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Published in: Antimicrobial Resistance & Infection Control 1/2020

01-12-2020 | Nosocomial Infection | Research

Estimating length of stay and inpatient charges attributable to hospital-acquired bloodstream infections

Authors: Yuzheng Zhang, Mingmei Du, Janice Mary Johnston, Ellie Bostwick Andres, Jijiang Suo, Hongwu Yao, Rui Huo, Yunxi Liu, Qiang Fu

Published in: Antimicrobial Resistance & Infection Control | Issue 1/2020

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Abstract

Background

Hospital-acquired bloodstream infection (BSI) is associated with high morbidity and mortality and increases patients’ length of stay (LOS) and hospital charges. Our goals were to calculate LOS and charges attributable to BSI and compare results among different models.

Methods

A retrospective observational cohort study was conducted in 2017 in a large general hospital, in Beijing. Using patient-level data, we compared the attributable LOS and charges of BSI with three models: 1) conventional non-matching, 2) propensity score matching controlling for the impact of potential confounding variables, and 3) risk set matching controlling for time-varying covariates and matching based on propensity score and infection time.

Results

The study included 118,600 patient admissions, 557 (0.47%) with BSI. Six hundred fourteen microorganisms were cultured from patients with BSI. Escherichia coli was the most common bacteria (106, 17.26%). Among multi-drug resistant bacteria, carbapenem-resistant Acinetobacter baumannii (CRAB) was the most common (42, 38.53%). In the conventional non-matching model, the excess LOS and charges associated with BSI were 25.06 days (P < 0.05) and US$22041.73 (P < 0.05), respectively. After matching, the mean LOS and charges attributable to BSI both decreased. When infection time was incorporated into the risk set matching model, the excess LOS and charges were 16.86 days (P < 0.05) and US$15909.21 (P < 0.05), respectively.

Conclusion

This is the first study to consider time-dependent bias in estimating excess LOS and charges attributable to BSI in a Chinese hospital setting. We found matching on infection time can reduce bias.
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Metadata
Title
Estimating length of stay and inpatient charges attributable to hospital-acquired bloodstream infections
Authors
Yuzheng Zhang
Mingmei Du
Janice Mary Johnston
Ellie Bostwick Andres
Jijiang Suo
Hongwu Yao
Rui Huo
Yunxi Liu
Qiang Fu
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Antimicrobial Resistance & Infection Control / Issue 1/2020
Electronic ISSN: 2047-2994
DOI
https://doi.org/10.1186/s13756-020-00796-5

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