This study will compare two emergency triage algorithm - Ten Second Triage (TST) versus Sieve - to see which one works better during simulated mass-casualty incidents. Triage is the process of quickly deciding which patients need immediate care when there are many injured people. Making fast and accurate decisions is essential in these situations. Ambulance professionals and students in French-speaking Switzerland will be invited to take part. Participants will be randomly assigned to use either the TST method or the Sieve method. After a short introduction to the assigned method, each participant will complete two computer-based simulation scenarios involving 17 injured patients each (one scenario with penetrating injuries and one with blunt injuries). The simulated patients' conditions will change over time, similar to real-life emergencies using a physiological validated simulator (HUMAn). The main goal is to measure how accurately participants identify patients who need immediate treatment. For each correct triage decision, participants receive one point. A total score will be calculated across both scenarios. If a sufficient sample size could be reached, a mixed effect logistic regression model will be generated to answer to research question. The study will also measure how long participants take to make triage decisions, how often patients are over-triaged or under-triaged, and how easy participants find the method to use. The results will help determine which triage method may be more effective for use by ambulance personnel during major incidents.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
TRIPLE
Enrollment
200
Ten Second Triage (TST) is a rapid primary triage algorithm designed for use in mass-casualty incidents. It aims to allow rescuers to assess and categorize a patient in approximately 10 seconds based on a small number of immediately observable clinical signs. The algorithm focuses on key life-saving indicators such as ability to walk, presence of major external bleeding, airway status, breathing effectiveness, and level of consciousness. Based on these findings, patients are assigned to standard triage categories (e.g., immediate, urgent, delayed, or deceased). TST prioritizes speed and simplicity to support rapid decision-making when resources are limited and many victims require simultaneous assessment.
Sieve (NARU) triage algorithm is a structured primary triage method used during mass-casualty incidents, developed and promoted by the National Ambulance Resilience Unit (NARU). It is designed to rapidly sort large numbers of patients based on simple physiological criteria. The Sieve algorithm follows a stepwise assessment focusing on the ability to walk, breathing status and rate, and circulation (including signs of life-threatening hemorrhage). Patients are then assigned to standard triage categories (immediate, urgent, delayed, or deceased). Sieve emphasizes consistency and reproducibility of triage decisions and is widely used in prehospital disaster response and training to support safe prioritization when resources are limited.
École supérieure de soins ambulanciers (ESAMB)
Geneva, Canton of Geneva, Switzerland
RECRUITINGTriage accuracy (triage score)
Triage accuracy is defined as the proportion of correct triage decisions made by each participant across two simulated mass-casualty scenarios (34 patients in total). For each simulated patient, participants receive: 1 point for a correct triage decision (0 points for an incorrect decision). A triage decision is considered correct if the assigned priority category matches the simulated patient's expected clinical evolution based on the HUMAn dynamic simulation model (i.e., correct identification of patients requiring immediate treatment versus those who do not, including appropriate classification of deceased patients). The primary endpoint is the total triage score per participant (range 0-34), calculated by summing correct decisions across both scenarios.
Time frame: Through study completion, an average of 1 hour
Triage duration
Time required to assign a triage category to each simulated patient, measured automatically from first patient contact to final triage decision within the simulation platform. Results will be analyzed as mean triage time per patient and/or per participant.
Time frame: Through study completion, an average of 1 hour
Overtriage rate
Proportion of patients assigned to a higher priority category than clinically indicated according to the reference standard (HUMAn simulation model). Expressed as a percentage of total triage decisions per participant.
Time frame: Through study completion, an average of 1 hour
Undertriage rate
Proportion of patients assigned to a lower priority category than clinically indicated according to the reference standard. Expressed as a percentage of total triage decisions per participant.
Time frame: Through study completion, an average of 1 hour
User satisfaction and perceived ease of use
Participant-reported evaluation of the assigned triage algorithm, measured using a post-simulation questionnaire (e.g., Likert-scale items assessing clarity, ease of application, and overall satisfaction on a scale of 1 "Very unsatisfied/Not clear at all/Very difficult to apply to 5 "Very satisfied/Absolutely clear/Very easy to apply).
Time frame: Through study completion, an average of 1 hour
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