There is a paucity of literature evaluating mass casualty systems and no clear 'gold standard' for measuring the efficacy of information decision support systems or triage systems that can be used in mass casualty events. The purpose of this research was the preliminary validation of a comprehensive conceptual model for a mass casualty continuum of care. This research examined key relationships among entities/factors needed to provide real-time visibility of data that track patients, personnel, resources and potential hazards that influence outcomes of care during mass casualty events.A modified Delphi technique was used to validate the proposed model using a panel of experts. The four research questions measured the extent to which experts agreed that the: 1) ten constructs represent appropriate predictors of outcomes of care during mass casualty events; 2) proposed relationships among the constructs provide valid representations of mass casualty triage; 3) proposed indicators for each construct represent appropriate measurements for the constructs; and 4) the proposed model is seen as useful to the further study of information and technology requirements during mass casualty events. The usefulness of the online Delphi process was also evaluated.A purposeful sample of 18 experts who work in the field of emergency preparedness/response was selected from across the United States. Computer, Internet and email applications were used to facilitate a modified Delphi technique through which experts provided initial validation for the proposed conceptual model. Two rounds of the Delphi process were needed to satisfy the criteria for consensus and/or stability related to the constructs, relationships and indicators in the model. Experts viewed the proposed model as relatively useful (Mean = 5.3 on a 7-point scale). Experts rated the online Delphi process favorably.Constructs, relationships and indicators presented in this model are viewed as preliminary. Future research is needed to develop the tools to measure the constructs and then test the model as a framework for studying effects and outcomes of mass casualty events. This study provides a foundation for understanding the complex context in which mass casualty events take place and the factors that influence outcomes of care.