Robotic Surgery Readiness (RSR): A Prospective Randomized Skills Decay Recognition and Prevention Study
Technical Report,15 Jul 2016,14 Jul 2017
University of Washington Seattle United States
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Preliminary research has demonstrated that surgical warm-up, either on virtual reality VR simulator or reality-based module, can improve surgical performance, yet metrics to identify and counteract skills decay are not readily available to provide targeted curricula. We will establish performance signatures of Robotic Surgery Readiness RSR through tasks on the da Vinci robotic virtual reality simulator, testing the role intervals of inactivity have on task performance. These will be used to develop a simulation curriculum that brings the inactive surgeon to RSR. AIM 1 We are nearing the end of recruitment for AIM 1 with 2840 completed subjects. Another 8 subjects have reached proficiency and are in their trial sessions. The recruitment has taken longer than anticipated due to challenging clinic rotations schedules and deployments for some subjects. Data analysis cannot commence until all 40 subjects are complete, yet data upload standardization processes are established. AIM 2 We have settled on the most optimal method for extracting kinematic and video data from the da Vinci for Aim 2 using the intuitive dVLogger system which captures these data directly from the API of the robot, thus standardizing the method for capture. The work flow has been tested at two sites and is being optimized. We have not recruited the subjects for AIM 2, yet, pending completion of recruitment in Aim 1. Data analysis Pending completion of Aim 1 trial sessions.
- Medicine and Medical Research