Objectives: To develop a precise mathematical formulation of resource-constrained triage, denoted the Sacco triage method (STM), to develop an evidence-based application to blunt trauma, and to compare the STM with the simple triage and rapid treatment (START) method.
Methods: Resource-constrained triage is modeled mathematically as a classic resource allocation problem. The objective is to maximize expected survivors given constraints on the timing and availability of resources. The model incorporates estimates of time-dependent victim survival probabilities based on an initial assessment and expected deterioration. For application to blunt trauma, an "RPM" score, based on respiratory rate, pulse rate, and motor response, was used to predict survivability. Logistic function-generated survival probability estimates for scene values of RPM were determined from 76,459 blunt-injured patients from the Pennsylvania Trauma Outcome Study (PTOS). The Delphi method provided expert consensus on victim deterioration rates, and the model was solved using linear programming. STM was compared with START across various criteria of process and outcome. Outcome was measured by expected number of survivors in simulated resource-constrained casualty incidents.
Results: In this mathematical simulation, RPM was a more accurate predictor of survivability from blunt trauma than the Injury Severity Score and the Revised Trauma Score, as measured by calibration and discrimination statistics. STM resulted in greater expected survivorship than START in all simulations.
Conclusions: Resource-constrained triage is modeled precisely as an evidence-based, outcome-driven method that maximizes expected survivors in consideration of resources. The lifesaving potential and operational advantages over current methods warrant scrutiny and further research.