Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations. (February 2022)

• Record Type: Journal Article
• Authors: Perry, Omer; Jaffe, Eli; Bitan, Yuval
• Other Names: Keebler Joseph R. guest-editor.; Salas Eduardo guest-editor.; Rosen Michael A. guest-editor.; Sittig Dean F. guest-editor.; Thomas Eric guest-editor.
• Is Part Of: Human factors. Volume 64:Number 1(2022)
• Page Start: 228
• Page End: 249
• Publication Date: 2022-02
• Subjects: communication -- teamwork -- mass-casualty incident -- information management -- simulation; Human engineering -- Periodicals; 620.82
• DOI: 10.1177/00187208211018880
• Languages: English
• ISSNs: 0018-7208

Abstract

Objective: To develop a new model to quantify information management dynamically and to identify factors that lead to information gaps. Background: Information management is a core task for emergency medical service (EMS) team leaders during the prehospital phase of a mass-casualty incident (MCI). Lessons learned from past MCIs indicate that poor information management can lead to increased mortality. Various instruments are used to evaluate information management during MCI training simulations, but the challenge of measuring and improving team leaders' abilities to manage information remains. Method: The Dynamic Communication Quantification (DCQ) model was developed based on the knowledge representation typology. Using multi point-of-view synchronized video, the model quantifies and visualizes information management. It was applied to six MCI simulations between 2014 and 2019, to identify factors that led to information gaps, and compared with other evaluation methods. Results: Out of the three methods applied, only the DCQ model revealed two factors that led to information gaps: first, consolidation of numerous casualties from different areas, and second, tracking of casualty arrivals to the medical treatment area and departures from the MCI site. Conclusion: The DCQ model allows information management to be objectively quantified. Thus, it reveals a new layer of knowledge, presenting information gaps during an MCI. Because the model is applicable to all MCI team leaders, it can make MCI simulations more effective. Application: This DCQ model quantifies information management dynamically during MCI training simulations.