1. Robotic performance metrics model fellow proficiency in living donor nephrectomy.
- Author
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Davidson JT 4th, Clanahan JM, Kiani A, Vachharajani N, Yu J, Martens GR, Cullinan DR, Hill AL, Olumba F, Matson SC, Scherer MD, Doyle MBM, Wellen JR, and Khan AS
- Subjects
- Humans, Female, Male, Kidney Transplantation methods, Kidney Transplantation education, Middle Aged, Adult, Benchmarking, Fellowships and Scholarships, Nephrectomy methods, Nephrectomy education, Robotic Surgical Procedures education, Robotic Surgical Procedures methods, Living Donors, Clinical Competence
- Abstract
We investigated the use of robotic objective performance metrics (OPM) to predict number of cases to proficiency and independence among abdominal transplant fellows performing robot-assisted donor nephrectomy (RDN). 101 RDNs were performed by 5 transplant fellows from September 2020 to October 2023. OPM included fellow percent active control time (%ACT) and handoff counts (HC). Proficiency was defined as ACT ≥ 80% and HC ≤ 2, and independence as ACT ≥ 99% and HC ≤ 1. Case number was significantly associated with increasing fellow %ACT, with proficiency estimated at 14 cases and independence at 32 cases (R
2 = 0.56, p < 0.001). Similarly, case number was significantly associated with decreasing HC, with proficiency at 18 cases and independence at 33 cases (R2 = 0.29, p < 0.001). Case number was not associated with total active console time (p = 0.91). Patient demographics, operative characteristics, and outcomes were not associated with OPM, except for donor estimated blood loss (EBL), which positively correlated with HC. Abdominal transplant fellows demonstrated proficiency at 14-18 cases and independence at 32-33 cases. Total active console time remained unchanged, suggesting that increasing fellow autonomy does not impede operative efficiency. These findings may serve as a benchmark for training abdominal transplant surgery fellows independently and safely in RDN., (© 2024. The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.)- Published
- 2024
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