Objective: In this study, the authors have compared data concerning the pediatric triage that is carried out in 2 large emergency departments (EDs) in Rome, one located in a university pediatric clinic with qualified staff and the other one in a general hospital with a high flow of users and pediatric admissions.
Methods: A total of 324 children were selected (162 per hospital) with ages between 0 and 3 years who went to the ED in the period from October to December 2009 for respiratory pathologic findings at the lower respiratory tracts' expense. We took and compared the following data: assignation of the color code, congruity of the color code, and realization of the reevaluation.
Discussion: This study reveals several differences between the 2 structures considered with a clear tendency of nurses of the general ED to underestimate color codes, giving undertriage rates in a significant number of cases. Another significantly important difference was found on the detection of children's vital parameters. One last important parameter that emerged from this study was the lack of attention to the reevaluation of the patient after admission in ED.
Results: In the light of what we pointed out, it is necessary to implement the educational and informative quality of the triage operators and educators, planning periodical triage training courses to reduce errors. Particular emphasis must be placed on providing pediatric continuing education for nurses practicing in general ED.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/PEC.0000000000000075 | DOI Listing |
Cureus
December 2024
Department of Pediatric Emergency Care and Intensive Care Medicine, Tokyo Metropolitan Children's Medical Center, Tokyo, JPN.
Aim Preventing leaving-without-being-seen (LWBS) in children is crucial due to their inability to seek medical care independently. Because there are no studies of LWBS in Japan, the extent of this problem in Japan and its impacts on healthcare are uncertain. The present study seeks to fill this gap by investigating LWBS after triage and identifying the associated factors.
View Article and Find Full Text PDFIntroduction The pediatric intensive care unit (PICU) is a specialized area for treating critically ill infants and children. However, some of these children may experience poor outcomes, including death. However, it is necessary to predict the prognosis for critically ill patients as early as possible to commence triage as well as an early and effective intervention to prevent mortality.
View Article and Find Full Text PDFJAMIA Open
February 2025
Artificial Intelligence (AI) for Health Institute (AIHealth), Washington University in St Louis, St Louis, MO 63130, United States.
Objective: Extracorporeal membrane oxygenation (ECMO) is among the most resource-intensive therapies in critical care. The COVID-19 pandemic highlighted the lack of ECMO resource allocation tools. We aimed to develop a continuous ECMO risk prediction model to enhance patient triage and resource allocation.
View Article and Find Full Text PDFPediatr Emerg Care
January 2025
University of California Davis School of Medicine, Sacramento, CA.
Objective: Evaluate the accuracy and reliability of various generative artificial intelligence (AI) models (ChatGPT-3.5, ChatGPT-4.0, T5, Llama-2, Mistral-Large, and Claude-3 Opus) in predicting Emergency Severity Index (ESI) levels for pediatric emergency department patients and assess the impact of medically oriented fine-tuning.
View Article and Find Full Text PDFJ Surg Res
January 2025
Division of Emergency Medicine, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Introduction: Undertriage of children contributes to poorer clinical outcomes. The objective of this study was to determine factors associated with undertriage of pediatric major trauma victims.
Methods: We performed a retrospective cross-sectional study of children (aged < 16 ys) using the 2021 American College of Surgeons National Trauma Data Bank.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!