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Development Of A Novel Methodology To Assess The Surgeon’s Pre-Surgical Mental Model And Plan Of Complex Congenital Heart Procedures Within Virtual Reality (VR)
Matthew Bramlet, MD1, Eliot Bethke
2, Jenny Amos, PhD
2, Brad Sutton, PhD
1, Harma Turbendian, MD
3, Mark Plunkett, MD
4.
1University of Illinois, Peoria, IL, USA,
2University of Illinois, Champaign, IL, USA,
3University of Illinois College of Medicine Peoria, Peoria, IL, USA,
4University of Illinois College of Medicine Peoria, Peoria, IL, USA.
Objective(s):Patient outcomes research in 3D modeling of congenital heart disease remains difficult. Our single institution has performed 3D pre-surgical analysis on over 200 cases with enthusiastic adoption by team members. Therefore, we designed a study to analyze the change in understanding a surgeon experiences as they review patient specific 3D models.
Methods: Employing an established think aloud research format, we recorded the surgeon’s review of 3D models in VR. Capturing real-time verbalizations and actions in VR, we developed a method of quantitative measures from NASA task load indices (NASA-TLX) as well as qualitative evaluations of VR session recordings which enhance understanding of how VR influences clinical decision making, surgical confidence, and cognitive load borne by physicians when reviewing patient anatomy. Thirty surgical cases were recorded, this study represents review of the first ten. Five independent reviewers codified the context of oral responses to each case.
Results:The recorded behaviors and verbalizations revealed four major themes: 1) Decision making arises from exploration, 2) 3D exploration improves perception of anatomy, 3) Emotion identifies change in code, and 4) Physician’s confidence may mask more complex thought processes. Fleiss’ kappa analysis revealed an average agreement of 0.59 where 0.6-0.8 represents strong agreement with 0.0 implying random chance; pre-post 3D confidence in anatomy increased from 4/5 to 5/5 p 0.012.
Conclusions:Deploying this novel methodology, rich in data, into pre-surgical 3D analysis overcomes bias in survey-based studies through deeper insight into the surgeon’s mindset as they encounter the 3D model for the first time.
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