Patterns of Skills Acquisition in Anesthesiologists During Simulated Interscalene Block Training on a Soft Embalmed Thiel Cadaver: Cohort Study

Abstract

Background: The demand for regional anesthesia for major surgery has increased considerably, but only a small number of anesthesiologists can provide such care. Simulations may improve clinical performance. However, opportunities to rehearse procedures are limited, and the clinical educational outcomes prescribed by the Royal College of Anesthesiologists training curriculum 2021 are difficult to attain. Educational paradigms, such as mastery learning and dedicated practice, are increasingly being used to teach technical skills to enhance skills acquisition. Moreover, high-fidelity, resilient cadaver simulators are now available: the soft embalmed Thiel cadaver shows physical characteristics and functional alignment similar to those of patients. Tissue elasticity allows tissues to expand and relax, fluid to drain away, and hundreds of repeated injections to be tolerated without causing damage. Learning curves and their intra- and interindividual dynamics have not hitherto been measured on the Thiel cadaver simulator using the mastery learning and dedicated practice educational paradigm coupled with validated, quantitative metrics, such as checklists, eye tracking metrics, and self-rating scores.

Objective: Our primary objective was to measure the learning slopes of the scanning and needling phases of an interscalene block conducted repeatedly on a soft embalmed Thiel cadaver over a 3-hour period of training.

Methods: A total of 30 anesthesiologists, with a wide range of experience, conducted up to 60 ultrasound-guided interscalene blocks over 3 hours on the left side of 2 soft embalmed Thiel cadavers. The duration of the scanning and needling phases was defined as the time taken to perform all the steps correctly. The primary outcome was the best-fit linear slope of the log-log transformed time to complete each phase. Our secondary objectives were to measure preprocedural psychometrics, describe deviations from the learning slope, correlate scanning and needling phase data, characterize skills according to clinical grade, measure learning curves using objective eye gaze tracking and subjective self-rating measures, and use cluster analysis to categorize performance irrespective of grade.

Results: The median (IQR; range) log-log learning slopes were -0.47 (-0.62 to -0.32; -0.96 to 0.30) and -0.23 (-0.34 to -0.19; -0.71 to 0.27) during the scanning and needling phases, respectively. Locally Weighted Scatterplot Smoother curves showed wide variability in within-participant performance. The learning slopes of the scanning and needling phases correlated: ρ=0.55 (0.23-0.76), P<.001, and ρ=-0.72 (-0.46 to -0.87), P<.001, respectively. Eye gaze fixation count and glance count during the scanning and needling phases best reflected block duration. Using clustering techniques, fixation count and glance were used to identify 4 distinct patterns of learning behavior.

Conclusions: We quantified learning slopes by log-log transformation of the time taken to complete the scanning and needling phases of interscalene blocks and identified intraindividual and interindividual patterns of variability.

Keywords: eye tracking; learning curves; regional anesthesia; simulation; ultrasonography.

Figure 1

Best-fit linear learning slopes demonstrated on log-log transformed (power) model from participants 1 to 33 during search phase of simulated interscalene block. Participants 6, 26, and 29 are excluded. Log time (duration) taken to complete all steps on y-axis, and log sequence of blocks (1 to 4) the x-axis. The blue straight line is the best-fit line through the data. The 95% CIs about the slope are shown in light gray.

Figure 2

Best-fit Locally Weighted Scatterplot Smoother learning slopes demonstrated on log-log transformed (power) model from participants 1 to 33 during needling phase of simulated interscalene block. Participants 6, 26, and 29 were excluded. Log time (duration) taken to complete all steps on y-axis, and log sequence of blocks (1 to 4) the x-axis. The blue straight line is the best-fit line through the data. The 95% CIs about the slope are shown in light gray.

Figure 3

Grade. Experts had a flatter slope but greater variability during scanning, but less variability during needling (all comparisons P=.02). Novice anesthesiology trainees correspond to years 1 to 2 (1/2); intermediate anesthesiology trainees to years 3 to 4 (3/4); and higher anesthesiology trainees to years 5 to 7 (5/6/7). Consultant non-expert anesthesiologists designated as “Con”.

Figure 4

Eye gaze fixation count. Best-fit linear learning slopes demonstrated on log-log transformed (power) model from participants 1 to 33 during search phase of simulated interscalene block. Participants 6, 26, and 29 were excluded. Fixation count on y-axis, and log sequence of blocks (1 to 4) the x-axis. The blue straight line is the best-fit line through the data. The 95% CI about the slope are shown in light gray.

Figure 5

Slope estimate, slope standard error and asymptote of the primary end point, duration (Dur) and secondary end-points, median (IQR [range]). Secondary end-points include: eye gaze fixation count (Fix), relative fixation to the monitor (Fix%), glance count (G), and relative dwell time (W%) during the scanning and needling phases; and pre block anxiety (Anx) and self-confidence (Pre) and post block self-confidence (Pst). Large variation in effect with duration, fixation and glance count but not psychological variables.

Figure 6

Correlation (ranging from −1 to +1) between procedural duration, fixation count, and glance count in the scanning (S) and needling (N) phases; mean pre- and postprocedural confidence; procedural anxiety; and initial and final proficiency. The scale indicated on the right is color mapped in shades of purple from 0 to +1 and shades of blue from 0 to −1. The largest correlations existed among procedural duration, fixation, and glance count in both the scanning and needling phases.

Figure 7

Dendrograms created by cluster analysis of preprocedural and procedural fixation and glance counts. Search phase (groups A, B, C, D) and needle phase (groups a, b, c, d).

Figure 8

Characteristics of scanning phase learning slopes (procedure duration, eye fixation and glance) according to groups defined by cluster analysis. Characteristics include intercept, slope standard error and asymptote. Better performance was associated with reductions in: the asymptote of procedure duration (image J), (χ² 17.0, P<.001); the intercept (image B), (χ² 9.5, P=.02) and asymptote (image K), (χ² 21.2, P<.001) of eye gaze fixations; and the learning slope of eye glances (image F), (χ² 9.3, P=.03).

Figure 9

Characteristics (intercept, slope, error and asymptote) of the learning slopes for duration, eye fixations and eye glances during the needling phase, according to groups defined by cluster analysis. better performance was associated with reductions in: the standard error (image H) (χ² 9.6, P .02); and asymptote of procedure duration (image K) (χ² 14.4, P=.002); and the intercept (image B) (χ² 12.8, P=.005) and asymptote of eye gaze fixations (image L) (χ² 7.9, P=.04).