Evidence map›Paper›PMID 42202274›Full record

ArticleJMIR research protocols2026

Reducing Mis-triage in Emergency Departments (RemEDy): Protocol for Improving Triage Accuracy Through Real-time Evaluation and Artificial Intelligence.

Serena Sibilio, Bastiaan Van Grootven, Annette Christine Mettler, Philippe Claude Cattin, Ursula Feuz, Michael Simon, Franziska Zúñiga, Christian Hans Nickel

Abstract read
In one paragraph

Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Serena SibilioDepartment of Public Health, Institute of Nursing Science, Faculty of Medicine, University of Basel, Basel, Basel-City, Switzerland.ORCID 0000-0002-0223-3399
Bastiaan Van GrootvenDepartment of Public Health, Institute of Nursing Science, Faculty of Medicine, University of Basel, Basel, Basel-City, Switzerland.ORCID 0000-0002-3182-573X
Annette Christine MettlerDepartment of Biomedical Engineering, University of Basel, Allschwil, Basel-Landschaft, Switzerland.ORCID 0000-0003-1714-285X
Philippe Claude Cattin *Department of Biomedical Engineering, University of Basel, Allschwil, Basel-Landschaft, Switzerland.ORCID 0000-0001-8785-2713
Ursula FeuzDepartment of Public Health, Institute of Nursing Science, Faculty of Medicine, University of Basel, Basel, Basel-City, Switzerland.ORCID 0009-0002-1687-3095
Michael SimonDepartment of Public Health, Institute of Nursing Science, Faculty of Medicine, University of Basel, Basel, Basel-City, Switzerland.ORCID 0000-0003-2349-7219
Franziska ZúñigaDepartment of Public Health, Institute of Nursing Science, Faculty of Medicine, University of Basel, Basel, Basel-City, Switzerland.ORCID 0000-0002-8844-4903
Christian Hans NickelEmergency Department, University Hospital of Basel, Basel, Basel-City, Switzerland.ORCID 0000-0001-6619-9284

Funding

Swiss National Science Foundation 10004535
6 · The paper itself

Abstract

backgroundMis-triage represents a global concern, with reported rates ranging from 15% to 33%. Understanding its causes and contributing factors is essential for ensuring patient safety. Currently, available studies have mainly focused on evaluating triage systems rather than investigating the human factors affecting triage performance. A major limitation in triage evaluation studies is the lack of standardized criteria to assess patient acuity and the absence of a clear consensus on how to measure triage accuracy. Most studies rely on retrospective data, which often fail to capture real-life clinical complexity. Therefore, the underlying causes and consequences of mis-triage remain partially understood.

objectiveThis study aims to improve triage by defining the optimal triage evaluation process and identifying clinician-, patient-, and system-level factors that compromise its accuracy and safety.

methodsReducing Mis-Triage in Emergency Departments (RemEDy) will be a 4-phase, mixed methods project conducted across 7 Swiss emergency departments. The first phase will focus on developing a standardized triage evaluation instrument, combining evidence from a scoping review of triage evaluation processes, workshops with triage clinicians using design thinking methodology, and a modified Research and Development-University of California Delphi involving international experts and patient representatives. The second phase will prospectively implement this instrument in real time within a multicenter observational cohort study to evaluate triage performance; quantify mis-triage; and identify predictors at the patient level (eg, demographics), clinician level (eg, training), and system level (eg, crowding and length of stay). The third phase will focus on designing and validating an artificial intelligence-based decision support tool, applying multimodal models that integrate real-time triage data to enhance acuity prediction and minimize human error. The fourth phase will develop and evaluate a targeted training program, guided by the Capability, Opportunity, Motivation, and Behavior model, to strengthen triage accuracy and mitigate cognitive biases.

resultsThe project was funded by the Swiss National Science Foundation in March 2025 (grant 10004535). At submission, the scoping review is ongoing and expected to be completed in early 2026. Development and piloting of the triage evaluation instrument will take place in 2026. A multicenter cohort study is planned between October 2026 and June 2027. The intervention study is scheduled between October 2027 and December 2028. Final results are expected in 2029.

conclusionsThe RemEDy project addresses key limitations of current triage research, including the lack of standardized evaluation methods. By combining expert and clinician consensus; real-time assessment; and multilevel analysis of patient-, clinician-, and emergency department-level factors, RemEDy is expected to provide a more comprehensive understanding of mis-triage and its causes. RemEDy will establish a novel framework for real-time triage evaluation and inform the development of targeted training programs with the potential to improve triage accuracy, safety, and equity. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/92264.

Indexed as

Artificial IntelligenceEmergency Service, HospitalTriageHumansSwitzerlandAIartificial intelligencedecision supportemergency departmentmis-triagetraining programtriage evaluation

Identifiers

PMID42202274
PMCPMC13254509

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.