title: A spatiotemporal quantile regression model for emergency department expenditures.
abstract: Motivated by a recent study of geographic and temporal trends in emergency department care, we develop a spatiotemporal quantile regression model for the analysis of emergency department-related medical expenditures. The model yields distinct spatial patterns across time for each quantile of the response distribution, which is important in the spatial analysis of expenditures, as there is often little spatiotemporal variation in mean expenditures but more pronounced variation in the extremes. The model has a hierarchical structure incorporating patient-level and region-level predictors as well as spatiotemporal random effects. We model the random effects via intrinsic conditionally autoregressive priors, improving small-area estimation through maximum spatiotemporal smoothing. We adopt a Bayesian modeling approach based on an asymmetric Laplace distribution and develop an efficient posterior sampling scheme that relies solely on conjugate full conditionals. We apply our model to data from the Duke support repository, a large georeferenced database containing health and financial data for Duke Health System patients residing in Durham County, North Carolina.
authors.affiliation: Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, 29425, U.S.A.
authors.forename: Brian
authors.initials: B
authors.lastname: Neelon
authors.affiliation: Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, SC, 27710, U.S.A.
authors.forename: Fan
authors.initials: F
authors.lastname: Li
authors.affiliation: RAND Corporation, Arlington, VA, 22202, U.S.A.
authors.forename: Lane F
authors.initials: LF
authors.lastname: Burgette
authors.affiliation: Department of Community and Family Medicine, Duke University School of Medicine, Durham, NC, 27705, U.S.A.
authors.forename: Sara E Benjamin
authors.initials: SE
authors.lastname: Neelon
mesh_terms: D001499:Bayes Theorem; D056808:Biostatistics / Q000379:methods; D003198:Computer Simulation; D004636:Emergency Service, Hospital / Q000191:economics*; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D015233:Models, Statistical; D009657:North Carolina; D012044:Regression Analysis
keywords: Bayesian inference; asymmetric Laplace distribution; conditionally autoregressive prior; medical expenditures; quantile regression; spatiotemporal model