CJEM
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To characterize patients who left without being seen (LWBS) from a Canadian pediatric Emergency Department (ED) and create predictive models using machine learning to identify key attributes associated with LWBS. ⋯ Our analysis showed that machine learning models can be used on administrative data to predict patients who LWBS in a Canadian pediatric ED. From 16 variables, we identified the five most influential model attributes. System-level interventions to improve patient flow have shown promise for reducing LWBS in some centres. Predicting patients likely to LWBS raises the possibility of individual patient-level interventions to mitigate LWBS.
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Randomized Controlled Trial Multicenter Study
Are we talking about practice? A randomized study comparing simulation-based deliberate practice and mastery learning to self-guided practice.
Simulation-based technical skills training is now ubiquitous in medicine, particularly for high acuity, low occurrence (HALO) procedures. Mastery learning and deliberate practice (ML + DP) are potentially valuable educational methods, however, they are resource intensive. We sought to compare the effect of deliberate practice and mastery learning versus self-guided practice on skill performance of the rare, life-saving procedure, a bougie-assisted cricothyroidotomy (BAC). ⋯ There was no significant difference in skill performance between groups. Residents who received deliberate practice and mastery learning demonstrated an improvement in skill performance time.
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Homelessness increases the risk of cold-related injuries. We examined emergency department visits for cold-related injuries in Toronto over a 4-year period, comparing visits for patients identified as homeless to visits for patients not identified as homeless. ⋯ Patients experiencing homelessness visiting the emergency department are much more likely to be seen for cold-related injuries than non-homeless patients. Additional efforts are needed to prevent cold-related exposure and consequent injury among people experiencing homelessness.