• Kate Bradman, Meredith Borland, and Elaine Pascoe.
• Emergency Department, Princess Margaret Hospital, Perth, Western Australia, Australia.
• J Paediatr Child Health. 2014 Oct 1;50(10):E39-44.

AimThe aim of this study is to directly compare published prediction tools with triage nurse (TN) predictions within a defined paediatric population.MethodA prospective observational study carried out over a week in May 2010 in the Emergency Department (ED) at Princess Margaret Hospital for Children in Perth, Western Australia. TN predicted which patients would be admitted to hospital at the time of ED presentation. Data required for the other prediction tools (paediatric early warning score (PEWS); triage category and the Pediatric Risk of Admission Score (PRISA) and PRISA II were obtained from the notes following the patient's ED attendance.ResultsA total of 1223 patients presented during the study week, 91 patients were excluded and a total of 946 patients (83.6%) had TN predictions and were included in the analysis. TN predictions were compared against a PEWS ≥ 4, triage category 1, 2 and 3, PRISA ≥ 9 and PRISA II ≥ 2. TNs had the highest prediction accuracy (87.7%), followed by an elevated PEWS (82.9%), triage category of 1, 2, or 3 (82.9%). The PRISA and PRISA II score had an accuracy of 80.1% and 79.7%, respectively.ConclusionWhen compared with validated prediction tools, the TN is the most accurate predictor of need to admit. This study provides valuable information in planning efficient flow of patients through the ED.© 2012 The Authors. Journal of Paediatrics and Child Health © 2012 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

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