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Time‐dynamic profiling with application to hospital readmission among patients on dialysis
Author(s) -
Estes Jason P.,
Nguyen Danh V.,
Chen Yanjun,
Dalrymple Lorien S.,
Rhee Connie M.,
KalantarZadeh Kamyar,
Şentürk Damla
Publication year - 2018
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12908
Subject(s) - medicine , profiling (computer programming) , inference , dialysis , health care , emergency medicine , intensive care medicine , medical emergency , computer science , artificial intelligence , economics , economic growth , operating system
Summary 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.