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Activity Number: 198 - SPEED: Nonparametric Statistics: Estimation, Testing, and Modeling
Type: Contributed
Date/Time: Monday, July 30, 2018 : 11:35 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract #332825
Title: Quantile Function Modeling Applied to Time Between Healthcare-Associated Infection Events
Author(s): Jonathan R Edwards*
Companies: Center for Disease Control & Prevention
Keywords: Quantile Function; Healthcare; infection
Abstract:

Central line-associated bloodstream infection (CLABSI) event data are reported, pursuant to federal requirements, by acute care hospitals (ICUs and select ward locations) to CDC's National Healthcare Safety Network (NHSN) since 2015 to measure hospital performance and among a set of healthcare-associated infections (HAIs). Time Between Event (TBE) monitoring among HAIs such as CLABSI can add demonstrable value to measuring and improving healthcare quality. To better understand and account for factors that explain differences in TBE, quantile functions based on hospital, unit/location and patient-level factors were estimated.

In 2016, TBE data for 27,428 CLABSIs were reported to NHSN. Patient care location types reporting ?50 CLABSIs were included. Estimation of CLABSI probability occurring on any given day was obtained from TBE data and helped to demarcate differences in CLABSI risk. Quantile regression was used to estimate conditional quantiles of TBE given eligible covariates. Hospital and location-level factors can be used to augment existing measures and help to distinguish CLABSI TBE among hospital ICUs and select wards that will help improve performance measurement.


Authors who are presenting talks have a * after their name.

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