The virtual reality transurethral prostatic resection trainer: evaluation of discriminate validity

Rashid, Hani H., Kowalewski, Timothy, Oppenheimer, Peter, Ooms, Ann, Krieger, John N. and Sweet, Robert M. (2007) The virtual reality transurethral prostatic resection trainer: evaluation of discriminate validity. The Journal of Urology, 177(6), pp. 2283-2286. ISSN (print) 0022-5347

Official URL: http://dx.doi.org/doi:10.1016/j.juro.2007.01.120

Abstract

PURPOSE: To understand how urologists acquire resection skills we analyzed factors correlating with favorable resection metrics in groups defined as experts, residents and novices. We then evaluated discriminate validity by determining factors correlating with proficiency among individuals in the expert, resident and novice groups. MATERIALS AND METHODS: A total of 136 subjects completed the protocol, including 72 urologists, 45 residents and 19 novices. After a pre-task questionnaire and training video subjects performed a standardized 5-minute resection task. Primary metrics were gm resected, blood loss, irrigant volume used, foot pedal use and differential time spent with orientation, cutting or coagulation. RESULTS: Among experts larger resection correlated with more time spent cutting (p <0.001). In contrast, increased coagulation time correlated with gm resected in the novice group (p = 0.001). The number of transurethral prostate resections that residents reported having done in the real operating room correlated with gm resected (p = 0.043), use of more irrigating fluid (p = 0.024) and less time spent coagulating (p = 0.027) on the simulator. In residents and experts exclusively primary resection efficiency metrics, fluid use and blood loss correlated with cuts at tissue and correlated inversely with coagulation and orientation time (p <0.05). CONCLUSIONS: Different factors determine transurethral prostate resection performance metrics among experts, residents and novices. These correlations reinforce discriminate validity and provide insight into specific factors that likely determine success at different training levels. Such data could be used to isolate and train skill subsets in the curriculum and they may elucidate the safest and most efficient approach to train resection skills.

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