Analyzing Procedural Time and Its Relationship to Performance in Microsurgical Training: A Pilot Study

Introduction Objective measures and precise variable selection are cornerstones of skill assessment. While the quantity and quality of movements in microsurgery are evaluated using advanced technology and innovative methods, it remains a challenge to move beyond the notion that skill improvement is synonymous with faster procedures. A critical analysis reveals that quality does not always align with speed, nor does improved performance necessarily mean faster performance. This study aims to analyze and describe the progression of time variables during skill training and to provide new tools for their thorough assessment and evaluation. Methods This trial followed a published microsurgical protocol measuring time/errors at defined stages. Procedures were chronologically recorded, capturing per-session counts, inter-session intervals, and protocol data. Misat-APP® collected data, exported to PostgreSQL®, and analyzed via Python® scripts. Samples were categorized by mistake levels to better evaluate temporal progression patterns. Data dispersion was analyzed by the coefficient of determination (R²) for regression modeling. A standard deviation method was applied (±2 SD) to refine the sample, standardize calculations, and eliminate outliers often found when working with sensitive variables. After the first analysis, the target was aimed exclusively at mistake-free procedures to establish the average-zero (AVO) index. This benchmark was then cross-referenced with qualitative error markers, revealing a consistent mistake-free speed range named "Safe Pace" (±0.2 SD from the AVO). Statistical significance was set at p < 0.05 throughout all analyses. Results The trial included 158 procedures performed over nine months and 75 sessions. After removing procedures with major mistakes, the sample accounted for 150 procedures. The total microscope time was 61 hours, 22 minutes, and 55 seconds. The time to complete the task (TCT) presented significant fluctuations (slowest = 3,057 seconds at the fourth procedure; fastest = 890 seconds at the 81st procedure), tracing a decreasing pattern with a significant dispersion level (R² = 0.601). While observing inter-session time gaps, and after refining the sample by removing outliers (±2 SD), a strong correlation was evidenced between gaps longer than 10 days and their impact on the TCT at the next session (paired T-test, p = 0.009). When calculating the AVO index (1,463.27 seconds), it was cross-referenced with the full sample, and the widest and significant "Safe Pace" corresponded to ± 0.2 SD (1,362.88-1,563.67 seconds; p = 0.012). Other findings suggested that time is also linked to the number of procedures in the same session, procedural strategy (magnification level, instruments, sequence of steps), final end-product quality, and the operator's attitude. Conclusion Time-related performance metrics were analyzed throughout the trial. Findings suggest that time alone is a low-reliability indicator for skill assessment, showing high sensitivity to external factors. The concept of an average time and a speed range where procedural errors tend to decrease ("Safe Pace") may offer a useful benchmark for both advising operators during training and evaluating their performance. These findings, while consistent with prior studies, require further investigation for confirmation. Additionally, data from experienced operators indicated that excessively fast procedures could be associated with a higher risk of errors.