Assessment of competence in simulated flexible bronchoscopy using motion analysis

Sara Colella, Morten Bo Søndergaard Svendsen, Lars Konge, Lars Bo Svendsen, Pradeesh Sivapalan, Paul Clementsen

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    Abstrakt

    Background: Flexible bronchoscopy should be performed with a correct posture and a straight scope to optimize bronchoscopy performance and at the same time minimize the risk of work-related injuries and endoscope damage. Objectives: We aimed to test whether an automatic motion analysis system could be used to explore if there is a correlation in scope movements and the operator's level of experience. Our hypothesis was that experienced bronchoscopists move less and keep the flexible scope straighter than less-experienced bronchoscopists while performing procedures. Methods: Eleven novices, 9 intermediates and 9 experienced bronchoscopy operators performed 3 procedures each on a bronchoscopy simulator. The Microsoft Kinect system was used to automatically measure the total deviation of the scope from a perfectly straight, vertical line. Results: The low-cost motion analysis system could measure the accumulated deviation of the scope precisely during the procedure. The deviations were greatest for the novices and smallest for the most experienced operators for all 3 procedures (p = 0.01, p = 0.01 and p = 0.04, respectively). The total deviation from the straight scope correlated negatively with the performance on the simulator (virtual-reality simulator score; p < 0.001). Conclusion: The motion analysis system could discriminate between different levels of experience. Automatic feedback on correct movements during self-directed training on simulators might help new bronchoscopists learn how to handle the bronchoscope like an expert.

    OriginalsprogEngelsk
    Sider (fra-til)155-161
    Antal sider7
    TidsskriftRespiration
    Vol/bind89
    Udgave nummer2
    DOI
    StatusUdgivet - 6 mar. 2015

    Fingeraftryk Udforsk hvilke forskningsemner 'Assessment of competence in simulated flexible bronchoscopy using motion analysis' indeholder.

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