Ahmad Guni1, Nicholas Raison2, Ben Challacombe3, Shamim Khan4, Prokar Dasgupta4, Kamran Ahmed4. 1. GKT School of Medical Education, King's College London, Guy's Campus, St. Thomas Street, London, UK. 2. Division of Transplantation Immunology & Mucosal Biology, Faculty of Life Sciences & Medicine, Guy's Hospital, MRC Centre for Transplantation, King's College London, London, UK. nicholas.raison@kcl.ac.uk. 3. Department of Urology, Guy's and St Thomas', NHS Trust, London, UK. 4. Division of Transplantation Immunology & Mucosal Biology, Faculty of Life Sciences & Medicine, Guy's Hospital, MRC Centre for Transplantation, King's College London, London, UK.
Abstract
BACKGROUND: With the increased use of simulation for surgical training, there is a need for objective forms of assessment to evaluate trainees. The Global Evaluative Assessment of Robotic Skills (GEARS) is widely used for assessing skills in robotic surgery, but there are no recognised checklist scoring systems. This study aimed to develop a checklist for suturing in robotic surgery. METHODS: A suturing checklist for needle driving and knot tying was constructed following evaluation of participants performing urethrovesical anastomoses. Key procedural steps were identified from expert videos, while assessing novice videos allowed identification of common technical errors. 22 novice and 13 expert videos were marked on needle driving, while 18 novices and 10 experts were assessed on knot tying. Validation of the finalised checklist was performed with the assessment of 39 separate novices by an expert surgeon and compared to GEARS scoring. RESULTS: The internal consistency of the preliminary checklist was high (Cronbach's alpha = 0.870 for needle driving items; 0.736 for knot tying items), and after removal of poorly correlating items, the final checklist contained 23 steps. Both the needle driving and knot tying categories discriminated between novices and experts, p < 0.005. While the GEARS score demonstrated construct validity for needle driving, it could not significantly differentiate between novices and experts for knot tying, p = 0.286. The needle driving category significantly correlated with the corresponding GEARS scores (rs = 0.613, p < 0.005), but the correlation for knot tying was insignificant (rs = 0.296, p = 0.127). The pilot data indicates the checklist significantly correlated with the GEARS score (p < 0.005). CONCLUSION: This study reports the development of a valid assessment tool for suturing in robotic surgery. Given that checklists are simple to use, there is significant scope for this checklist to be used in surgical training.
BACKGROUND: With the increased use of simulation for surgical training, there is a need for objective forms of assessment to evaluate trainees. The Global Evaluative Assessment of Robotic Skills (GEARS) is widely used for assessing skills in robotic surgery, but there are no recognised checklist scoring systems. This study aimed to develop a checklist for suturing in robotic surgery. METHODS: A suturing checklist for needle driving and knot tying was constructed following evaluation of participants performing urethrovesical anastomoses. Key procedural steps were identified from expert videos, while assessing novice videos allowed identification of common technical errors. 22 novice and 13 expert videos were marked on needle driving, while 18 novices and 10 experts were assessed on knot tying. Validation of the finalised checklist was performed with the assessment of 39 separate novices by an expert surgeon and compared to GEARS scoring. RESULTS: The internal consistency of the preliminary checklist was high (Cronbach's alpha = 0.870 for needle driving items; 0.736 for knot tying items), and after removal of poorly correlating items, the final checklist contained 23 steps. Both the needle driving and knot tying categories discriminated between novices and experts, p < 0.005. While the GEARS score demonstrated construct validity for needle driving, it could not significantly differentiate between novices and experts for knot tying, p = 0.286. The needle driving category significantly correlated with the corresponding GEARS scores (rs = 0.613, p < 0.005), but the correlation for knot tying was insignificant (rs = 0.296, p = 0.127). The pilot data indicates the checklist significantly correlated with the GEARS score (p < 0.005). CONCLUSION: This study reports the development of a valid assessment tool for suturing in robotic surgery. Given that checklists are simple to use, there is significant scope for this checklist to be used in surgical training.
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