Who Are the Children Leaving the Emergency Department Without Being Seen by a Physician?
Notice bibliographique
Résumé
BACKGROUND: Waiting times to see a physician in emergency departments (EDs) are growing, and a greater number of patients are leaving the ED without being seen by a physician (LWBS). OBJECTIVES: The objective was to assess the characteristics of the children who left a pediatric ED without being seen by a physician. METHODS: This retrospective case-control study was performed using the computerized database of a tertiary care pediatric ED. All children aged less than 19 years old presenting to the ED between April 1, 2008, and March 31, 2009, were included. Cases were all triaged children who LWBS. Controls were all triaged children seen by a physician. Independent variables concerning the patient, the illness, and the period of consultation were assessed. A stepwise logistic regression model was constructed using significant variables identified through univariate analysis to select characteristics most predictive of patients who LWBS. The minimum sample size needed to evaluate 10 risk factors is 100 patients who LWBS. We estimated that evaluating all patients visiting the ED for 1 year would minimize seasonal variation and generate more than 10,000 patients who LWBS. RESULTS: During the study period, 60,525 patients presented to the ED. A total of 10,037 (16.6%) patients were triaged, but LWBS. On multiple logistic regression, referral by a physician (odds ratio [OR] = 0.1, 95% confidence interval [CI] = 0.08 to 0.12); summer or fall consultation (OR = 0.46, 95% CI = 0.43 to 0.45; and OR 0.42, 95% CI = 0.39 to 0.45, respectively, compared to winter); and higher acuity triage level were associated with a lower risk of patients who LWBS. Evening arrivals (OR = 2.1, 95% CI = 1.9 to 2.2, compared to night), ages between 3 months and 11 years (OR varying from 1.3 to 1.8 compared to more than 11 years of age), and living close to the hospital (OR = 1.2, 95% CI = 1.1 to 1.3) were risk factors for LWBS. The most important predictor of LWBS was triage level with rates of 0, 0, 1.5, 23, and 49% for Levels 1 to 5 according to the Canadian Triage and Acuity Scale (CTAS). CONCLUSIONS: This study shows that children who LWBS have a lower triage acuity, are less often referred by a physician, and are largely in the 3-month to 11-year-old age range. Environmental factors, such as the timing of the consultation and the proximity of patients' homes, are also associated with LWBS.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».