Introduction Exit block is the most significant cause of poor patient flow and crowding in the emergency department (ED). One proposed strategy to reduce exit block is early admission predictions by triage nurses to allow proactive bed management. We report a systematic review and meta-analysis of the accuracy of nurse prediction of admission at triage.
Methodology We searched MEDLINE, Cochrane, Embase, CINAHL and grey literature, up to and including February 2019. Our criteria were as follows: prospective studies analysing the accuracy of triage nurse intuition—after gathering standard triage information—for predicting disposition for adult ED patients. We analysed the results of this test—nurse prediction of disposition—in a diagnostic test analysis review style, assessing methodology with the Quality Assessment of Diagnostic Accuracy Studies 2 checklist. We generated sensitivity, specificity and likelihood ratios (LRs). We used LRs and pretest probability of admission (baseline admission rate) to find positive and negative post-test probabilities.
Results We reviewed 10 articles. Of these, seven had meta-analysable data (12 282 participants). The studies varied in participant selection and admission rate, but the majority were of moderate quality and exclusion of each in sensitivity analyses made little difference. Sensitivity was 72% and specificity was 83%. Pretest probability of admission was 29%. Positive and negative post-test probabilities of admission were 63% and 12%, respectively.
Conclusion Triage nurse prediction of disposition is not accurate enough to expedite admission for ED patients on a one-to-one basis. Future research should explore the benefit, and best method, of predicting total demand.
- emergency department
- emergency departments
Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.