Impact of Ten Second Triage vs. Sieve on Triage Performance in Simulated Mass-Casualty Incidents

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.

NCT Number	NCT07436052
Lead Sponsor	Stuby Loric Collaborators: École Supérieure de Soins Ambulanciers - College of Higher Education in Prehospital Care, University Hospital, Geneva, HEIG-VD- Haute Ecole d'Ingénierie et de Gestion du Canton de Vaud
Conditions	Mass Casualty Incidents
Enrollment	201 participants
Start Date	2026-02-13
Primary Completion	2026-03-13 (estimated)
Study Completion	2026-03-13 (estimated)
Updated on ClinicalTrials.gov	2026-04-22