Predicting admission at triage: are nurses better than a simple objective score?
- PMID: 26864326
- DOI: 10.1136/emermed-2014-204455
Predicting admission at triage: are nurses better than a simple objective score?
Abstract
Aim: We compared two methods of predicting hospital admission from ED triage: probabilities estimated by triage nurses and probabilities calculated by the Glasgow Admission Prediction Score (GAPS).
Methods: In this single-centre prospective study, triage nurses estimated the probability of admission using a 100 mm visual analogue scale (VAS), and GAPS was generated automatically from triage data. We compared calibration using rank sum tests, discrimination using area under receiver operating characteristic curves (AUC) and accuracy with McNemar's test.
Results: Of 1829 attendances, 745 (40.7%) were admitted, not significantly different from GAPS' prediction of 750 (41.0%, p=0.678). In contrast, the nurses' mean VAS predicted 865 admissions (47.3%), overestimating by 6.6% (p<0.0001). GAPS discriminated between admission and discharge as well as nurses, its AUC 0.876 compared with 0.875 for VAS (p=0.93). As a binary predictor, its accuracy was 80.6%, again comparable with VAS (79.0%), p=0.18. In the minority of attendances, when nurses felt at least 95% certain of the outcome, VAS' accuracy was excellent, at 92.4%. However, in the remaining majority, GAPS significantly outperformed VAS on calibration (+1.2% vs +9.2%, p<0.0001), discrimination (AUC 0.810 vs 0.759, p=0.001) and accuracy (75.1% vs 68.9%, p=0.0009). When we used GAPS, but 'over-ruled' it when clinical certainty was ≥95%, this significantly outperformed either method, with AUC 0.891 (0.877-0.907) and accuracy 82.5% (80.7%-84.2%).
Conclusions: GAPS, a simple clinical score, is a better predictor of admission than triage nurses, unless the nurse is sure about the outcome, in which case their clinical judgement should be respected.
Keywords: clinical assessment; efficiency; management, emergency department management; nursing, emergency departments; triage.
Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Similar articles
-
Comparison of Glasgow Admission Prediction Score and Amb Score in predicting need for inpatient care.Emerg Med J. 2018 Apr;35(4):247-251. doi: 10.1136/emermed-2017-207246. Epub 2018 Feb 14. Emerg Med J. 2018. PMID: 29444899
-
Prospective comparison of AMB, GAP AND START scores and triage nurse clinical judgement for predicting admission from an ED: a single-centre prospective study.Emerg Med J. 2022 Dec;39(12):897-902. doi: 10.1136/emermed-2020-210814. Epub 2021 Dec 30. Emerg Med J. 2022. PMID: 34969662
-
Predicting emergency department inpatient admissions to improve same-day patient flow.Acad Emerg Med. 2012 Sep;19(9):E1045-54. doi: 10.1111/j.1553-2712.2012.01435.x. Acad Emerg Med. 2012. PMID: 22978731
-
Emergency Severity Index version 4: a valid and reliable tool in pediatric emergency department triage.Pediatr Emerg Care. 2012 Aug;28(8):753-7. doi: 10.1097/PEC.0b013e3182621813. Pediatr Emerg Care. 2012. PMID: 22858740
-
Ability of triage nurses to predict, at the time of triage, the eventual disposition of patients attending the emergency department (ED): a systematic literature review and meta-analysis.Emerg Med J. 2021 Sep;38(9):694-700. doi: 10.1136/emermed-2019-208910. Epub 2020 Jun 19. Emerg Med J. 2021. PMID: 32561525
Cited by
-
Applications of Machine Learning Approaches in Emergency Medicine; a Review Article.Arch Acad Emerg Med. 2019 Jun 3;7(1):34. eCollection 2019. Arch Acad Emerg Med. 2019. PMID: 31555764 Free PMC article. Review.
-
Predicting Inpatient Admissions From Emergency Department Triage Using Machine Learning: A Systematic Review.Mayo Clin Proc Digit Health. 2025 Jan 30;3(1):100197. doi: 10.1016/j.mcpdig.2025.100197. eCollection 2025 Mar. Mayo Clin Proc Digit Health. 2025. PMID: 40206990 Free PMC article. Review.
-
Comparing Machine Learning and Nurse Predictions for Hospital Admissions in a Multisite Emergency Care System.Mayo Clin Proc Digit Health. 2025 Jul 9;3(3):100249. doi: 10.1016/j.mcpdig.2025.100249. eCollection 2025 Sep. Mayo Clin Proc Digit Health. 2025. PMID: 40791833 Free PMC article.
-
Multicentre, prospective observational study of the correlation between the Glasgow Admission Prediction Score and adverse outcomes.BMJ Open. 2019 Aug 10;9(8):e026599. doi: 10.1136/bmjopen-2018-026599. BMJ Open. 2019. PMID: 31401591 Free PMC article.
-
Predicting hospital admission at emergency department triage using machine learning.PLoS One. 2018 Jul 20;13(7):e0201016. doi: 10.1371/journal.pone.0201016. eCollection 2018. PLoS One. 2018. PMID: 30028888 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Research Materials