The impact of rater training on the psychometric properties of standardized surgical skill assessment tools

2020 ◽  
Vol 220 (3) ◽  
pp. 610-615 ◽  
Author(s):  
Reagan L. Robertson ◽  
Jason Park ◽  
Lawrence Gillman ◽  
Ashley Vergis
Author(s):  
Tora Rydtun Haug ◽  
Mai-Britt Worm Ørntoft ◽  
Danilo Miskovic ◽  
Lene Hjerrild Iversen ◽  
Søren Paaske Johnsen ◽  
...  

Abstract Background In laparoscopic colorectal surgery, higher technical skills have been associated with improved patient outcome. With the growing interest in laparoscopic techniques, pressure on surgeons and certifying bodies is mounting to ensure that operative procedures are performed safely and efficiently. The aim of the present review was to comprehensively identify tools for skill assessment in laparoscopic colon surgery and to assess their validity as reported in the literature. Methods A systematic search was conducted in EMBASE and PubMed/MEDLINE in May 2021 to identify studies examining technical skills assessment tools in laparoscopic colon surgery. Available information on validity evidence (content, response process, internal structure, relation to other variables, and consequences) was evaluated for all included tools. Results Fourteen assessment tools were identified, of which most were procedure-specific and video-based. Most tools reported moderate validity evidence. Commonly not reported were rater training, assessment correlation with variables other than training level, and validity reproducibility and reliability in external educational settings. Conclusion The results of this review show that several tools are available for evaluation of laparoscopic colon cancer surgery, but few authors present substantial validity for tool development and use. As we move towards the implementation of new techniques in laparoscopic colon surgery, it is imperative to establish validity before surgical skill assessment tools can be applied to new procedures and settings. Therefore, future studies ought to examine different aspects of tool validity, especially correlation with other variables, such as patient morbidity and pathological reports, which impact patient survival.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joël L. Lavanchy ◽  
Joel Zindel ◽  
Kadir Kirtac ◽  
Isabell Twick ◽  
Enes Hosgor ◽  
...  

AbstractSurgical skills are associated with clinical outcomes. To improve surgical skills and thereby reduce adverse outcomes, continuous surgical training and feedback is required. Currently, assessment of surgical skills is a manual and time-consuming process which is prone to subjective interpretation. This study aims to automate surgical skill assessment in laparoscopic cholecystectomy videos using machine learning algorithms. To address this, a three-stage machine learning method is proposed: first, a Convolutional Neural Network was trained to identify and localize surgical instruments. Second, motion features were extracted from the detected instrument localizations throughout time. Third, a linear regression model was trained based on the extracted motion features to predict surgical skills. This three-stage modeling approach achieved an accuracy of 87 ± 0.2% in distinguishing good versus poor surgical skill. While the technique cannot reliably quantify the degree of surgical skill yet it represents an important advance towards automation of surgical skill assessment.


2007 ◽  
Vol 6 (2) ◽  
pp. 188-191 ◽  
Author(s):  
Sharif Al-Ruzzeh ◽  
Shishir Karthik ◽  
David O'Regan

Ophthalmology ◽  
2011 ◽  
Vol 118 (2) ◽  
pp. 427-427.e5 ◽  
Author(s):  
Karl C. Golnik ◽  
Hilary Beaver ◽  
Vinod Gauba ◽  
Andrew G. Lee ◽  
Eduardo Mayorga ◽  
...  

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