Comparison of the SALT and Smart triage systems using a virtual reality simulator with paramedic students

Eur J Emerg Med. 2011 Dec;18(6):314-21. doi: 10.1097/MEJ.0b013e328345d6fd.

Abstract

Objectives: Virtual reality systems may allow for organized study of mass casualty triage systems by allowing investigators to replicate the same mass casualty incident, with the same victims, for a large number of rescuers. The study objectives were to develop such a virtual reality system, and use it to assess the ability of trained paramedic students to triage simulated victims using two triage systems.

Methods: Investigators created 25 patient scenarios for a highway bus crash in a virtual reality simulation system. Paramedic students were trained to proficiency on the new 'Sort, Assess, Life saving interventions, Treat and Transport (SALT)' triage system, and 22 students ran the simulation, applying the SALT algorithm to each victim. After a 3-month washout period, the students were retrained on the 'Smart' triage system, and each student ran the same crash simulation using the Smart system. Data inputs were recorded by the simulation software and analyzed with the paired t-tests.

Results: The students had a mean triage accuracy of 70.0% with SALT versus 93.0% with Smart (P=0.0001). Mean overtriage was 6.8% with SALT versus 1.8% with Smart (P=0.0015), and mean undertriage was 23.2% with SALT versus 5.1% with Smart (P=0.0001). The average time for a student to triage the scene was 21 min 3 s for SALT versus 11 min 59 s for Smart (P=0.0001).

Conclusion: The virtual reality platform seems to be a viable research tool for examining mass casualty triage. A small sample of trained paramedic students using the virtual reality system was able to triage simulated patients faster and with greater accuracy with 'Smart' triage than with 'SALT' triage.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Accidents, Traffic*
  • Algorithms
  • Allied Health Personnel / education*
  • Computer Simulation*
  • Confidence Intervals
  • Disaster Planning
  • Humans
  • Learning
  • Mass Casualty Incidents
  • Statistics as Topic
  • Teaching / methods
  • Triage / methods*
  • United States
  • User-Computer Interface*