Triage effectiveness : a framework for quantifying the effect of emergency triage prioritization
Johansson, André LU
; Fodor, Viktoria
; Forberg, Jakob Lundager
LU
; Ekwall, Anna
LU
and Ekelund, Ulf
LU
(2026)
In BMC Medical Research Methodology
26(1).
- Abstract
Background: Emergency departments use triage to identify time-critical patients and reduce waiting times by assigning higher priority. However, no existing method directly measures this core clinical function. We developed and validated Triage Effectiveness (TE) as a framework for quantifying how well triage systems reduce waiting times for time-critical patients. Methods: Using data from 463,209 visits across eight emergency departments, we developed TE as a scale where 0% equals a first-come-first-serve strategy (no triage) and 100% equals perfect prioritization. The framework includes two complementary measures: 1. Waiting Time-based TE (WTE) measuring actual waiting time reduction, where 100% represents zero waiting time, and 2.... (More)
Background: Emergency departments use triage to identify time-critical patients and reduce waiting times by assigning higher priority. However, no existing method directly measures this core clinical function. We developed and validated Triage Effectiveness (TE) as a framework for quantifying how well triage systems reduce waiting times for time-critical patients. Methods: Using data from 463,209 visits across eight emergency departments, we developed TE as a scale where 0% equals a first-come-first-serve strategy (no triage) and 100% equals perfect prioritization. The framework includes two complementary measures: 1. Waiting Time-based TE (WTE) measuring actual waiting time reduction, where 100% represents zero waiting time, and 2. Rank-based TE (RTE) measuring queue position improvement where 100% represents placement first in queue. Both can be calculated as theoretical TE (based only on priorities) and observed TE (actual clinical performance). We validated WTE and RTE calculations using analytical queueing models adapted for classification uncertainty and assessed transferability across hospitals. Results: Queueing theory validation showed strong alignment with both WTE and RTE calculations, with RTE demonstrating greater robustness and less sensitivity to ED utilization patterns. TE increased with accuracy and produced negative values when triage performance was worse than chance. When applying the framework we found substantial gaps between theoretical and observed TE across all emergency departments, indicating significant post triage reprioritization. Conclusions: The TE framework provides the first method for directly measuring the effectiveness of triage while utilizing full ordinal priority information. TE can assess the effectiveness of initial triage and the impact of post-triage re-prioritization.
(Less)
- author
- Johansson, André
LU
; Fodor, Viktoria
; Forberg, Jakob Lundager
LU
; Ekwall, Anna
LU
and Ekelund, Ulf
LU
- organization
- publishing date
- 2026-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Emergency Care, Patient Prioritization, Performance Metrics, Priority Queues, Priority Triage, Quality Indicators, Queueing Theory, Triage Effectiveness, Waiting Time Analysis
- in
- BMC Medical Research Methodology
- volume
- 26
- issue
- 1
- article number
- 142
- publisher
- BioMed Central (BMC)
- external identifiers
-
- pmid:42321619
- scopus:105042227652
- ISSN
- 1471-2288
- DOI
- 10.1186/s12874-026-02918-w
- language
- English
- LU publication?
- yes
- id
- f105d718-8e19-4c47-ba52-643206295c5f
- date added to LUP
- 2026-08-20 16:19:12
- date last changed
- 2026-09-03 17:21:13
@article{f105d718-8e19-4c47-ba52-643206295c5f,
abstract = {{<p>Background: Emergency departments use triage to identify time-critical patients and reduce waiting times by assigning higher priority. However, no existing method directly measures this core clinical function. We developed and validated Triage Effectiveness (TE) as a framework for quantifying how well triage systems reduce waiting times for time-critical patients. Methods: Using data from 463,209 visits across eight emergency departments, we developed TE as a scale where 0% equals a first-come-first-serve strategy (no triage) and 100% equals perfect prioritization. The framework includes two complementary measures: 1. Waiting Time-based TE (WTE) measuring actual waiting time reduction, where 100% represents zero waiting time, and 2. Rank-based TE (RTE) measuring queue position improvement where 100% represents placement first in queue. Both can be calculated as theoretical TE (based only on priorities) and observed TE (actual clinical performance). We validated WTE and RTE calculations using analytical queueing models adapted for classification uncertainty and assessed transferability across hospitals. Results: Queueing theory validation showed strong alignment with both WTE and RTE calculations, with RTE demonstrating greater robustness and less sensitivity to ED utilization patterns. TE increased with accuracy and produced negative values when triage performance was worse than chance. When applying the framework we found substantial gaps between theoretical and observed TE across all emergency departments, indicating significant post triage reprioritization. Conclusions: The TE framework provides the first method for directly measuring the effectiveness of triage while utilizing full ordinal priority information. TE can assess the effectiveness of initial triage and the impact of post-triage re-prioritization.</p>}},
author = {{Johansson, André and Fodor, Viktoria and Forberg, Jakob Lundager and Ekwall, Anna and Ekelund, Ulf}},
issn = {{1471-2288}},
keywords = {{Emergency Care; Patient Prioritization; Performance Metrics; Priority Queues; Priority Triage; Quality Indicators; Queueing Theory; Triage Effectiveness; Waiting Time Analysis}},
language = {{eng}},
number = {{1}},
publisher = {{BioMed Central (BMC)}},
series = {{BMC Medical Research Methodology}},
title = {{Triage effectiveness : a framework for quantifying the effect of emergency triage prioritization}},
url = {{http://dx.doi.org/10.1186/s12874-026-02918-w}},
doi = {{10.1186/s12874-026-02918-w}},
volume = {{26}},
year = {{2026}},
}