Outcomes of boarding critically ill patients in U.S. EDs: A systematic review and meta-analysis
Abstract
INTRODUCTION
Boarding is the practice of holding patients in the emergency department (ED) or a temporary location after the decision to admit or transfer has been made. Previous literature suggests that ED Length of Stay (LOS), prolonged in boarded patients, is linked to worse outcomes. We conducted a systematic review and meta-analysis (SR/MA) to evaluate the differences in mortality and hospital LOS in ED-boarding (EDB) and non-ED boarding (non-EDB) critically ill patients in U.S. EDs.
METHODS
A systematic search was performed with medical librarians using major health science databases from 2012 through December 2024. Eligible studies included observational or randomized trials involving adults comparing EDB and non-EDB groups in U.S. EDs. Only full-text English-language articles were included. Outcomes were mortality and hospital LOS. We used random-effects meta-analysis to compare the outcomes. Heterogeneity was assessed with the I2 value while publication bias was assessed via the funnel plot.
RESULTS
We identified 3139 studies and included 17, comprising 407,178 ED patients: 194,814 (48 %) EDB and 212,364 (52 %) non-EDB. 87.4 % of patients came from urban academic Emergency Departments with a resuscitation unit or team. Median ED LOS was 6.5 h (IQR 5.18-8.1) for EDB and 4.2 h (IQR 2.38-5.75) for non-EDB (p < 0.01). EDB patients had similar all-cause mortality (OR 1.06, 95 % CI 0.94-1.19, I2 = 69 %, p = 0.38) and hospital LOS (mean difference 0.38 days, 95 % CI…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 407,178 participants or records.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.