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Chest tube insertion is required for most cases of traumatic pneumothorax. However, this procedure entails risks of potentially life-threatening complications. A “surgical” approach is widely recommended to minimize these risks. Simulation-based education has previously been used in surgical chest tube insertion, but not been subjected to rigorous evaluation. The primary objective was to evaluate the success rate of surgical chest tube insertion in a task trainer (previously published). Secondary objectives were to assess performance with a performance assessment scale (previously designed), to measure the time of insertion, and to seek out a correlation between the learner’s status, experience, and performance and success rate. Participants were surveyed for realism of the model and satisfaction; 65 participants (18 residents, 47 senior physicians) were randomized into SIM+ or SIM− groups. Both groups received didactic lessons. The SIM+ group was assigned deliberate practice on the model under supervision. Both groups were assessed on the model 1 month later. There was no difference between the SIM+ (n = 34) and SIM− (n = 31) groups regarding status (p = 0.44) or previous surgical insertion (p = 0.12). Success rate was 97 % (SIM+) and 58 % (SIM−), p = 0.0002. Performance score was 16.29 ± 1.82 (SIM+) and 11.39 ± 3.67 (SIM−), p = 3.13 × 10−8. SIM+ presented shorter dissection time than SIM− (p = 0.047), but procedure time was similar (p = 0.71). Status or experience was not correlated with success rate, performance score, procedure time, or dissection time. SIM+ gained more self-confidence, judged the model more realistic, and were more satisfied than SIM−. Simulation-based education significantly improved the success rate and performance of surgical chest tube insertion on a traumatic pneumothorax model.
Léger, A., Ghazali, A., Petitpas, F., Guéchi, Y., Boureau-Voultoury, A., & Oriot, D. (2016). Impact of simulation-based training in surgical chest tube insertion on a model of traumatic pneumothorax. Advances in Simulation, 1(1). https://doi.org/10.1186/s41077-016-0021-2
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