Literature DB >> 20961928

Can emergency department nurses performing triage predict the need for admission?

Iain Beardsell1, Sarah Robinson.   

Abstract

OBJECTIVE: To investigate whether nurses performing triage are able to predict the need for admission of patients attending the emergency department (ED) with sufficient accuracy to facilitate hospital bed management.
METHODS: A prospective observational study was performed in which nurses performing triage, in a large urban UK hospital, were asked to predict whether patients would ultimately be admitted or discharged from the ED.
RESULTS: 3144 patients attended the ED during the trial period, of which 296 were excluded from the study. The positive predictive value of the nurse performing triage's prediction for the whole study cohort was 54.23.
CONCLUSION: Predicting admission at triage is not sufficiently accurate to inform hospital in-patient bed management systems. The decision to admit can only be determined after a comprehensive clinical work up and patients cannot be accurately 'signposted' during the triage process.

Entities:  

Mesh:

Year:  2010        PMID: 20961928     DOI: 10.1136/emj.2010.096362

Source DB:  PubMed          Journal:  Emerg Med J        ISSN: 1472-0205            Impact factor:   2.740


  6 in total

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2.  Development of a low-dimensional model to predict admissions from triage at a pediatric emergency department.

Authors:  Fiona Leonard; John Gilligan; Michael J Barrett
Journal:  J Am Coll Emerg Physicians Open       Date:  2022-07-15

3.  Predicting Admissions From a Paediatric Emergency Department - Protocol for Developing and Validating a Low-Dimensional Machine Learning Prediction Model.

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4.  Real-time prediction of patient disposition and the impact of reporter confidence on mid-level triage accuracies: an observational study in Israel.

Authors:  Daniel Trotzky; Noaa Shopen; Jonathan Mosery; Neta Negri Galam; Yizhaq Mimran; Daniel Edward Fordham; Shiran Avisar; Aya Cohen; Malka Katz Shalhav; Gal Pachys
Journal:  BMJ Open       Date:  2021-12-09       Impact factor: 2.692

Review 5.  Machine learning in patient flow: a review.

Authors:  Rasheed El-Bouri; Thomas Taylor; Alexey Youssef; Tingting Zhu; David A Clifton
Journal:  Prog Biomed Eng (Bristol)       Date:  2021-02-22

6.  A simple tool to predict admission at the time of triage.

Authors:  Allan Cameron; Kenneth Rodgers; Alastair Ireland; Ravi Jamdar; Gerard A McKay
Journal:  Emerg Med J       Date:  2014-01-13       Impact factor: 2.740

  6 in total

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