From communication to action: using ordered network analysis to model team performance in clinical simulation

Area of Science:

• Medical simulation
• Teamwork dynamics
• Network analysis

Background:

• Effective team communication is vital for managing medical emergencies like malignant hyperthermia (MH).
• Current assessment methods lack the dynamic and temporal analysis needed for effective simulation training feedback.
• Ordered network analysis (ONA) offers a novel approach to model communication sequences in simulated scenarios.

Purpose of the Study:

• To demonstrate the application of ONA for analyzing team communication patterns during simulated MH events.
• To identify communication differences between high- and low-performing teams in managing MH.
• To provide a quantitative method for assessing teamwork in critical care simulations.

Main Methods:

• Twenty-two anesthesiologists participated in video-recorded MH simulations.
• Team communication was coded using the Team Reflection Behavioral Observation (TuRBO) framework.
• ONA modeled communication sequences, comparing patterns between high- (timely dantrolene) and low-performing teams.

Main Results:

• High-performing teams (23%) showed smoother transitions from situation assessment to planning and implementation.
• Low-performing teams frequently cycled through assessment behaviors without progressing (p=0.04).
• High-performers exhibited stronger links between input, assessment, planning, and implementation.

Conclusions:

• Integrating video coding with ONA provides an innovative method for examining team behaviors.
• ONA can reveal crucial patterns in communication timing and sequences.
• This approach can guide targeted interventions to improve team coordination in clinical and simulated settings.