Pediatric triage variations among nurses, pediatric and emergency residents using the Canadian triage and acuity scale
Notice bibliographique
Résumé
BACKGROUND: Emergency care continues to be a challenge, since patients' arrival is unscheduled and could occur at the same time which may fill the Emergency Department with non-urgent patients. Triaging is an integral part of every busy ED. The Canadian Triage and Acuity Scale (CTAS) is considered an accurate tool to be used outside Canada. This study aims to identify the chosen triage level and compare the variation between registered nurses, pediatric and adult emergency residents by using CTAS cases. METHOD: This study was conducted at King Abdulaziz Medical City,Saudi Arabia. A cross-sectional self-administered questionnaire was used, and which contains 15 case scenarios with different triage levels. All cases were adopted from a Canadian triage course after receiving permission. Each case provides the patient's symptoms, clinical signs and mode of arrival to the ED. The participants were instructed to assign a triage level using the following scale. A non-random sampling technique was used for this study. The rates of agreement between residents were calculated using kappa statistics (weighted-kappa) (95%CI). RESULT: A total of 151 participants completed the study questionnaire which include 15 case scenarios. 73 were nurses and 78 were residents. The results showed 51.3, 56.6, and 59.9% mis-triaged the cases among the nurses, emergency residents, and pediatric residents respectively. Triage scores were compared using the Kruskal Wallis test and were statistically significant with a p value of 0.006. The mean ranks for nurses, emergency residents and pediatric residents were 86.41, 73.6 and 59.96, respectively. The Kruskal Wallis Post-Hoc test was performed to see which groups were statistically significant, and it was found that there was a significant difference between nurses and pediatrics residents (P value = 0.005). Moreover, there were no significant differences found between nurses and ER residents (P value> 0.05). CONCLUSION: The triaging system was found to be a very important tool to prioritize patients based on their complaints. The results showed that nurses had the greatest experience in implementing patients on the right triage level. On the other hand, ER and pediatric residents need to develop more knowledge about CTAS and become exposed more to the triaging system during their training.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».