between urban and rural mortality were found to be growing, with the gap almost doubling between 2012 and 2016. CONCLUSIONS: Rural and urban uninsured patients differed significantly, specifically in terms of race and median income. Among the uninsured, rurality was associated with higher in-hospital mortality, and the gap between urban and rural in-hospital mortality was widening. Our findings suggest the rural uninsured are a vulnerable population in need of informed, tailored policies to reduce these disparities.
Authors: Rasmus Gregersen; Cathrine Fox Maule; Henriette Husum Bak-Jensen; Allan Linneberg; Olav Wendelboe Nielsen; Simon Francis Thomsen; Christian S Meyhoff; Kim Dalhoff; Michael Krogsgaard; Henrik Palm; Hanne Christensen; Celeste Porsbjerg; Kristian Antonsen; Jørgen Rungby; Steen B Haugaard; Janne Petersen; Finn E Nielsen Journal: Clin Epidemiol Date: 2022-03-31 Impact factor: 4.790
Authors: Ene M Enogela; Taylor Buchanan; Christy S Carter; Ronit Elk; Shena B Gazaway; Burel R Goodin; Elizabeth A Jackson; Raymond Jones; Richard E Kennedy; Emma Perez-Costas; Lisa Zubkoff; Emily L Zumbro; Alayne D Markland; Thomas W Buford Journal: Int J Equity Health Date: 2022-08-27