A Taxonomy of Delivery and Documentation Deviations During Delivery of High-Fidelity Simulations. Issue 1 (February 2017) - McIvor, William R.; Banerjee, Arna; Boulet, John R.; Bekhuis, Tanja; Tseytlin, Eugene; Torsher, Laurence; DeMaria, Samuel; Rask, John P.; Shotwell, Matthew S.; Burden, Amanda; Cooper, Jeffrey B.; Gaba, David M.; et al.
Abstract : Introduction: We developed a taxonomy of simulation delivery and documentation deviations noted during a multicenter, high-fidelity simulation trial that was conducted to assess practicing physicians' performance. Eight simulation centers sought to implement standardized scenarios over 2 years. Rules, guidelines, and detailed scenario scripts were established to facilitate reproducible scenario delivery; however, pilot trials revealed deviations from those rubrics. A taxonomy with hierarchically arranged terms that define a lack of standardization of simulation scenario delivery was then created to aid educators and researchers in assessing and describing their ability to reproducibly conduct simulations. Methods: Thirty-six types of delivery or documentation deviations were identified from the scenario scripts and study rules. Using a Delphi technique and open card sorting, simulation experts formulated a taxonomy of high-fidelity simulation execution and documentation deviations. The taxonomy was iteratively refined and then tested by 2 investigators not involved with its development. Results: The taxonomy has 2 main classes, simulation center deviation and participant deviation, which are further subdivided into as many as 6 subclasses. Inter-rater classification agreement using the taxonomy was 74% or greater for each of the 7 levels of its hierarchy. Cohen kappa calculations confirmed substantial agreement beyond that expected by chance. All deviations were classified within the taxonomy. Conclusions: This is a useful taxonomy that standardizes terms for simulation delivery and documentation deviations, facilitates quality assurance in scenario delivery, and enables quantification of the impact of deviations upon simulation-based performance assessment. Abstract : Supplemental digital content is available in the text.