A review of 45 publications on objective computer-aided technical skill evaluation (OCASE-T) found that most studies are simulation-based with highly varied algorithms and validation methodologies.
Highlights the need for future research in objective computer-aided technical skill evaluation to emphasize competency assessment in the operating room and validation against patient outcomes.
Training skillful and competent surgeons is critical to ensure high quality of care and to minimize disparities in access to effective care. Traditional models to train surgeons are being challenged by rapid advances in technology, an intensified patient-safety culture, and a need for value-driven health systems. Simultaneously, technological developments are enabling capture and analysis of large amounts of complex surgical data. These developments are motivating a "surgical data science" approach to objective computer-aided technical skill evaluation (OCASE-T) for scalable, accurate assessment; individualized feedback; and automated coaching. We define the problem space for OCASE-T and summarize 45 publications representing recent research in this domain. We find that most studies on OCASE-T are simulation based; very few are in the operating room. The algorithms and validation methodologies used for OCASE-T are highly varied; there is no uniform consensus. Future research should emphasize competency assessment in the operating room, validation against patient outcomes, and effectiveness for surgical training.
Vedula et al. (Tue,) conducted a review in Surgical technical skill evaluation (n=45). Objective computer-aided technical skill evaluation (OCASE-T) was evaluated. A review of 45 publications on objective computer-aided technical skill evaluation (OCASE-T) found that most studies are simulation-based with highly varied algorithms and validation methodologies.