Development and verification of a taxonomy of assessment metrics for surgical technical skills.

PURPOSE: To create and empirically verify a taxonomy of metrics for assessing surgical technical skills, and to determine which types of metrics, skills, settings, learners, models, and instruments were most commonly reported in the technical skills assessment literature. METHOD: In 2011-2012, the authors used a rational analysis of existing and emerging metrics to create the taxonomy, and used PubMed to conduct a systematic literature review (2001-2011) to test the taxonomy's comprehensiveness and verifiability. Using 202 articles identified from the review, the authors classified metrics according to the taxonomy and coded data concerning their context and use. Frequencies (counts, percentages) were calculated for all variables. RESULTS: The taxonomy contained 12 objective and 4 subjective categories. Of 567 metrics identified in the literature, 520 (92%) were classified using the new taxonomy. Process metrics outnumbered outcome metrics by 8:1. The most frequent metrics were "time," "manual techniques" (objective and subjective), "errors," and "procedural steps." Only one new metric, "learning curve," emerged. Assessments of basic motor skills and skills germane to laparoscopic surgery dominated the literature. Novices, beginners, and intermediate learners were the most frequent subjects, and box trainers and virtual reality simulators were the most frequent models used for assessing performance. CONCLUSIONS: Metrics convey what is valued in human performance. This taxonomy provides a common nomenclature. It may help educators and researchers in procedurally oriented disciplines to use metrics more precisely and consistently. Future assessments should focus more on bedside tasks and open surgical procedures and should include more outcome metrics.