Literature DB >> 35253018

Towards an AI Coach to Infer Team Mental Model Alignment in Healthcare.

Sangwon Seo1, Lauren R Kennedy-Metz2, Marco A Zenati2, Julie A Shah3, Roger D Dias4, Vaibhav V Unhelkar1.   

Abstract

Shared mental models are critical to team success; however, in practice, team members may have misaligned models due to a variety of factors. In safety-critical domains (e.g., aviation, healthcare), lack of shared mental models can lead to preventable errors and harm. Towards the goal of mitigating such preventable errors, here, we present a Bayesian approach to infer misalignment in team members' mental models during complex healthcare task execution. As an exemplary application, we demonstrate our approach using two simulated team-based scenarios, derived from actual teamwork in cardiac surgery. In these simulated experiments, our approach inferred model misalignment with over 75% recall, thereby providing a building block for enabling computer-assisted interventions to augment human cognition in the operating room and improve teamwork.

Entities:  

Keywords:  Bayesian inference; artificial intelligence; cardiac surgery; patient safety; surgical data science; teamwork

Year:  2021        PMID: 35253018      PMCID: PMC8893011          DOI: 10.1109/cogsima51574.2021.9475925

Source DB:  PubMed          Journal:  IEEE Conf Cogn Comput Asp Situat Manag


  6 in total

1.  Association between implementation of a medical team training program and surgical mortality.

Authors:  Julia Neily; Peter D Mills; Yinong Young-Xu; Brian T Carney; Priscilla West; David H Berger; Lisa M Mazzia; Douglas E Paull; James P Bagian
Journal:  JAMA       Date:  2010-10-20       Impact factor: 56.272

2.  First Reported Use of Team Cognitive Workload for Root Cause Analysis in Cardiac Surgery.

Authors:  Marco A Zenati; Kay B Leissner; Suzana Zorca; Lauren Kennedy-Metz; Steven J Yule; Roger D Dias
Journal:  Semin Thorac Cardiovasc Surg       Date:  2018-12-19

3.  Dissecting Cardiac Surgery: A Video-based Recall Protocol to Elucidate Team Cognitive Processes in the Operating Room.

Authors:  Roger D Dias; Marco A Zenati; Heather M Conboy; Lori A Clarke; Leon J Osterweil; George S Avrunin; Steven J Yule
Journal:  Ann Surg       Date:  2021-08-01       Impact factor: 12.969

Review 4.  Patient safety in the cardiac operating room: human factors and teamwork: a scientific statement from the American Heart Association.

Authors:  Joyce A Wahr; Richard L Prager; J H Abernathy; Elizabeth A Martinez; Eduardo Salas; Patricia C Seifert; Robert C Groom; Bruce D Spiess; Bruce E Searles; Thoralf M Sundt; Juan A Sanchez; Scott A Shappell; Michael H Culig; Elizabeth H Lazzara; David C Fitzgerald; Vinod H Thourani; Pirooz Eghtesady; John S Ikonomidis; Michael R England; Frank W Sellke; Nancy A Nussmeier
Journal:  Circulation       Date:  2013-08-05       Impact factor: 29.690

5.  Computer Vision in the Operating Room: Opportunities and Caveats.

Authors:  Lauren R Kennedy-Metz; Pietro Mascagni; Antonio Torralba; Roger D Dias; Pietro Perona; Julie A Shah; Nicolas Padoy; Marco A Zenati
Journal:  IEEE Trans Med Robot Bionics       Date:  2020-11-24

6.  Sensors for Continuous Monitoring of Surgeon's Cognitive Workload in the Cardiac Operating Room.

Authors:  Lauren R Kennedy-Metz; Roger D Dias; Rithy Srey; Geoffrey C Rance; Cesare Furlanello; Marco A Zenati
Journal:  Sensors (Basel)       Date:  2020-11-19       Impact factor: 3.576

  6 in total
  2 in total

1.  Association Between Operating Room Noise and Team Cognitive Workload in Cardiac Surgery.

Authors:  Lauren R Kennedy-Metz; Maria Arshanskiy; Sandra Keller; David Arney; Roger D Dias; Marco A Zenati
Journal:  IEEE Conf Cogn Comput Asp Situat Manag       Date:  2022-07-22

2.  Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing.

Authors:  Manpreet Kaur; Jeremy Costello; Elyse Willis; Karen Kelm; Marek Z Reformat; Francois V Bolduc
Journal:  J Med Internet Res       Date:  2022-08-05       Impact factor: 7.076

  2 in total

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