Decreasing Hospital Admissions From the Emergency Department for Acute Atrial Fibrillation
Abstract
Acute atrial fibrillation and flutter (AAFF) is characterized by rapid heart rates with onset less than seven days. It's the most common type of palpitation treated in the Emergency Department (ED). Some Canadian ED's will discharge 95% of AAFF patients whereas others admit up to 40%. With hospital and ED crowding, discharge is the most optimal, effective and safe strategy. Our aim is to improve the care and reduce the length of stay (LOS) of ED AAFF patients, while decreasing unnecessary hospitalizations. First, the investigators must understand the local barriers. In the previous study, the investigators conducted interviews of emergency physicians, cardiologists and AAFF patients. In Project 1b, the investigators created the CAEP ED AAFF Guidelines Checklist to assist physicians to manage AAFF more efficiently and safely. The Guidelines are comprised of two algorithms and four sets of checklists for ED assessment and management. They have been endorsed by CAEP and are published in CJEM.
The investigators are now planning Project 2 in which the investigators will conduct a cluster \[group\] randomized trial at 11 Canadian EDs and enroll 1,300 patients over thirteen months. The investigators are not randomizing individual patients or doctors; instead the investigators are randomizing the start date of individual hospitals. Our goal is to introduce the new Guidelines into these hospitals to improve the care of AAFF patients. The investigators hope to improve AAFF management,…
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design. Reported size: 846 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.