ArticleEinstein (Sao Paulo, Brazil)
Emergency Severity Index: accuracy in risk classification.
Article in Einstein (Sao Paulo, Brazil). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The effects of applying artificial intelligence to triage in the emergency department: A systematic review of prospective studies.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025Pooled it
- The role of perfusion index in the evaluation of patients with cancer.BMC emergency medicine · 2025Article
- Machine Learning-Based Model to Classify Emergency Severity Index Levels 1-3 in Febrile Patients With Tachycardia: Thailand Triage Prediction System.Journal of clinical medicine research · 2025Article
- Stranded in the emergency department: an analysis of boarding trends in older adults in the United States.Health affairs scholar · 2025Article
- A new Bayesian method for the estimation of emergency nurses' thresholds and agreement in the context of telephone triage.Frontiers in psychology · 2025Article
- Factors influencing the classification accuracy of triage nurses in emergency department: analysis of triage nurses' characteristics.BMC nursing · 2024Article
- Clinical characteristics and prognostic marker for hospitalization in children with influenza infection in an emergency setting.BMC pediatrics · 2024Article
- Implementation of advanced triage in the Emergency Department of high complexity public hospital: Research protocol.Nursing open · 2023Article
- Medical Admission Prediction Score (MAPS); a simple tool to predict medical admissions in the emergency department.PloS one · 2023Article
- Article
- A Scoping Review of Emergency Department Discharge Risk Stratification.The western journal of emergency medicine · 2021Article
- Machine Learning and Initial Nursing Assessment-Based Triage System for Emergency Department.Healthcare informatics research · 2020Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo verify agreement between estimative of predicted resources using the adapted Emergency Severity Index and the real amount of resources used by patients. To analyze the variables number of years since graduation, years of work experience and years of experience in emergency services especially with accurate anticipation of resources need.
methodsThis retrospective analytical study with a quantitative approach included 538 medical records of patients assisted by 11 triage nurses. Data collected were related to assistances carried out from December 2012 to February 2013.
resultsThere was no significant association between the adequacy of the number of resources used, based on Emergency Severity Index score, number of years since graduation, year of work experience or years of experience in emergency services. Kappa agreement coefficient (0.34) showed that agreement was low between predicted and real used number of resources.
conclusionNurses' accuracy index to predict resources for patients care from emergency room using the adapted Emergency Severity Index was lower than results reported in the studies in the literature that used the original scale. There was low agreement of diagnostic exams predicted by nurses and those really performed. There was no association among correct prediction of resources needed, number of years since graduation, years of experience in emergency services and years of work experience in the unit where the study was done.
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