Analysis of racial differences in hospital stays in the presence of geographic confounding. Spat Spatiotemporal Epidemiol 2019 Aug;30:100284
Date
08/20/2019Pubmed ID
31421795Pubmed Central ID
PMC7359673DOI
10.1016/j.sste.2019.100284Scopus ID
2-s2.0-85069635368 (requires institutional sign-in at Scopus site) 2 CitationsAbstract
Using recent methods for spatial propensity score modeling, we examine differences in hospital stays between non-Hispanic black and non-Hispanic white veterans with type 2 diabetes. We augment a traditional patient-level propensity score model with a spatial random effect to create a matched sample based on the estimated propensity score. We then use a spatial negative binomial hurdle model to estimate differences in both hospital admissions and inpatient days. We demonstrate that in the presence of unmeasured geographic confounding, spatial propensity score matching in addition to the spatial negative binomial hurdle outcome model yields improved performance compared to the outcome model alone. In the motivating application, we construct three estimates of racial differences in hospitalizations: the risk difference in admission, the mean difference in number of inpatient days among those hospitalized, and the mean difference in number of inpatient days across all patients (hospitalized and non-hospitalized). Results indicate that non-Hispanic black veterans with type 2 diabetes have a lower risk of hospital admission and a greater number of inpatient days on average. The latter result is especially important considering that we observed much smaller effect sizes in analyses that did not incorporate spatial matching. These results emphasize the need to address geographic confounding in health disparity studies.
Author List
Davis ML, Neelon B, Nietert PJ, Burgette LF, Hunt KJ, Lawson AB, Egede LEAuthor
Leonard E. Egede MD Center Director, Chief, Professor in the Medicine department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
Diabetes Mellitus, Type 2Female
Healthcare Disparities
Humans
Length of Stay
Male
Middle Aged
Propensity Score
Spatial Analysis
United States
Veterans
