The epidemiology of emergency department crowding and boarding in Brazil: a nationwide multicenter study
Abstract
Abstract Background Emergency department (ED) crowding is associated with adverse patient outcomes, yet its epidemiology remains poorly characterized in low- and middle-income countries. We aimed to characterize ED crowding and boarding across Brazil, including their geographic distribution, temporal trends, hospital characteristics, and association with municipal socioeconomic indicators. Methods We conducted a multicenter observational study using operational data from 160 Brazilian EDs participating in a national quality improvement program between 2019 and 2025. Two ED strain indicators were evaluated: occupancy ratio (ED census divided by designated ED beds) and boarding proportion (admitted patients remaining in the ED divided by total ED census). Descriptive analyses examined temporal trends and geographic variation. Multivariable linear regression assessed associations between municipal Human Development Index (MHDI) and ED strain, with prespecified sensitivity analyses. Results The final cohort comprised 160 hospitals contributing 351 hospital-years and 2,443 hospital-month observations. Median occupancy ratio was 1.03 (IQR, 0.74–1.39), indicating that EDs routinely operated beyond formal capacity. Median boarding proportion was 0.45 (IQR, 0.29–0.63), meaning that nearly half of ED patients were awaiting inpatient beds. Occupancy declined transiently during the COVID-19 pandemic but subsequently returned to pre-pandemic levels, whereas boarding remained consistently…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.
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.