E. E. Howie1, R. D. Dias2, R. J. Skipworth1, S. J. Wigmore1, S. Yule1,2 1University of Edinburgh, Surgical Sabermetrics Group, Edinburgh, SCOTLAND, United Kingdom 2Harvard School Of Medicine, Brookline, MA, USA
Introduction:
Surgeons constantly strive to optimize performance. Performance optimization in surgery can be informed by practices and evidence from other high-performing fields such as professional sports. Currently, performance assessments rely on subjective and retrospective measures, limiting the ability to improve performance and patient safety in real-time. Surgeons can learn from athletes’ performance monitoring and harness information from digital metrics via surgical sabermetrics which utilizes digital data from multiple sources to provide data-driven performance analysis. Cognitive load(CogL) plays a crucial role in performance, with overload impairing skills and judgment. CogL can be measured objectively using physiological metrics, such as Electrodermal activity(EDA), which measures autonomic change, or subjectively through self-report questionnaires such as the Surgery Task Load Index(SURG-TLX). This study aims to combine measures to assess changes to and influences on surgeon CogL throughout an operating list.
Methods:
Intraoperative EDA from attending surgeons was captured using a digital EDA sensor, worn on the upper shoulder. Additional data were collected on (i)mood, (ii)sleep quality and (iii)subjective workload, via SURG-TLX. EDA data underwent continuous decomposition analysis into its two components: tonic and phasic. Tonic EDA represents background autonomic arousal, whereas phasic EDA represents rises in response to an event or activity.
Results:
Six attending surgeons were recruited from one academic centre. Twenty-four general surgical procedures, such as cholecystectomy, from seven operating lists were included. The mean procedure length was 01:09:45 and the mean number of cases per operating list was 3.4. Tonic and phasic EDA increased over the operating list. Across all individuals, both mean EDA components increased from case one(phasic:0.02µ, tonic:0.39µ) to case three(phasic:0.07µ, tonic:1.05µ). Kruskal-Wallis chi-squared showed significant differences in both phasic(x2 = 6.62, p <0.05) and tonic(x2 = 8.008, p<0.05) EDA components across each case. The mean total SURG-TLX score was 46/126. Procedure duration was moderately correlated with the total SURG-TLX score(rs=0.560, p<0.05), and specifically with the mental demand(rs=0.544, p<0.05), temporal demand(rs=0.601, p=0.008) and task complexity(rs=0.552, p<0.05) subscores of the SURG-TLX. Mean phasic EDA was strongly correlated with overall SURG-TLX scores(rs=0.709, p<0.05).
Conclusion:
This study found EDA increases across a surgical list, demonstrating that CogL builds throughout a surgeon's day. In addition, surgeons perceived workload significantly correlated with case duration. Using digital sensors to measure objective CogL provides the opportunity for automated, real-time performance assessment and advanced feedback, with opportunities to identify factors that impact CogL and to modify behaviour accordingly.