Content area

Abstract

Background

Effective team communication is crucial for managing medical emergencies like malignant hyperthermia (MH), but current assessment methods fail to capture the dynamic and temporal nature of teamwork processes. The lack of reliable measures to inform feedback to teams is likely limiting the overall effectiveness of simulation training. This study demonstrates the application of ordered network analysis (ONA) to model communication sequences during the simulated MH scenario.

Methods

Twenty-two anesthesiologists participated in video-recorded MH simulations. Each scenario involved one participant as the primary anesthesiologist with confederates in supporting roles. Team communication was coded using the Team Reflection Behavioral Observation (TuRBO) framework, capturing behaviors related to information gathering, evaluation, planning, and implementation. ONA modeled the sequences of these coded behaviors as dynamic networks. Teams were classified as high- or low-performing based on timely dantrolene administration and appropriate MH treatment actions. Network visualizations and statistical tests compared communication patterns between groups.

Results

Five of 22 teams (23%) were high-performing. ONA revealed high-performers transitioned more effectively from situation assessment (information seeking/evaluation) to planning and implementation, while low-performers cycled between assessment behaviors without progressing (p = 0.04, Cohen’s d = 1.72). High-performers demonstrated stronger associations between invited input, explicitly assessing the situation, stating plans, and implementation.

Conclusions

Integrating video coding with ONA provides an innovative approach for examining team behaviors. Leveraging ONA can uncover patterns in communication timing and sequences, guiding targeted interventions to improve team coordination in various real-world clinical and simulated settings (e.g., operating room, EMS, ICU).

Details

1009240
Business indexing term
Title
From communication to action: using ordered network analysis to model team performance in clinical simulation
Publication title
Volume
25
Pages
1-10
Publication year
2025
Publication date
2025
Section
Research
Publisher
Springer Nature B.V.
Place of publication
London
Country of publication
Netherlands
e-ISSN
14726920
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-04-03
Milestone dates
2024-06-13 (Received); 2025-03-26 (Accepted); 2025-04-03 (Published)
Publication history
 
 
   First posting date
03 Apr 2025
ProQuest document ID
3187549524
Document URL
https://www.proquest.com/scholarly-journals/communication-action-using-ordered-network/docview/3187549524/se-2?accountid=208611
Copyright
© 2025. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-04-29
Database
ProQuest One Academic