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Observational Study
. 2016 May 12;11(5):e0155363.
doi: 10.1371/journal.pone.0155363. eCollection 2016.

Predictors for Delayed Emergency Department Care in Medical Patients with Acute Infections - An International Prospective Observational Study

Affiliations
Observational Study

Predictors for Delayed Emergency Department Care in Medical Patients with Acute Infections - An International Prospective Observational Study

Alexander Kutz et al. PLoS One. .

Abstract

Introduction: In overcrowded emergency department (ED) care, short time to start effective antibiotic treatment has been evidenced to improve infection-related clinical outcomes. Our objective was to study factors associated with delays in initial ED care within an international prospective medical ED patient population presenting with acute infections.

Methods: We report data from an international prospective observational cohort study including patients with a main diagnosis of infection from three tertiary care hospitals in Switzerland, France and the United States (US). We studied predictors for delays in starting antibiotic treatment by using multivariate regression analyses.

Results: Overall, 544 medical ED patients with a main diagnosis of acute infection and antibiotic treatment were included, mainly pneumonia (n = 218; 40.1%), urinary tract (n = 141; 25.9%), and gastrointestinal infections (n = 58; 10.7%). The overall median time to start antibiotic therapy was 214 minutes (95% CI: 199, 228), with a median length of ED stay (ED LOS) of 322 minutes (95% CI: 308, 335). We found large variations of time to start antibiotic treatment depending on hospital centre and type of infection. The diagnosis of a gastrointestinal infection was the most significant predictor for delay in antibiotic treatment (+119 minutes compared to patients with pneumonia; 95% CI: 58, 181; p<0.001).

Conclusions: We found high variations in hospital ED performance in regard to start antibiotic treatment. The implementation of measures to reduce treatment times has the potential to improve patient care.

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Conflict of interest statement

Competing Interests: AK, BM, and PS received support from B·R·A·H·M·S AG (now Thermo Fisher Scientific Biomarkers) to attend meetings and fulfill speaking engagements. BM and PS received support from bioMérieux to attend meetings and fulfill speaking engagements and received research grants from both firms, and BM has served as a consultant to both companies. PH received research grants and support from ThermoFisher Scientific BRAHMS to attend meetings and fulfill speaking engagements. All other authors have no conflicts of interest relevant to this paper. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Distribution of ED measures of timely care in patients with acute infections across different countries.
The bottom and top of the box represent the 25th and 75th percentiles of the hospital-reported mean times for that measure, with the middle line representing the median. * Time of arrival to time seen by a doctor. ** Time of arrival to time being given medication. *** Time of arrival to time leaving the emergency department for home or for an in-hospital bed.

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