MP10-07: The Relationship of Technical Skills and Cognitive Workload to Errors During Robotic Surgical Exercises

Sidney I Roberts, Steven Cen, Jessica H Nguyen, Laura C Perez, Luis G Medina, Runzhuo Ma*, Los Angeles, CA, Sandra P Marshall, Solana Beach, CA, Rafal Kocielnik, Anima Anandkumar, Pasadena, CA, Andrew J Hung, Los Angeles, CA

Introduction: Surgical performance and skill in robotic surgery has been shown to impact patient outcomes and complication rates. Cognitive workload, or mental strain in the working memory, has been shown to differ between surgeon experience levels. Herein, we attempt to understand the relationship between surgeon technical skills, cognitive workload, and discrete errors committed during a simulated robotic dissection task.

Methods: Participant surgeons performed a robotic surgery dissection exercise (peeling a clementine, removing a single wedge). Participants were grouped based on surgical experience: novice (no prior surgical experience), intermediate ( < 100 robotic cases), and expert (= 100 cases). Technical skills were evaluated utilizing the validated Global Evaluative Assessment of Robotic Skills (GEARS) assessment tool. The task was also evaluated for errors during active dissection or passive retraction. Cognitive workload was quantified as an Index of Cognitive Activity (ICA), derived from Task-Evoked-Pupillary-Response metrics; ICA ranged 0-1, with 1 representing maximum ICA. Generalized Estimating Equation (GEE) was used for all modelings to establish relationships between surgeon technical skills, cognitive workload and errors.

Results: Overall there were 22 patients: 7 novices, 9 intermediates, and 6 experts. We found a strong association between technical skills, as measured by multiple GEARS domains (depth perception, force sensitivity and robotic control), and passive errors - with higher GEARS scores associated with a lower relative risk of errors (all p < 0.01). For novice surgeons, as average GEARS scores increased, the average estimated ICA decreased. In contrast, as average GEARS increased for expert surgeons, the average estimated ICA increased. When exhibiting optimal technical skill (maximal GEARS scores) novices and experts had a similar range of ICA scores (ICA 0.47 and 0.42, respectively) (Figure 1).

Conclusions: This study found that there is an optimal cognitive workload level for surgeons of all experience levels during our robotic surgical exercise. Select technical skills were strong predictors of errors. Future research will explore whether an ideal cognitive workload range truly optimizes surgical performance and reduce surgical errors.

Source of Funding: This study was supported in part by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number K23EB026493.