| Literature DB >> 29870064 |
Jason P Estes1, Danh V Nguyen2, Yanjun Chen3, Lorien S Dalrymple4, Connie M Rhee2, Kamyar Kalantar-Zadeh2, Damla Şentürk5.
Abstract
Standard profiling analysis aims to evaluate medical providers, such as hospitals, nursing homes, or dialysis facilities, with respect to a patient outcome. The outcome, for instance, may be mortality, medical complications, or 30-day (unplanned) hospital readmission. Profiling analysis involves regression modeling of a patient outcome, adjusting for patient health status at baseline, and comparing each provider's outcome rate (e.g., 30-day readmission rate) to a normative standard (e.g., national "average"). Profiling methods exist mostly for non time-varying patient outcomes. However, for patients on dialysis, a unique population which requires continuous medical care, methodologies to monitor patient outcomes continuously over time are particularly relevant. Thus, we introduce a novel time-dynamic profiling (TDP) approach to assess the time-varying 30-day readmission rate. TDP is used to estimate, for the first time, the risk-standardized time-dynamic 30-day hospital readmission rate, throughout the time period that patients are on dialysis. We develop the framework for TDP by introducing the standardized dynamic readmission ratio as a function of time and a multilevel varying coefficient model with facility-specific time-varying effects. We propose estimation and inference procedures tailored to the problem of TDP and to overcome the challenge of high-dimensional parameters when examining thousands of dialysis facilities.Entities:
Keywords: End-stage renal disease; Hospital readmission; Multilevel varying coefficient models; Profiling of medical care providers; United States Renal Data System
Mesh:
Year: 2018 PMID: 29870064 PMCID: PMC6296887 DOI: 10.1111/biom.12908
Source DB: PubMed Journal: Biometrics ISSN: 0006-341X Impact factor: 2.571