Abstract

BackgroundHospital-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.MethodsA 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.ResultsThe 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.ConclusionThis 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.

Highlights

  • Hospital-acquired bloodstream infection (BSI) is associated with high morbidity and mortality and increases patients’ length of stay (LOS) and hospital charges

  • Bloodstream infection (BSI) is a serious adverse event associated with high morbidity and mortality

  • The hospital conducted hospital-wide healthcare associated infections (HAI) surveillance with a real-time nosocomial infection surveillance system (RT-NISS)

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Summary

Introduction

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. Bloodstream infection (BSI) is a serious adverse event associated with high morbidity and mortality. Studies in Canada demonstrated that 28% of BSIs are nosocomial [1], and data from North America and Europe showed. Our previous study in a Chinese tertiary hospital indicated an increasing incidence of BSI from 0.53 to 0.65 per 1000 patient-days over 5 years (2013–2017) [3]. BSIs are associated with increased length of stay (LOS) and medical costs [4,5,6]. Reduced healthcare associated infections (HAI) and LOS could increase the bed turnover rate and hospital

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