A2069
Title: Statistical modeling challenges in large-scale population database: United States renal data system modeling
Authors: Danh Nguyen - University of California, Irvine (United States) [presenting]
Abstract: The United States Renal Data System (USRDS), funded by the National Institute of Diabetes and Digestive and Kidney Diseases, is a National Data System that collects, analyzes, and disseminates information on chronic Kidney disease (CKD) and end-stage Kidney disease (ESKD) in the US (USRDS.org). It includes Data on nearly all patients on dialysis in the US. Several challenges in modeling CKD and ESKD patient outcomes are addressed: (1) profiling healthcare providers; (2) joint modeling including multivariate joint modeling of longitudinal, recurrent, and terminal outcomes and spatiotemporal modeling of patient outcomes, including longitudinal hospitalization and mortality. Several frequentist and Bayesian approaches to addressing large Data size and high-dimensional parameters associated with modeling spatial effects and parametrization of time-varying dynamic effects of risk factors on patient outcomes are presented. The discussion highlights opportunities and open challenges in modeling patient outcomes using the USRDS database.
