title: ReSTART: A Novel Framework for Resource-Based Triage in Mass-Casualty Events.
abstract: OBJECTIVE
  Current guidelines for mass-casualty triage do not explicitly use information about resource availability. Even though this limitation has been widely recognized, how it should be addressed remains largely unexplored. The authors present a novel framework developed using operations research methods to account for resource limitations when determining priorities for transportation of critically injured patients. To illustrate how this framework can be used, they also develop two specific example methods, named ReSTART and Simple-ReSTART, both of which extend the widely adopted triage protocol Simple Triage and Rapid Treatment (START) by using a simple calculation to determine priorities based on the relative scarcity of transportation resources.
  
  
  METHODS
  The framework is supported by three techniques from operations research: mathematical analysis, optimization, and discrete-event simulation. The authors? algorithms were developed using mathematical analysis and optimization and then extensively tested using 9,000 discrete-event simulations on three distributions of patient severity (representing low, random, and high acuity). For each incident, the expected number of survivors was calculated under START, ReSTART, and Simple-ReSTART. A web-based decision support tool was constructed to help providers make prioritization decisions in the aftermath of mass-casualty incidents based on ReSTART.
  
  
  RESULTS
  In simulations, ReSTART resulted in significantly lower mortality than START regardless of which severity distribution was used (paired t test, p<.01). Mean decrease in critical mortality, the percentage of immediate and delayed patients who die, was 8.5% for low-acuity distribution (range ?2.2% to 21.1%), 9.3% for random distribution (range ?0.2% to 21.2%), and 9.1% for high-acuity distribution (range ?0.7% to 21.1%). Although the critical mortality improvement due to ReSTART was different for each of the three severity distributions, the variation was less than 1 percentage point, indicating that the ReSTART policy is relatively robust to different severity distributions.
  
  
  CONCLUSIONS
  Taking resource limitations into account in mass-casualty situations, triage has the potential to increase the expected number of survivors. Further validation is required before field implementation; however, the framework proposed in here can serve as the foundation for future work in this area.
authors.forename: Alex F
authors.initials: AF
authors.lastname: Mills
authors.forename: Nilay T
authors.initials: NT
authors.lastname: Argon
authors.forename: Serhan
authors.initials: S
authors.lastname: Ziya
authors.forename: Brian
authors.initials: B
authors.lastname: Hiestand
authors.forename: James
authors.initials: J
authors.lastname: Winslow
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006295:Health Resources; D006801:Humans; D054527:Mass Casualty Incidents; D009026:Mortality; D014218:Triage / Q000379:methods*