TY - JOUR
T1 - Training Modalities in Robot-assisted Urologic Surgery
T2 - A Systematic Review
AU - Lovegrove, Catherine Elizabeth
AU - Elhage, Oussama
AU - Khan, M Shamim
AU - Novara, Giacomo
AU - Mottrie, Alex
AU - Dasgupta, Prokar
AU - Ahmed, Kamran
N1 - Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.
PY - 2017/2
Y1 - 2017/2
N2 - CONTEXT: Novel surgical techniques demand that surgical training adapts to the need for technical and nontechnical skills.OBJECTIVE: To identify training methods available for robot-assisted surgical (RAS) training in urology, evaluate their effectiveness in terms of validation, educational impact, acceptability, and cost effectiveness, and assess their effect on learning curves (LCs).EVIDENCE ACQUISITION: A systematic review following Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines searched Ovid Medline, Embase, PsycINFO, and the Cochrane Library. Results were screened to include appropriate studies. Quality was evaluated. Each method was evaluated, and conclusions were drawn regarding LCs.EVIDENCE SYNTHESIS: Of 359 records, 24 were included (521 participants). Training methods included dry-lab training (n=7), wet-lab training (n=7), mentored training (n=7), and nonstructured pathways (n=5). Dry-lab training demonstrated educational impact by reducing console time and was acceptable in a study; 100% of participants confirmed face validity. Wet-lab training principally uses human cadaveric material; effectiveness is well rated, although dry-lab training and observation were rated as equally useful. Mentored programmes combine lectures, tutorials, observation, simulation, and proctoring. Minifellowships were linked to greater practice of RAS 1 yr later. LCs vary according to experience. One study found that surgeons from robot-related fellowships demonstrated fewer positive surgical margins than surgeons from laparoscopic-related fellowships (24% vs 34.6%; p=0.05) and reduced time (132 vs 152min; p=0.0003). Five studies examined nonstructured training pathways (clinical practice). Experience correlated with fewer complications (p=0.007), improved continence (p=0.049), and reduced time (p=0.002).CONCLUSIONS: RAS training methods include dry and wet lab, mentored training, and nonstructured pathways. Limited available evidence suggests that they affect LCs differently and are rarely used alone. The different methods of training appear effective when combined. Their benefits must be explored to facilitate validated acceptable training with educational impact.PATIENT SUMMARY: Robot-assisted training encompasses several methods used in combination, but more evidence is required to gain the greatest benefit and formulate future training pathways.
AB - CONTEXT: Novel surgical techniques demand that surgical training adapts to the need for technical and nontechnical skills.OBJECTIVE: To identify training methods available for robot-assisted surgical (RAS) training in urology, evaluate their effectiveness in terms of validation, educational impact, acceptability, and cost effectiveness, and assess their effect on learning curves (LCs).EVIDENCE ACQUISITION: A systematic review following Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines searched Ovid Medline, Embase, PsycINFO, and the Cochrane Library. Results were screened to include appropriate studies. Quality was evaluated. Each method was evaluated, and conclusions were drawn regarding LCs.EVIDENCE SYNTHESIS: Of 359 records, 24 were included (521 participants). Training methods included dry-lab training (n=7), wet-lab training (n=7), mentored training (n=7), and nonstructured pathways (n=5). Dry-lab training demonstrated educational impact by reducing console time and was acceptable in a study; 100% of participants confirmed face validity. Wet-lab training principally uses human cadaveric material; effectiveness is well rated, although dry-lab training and observation were rated as equally useful. Mentored programmes combine lectures, tutorials, observation, simulation, and proctoring. Minifellowships were linked to greater practice of RAS 1 yr later. LCs vary according to experience. One study found that surgeons from robot-related fellowships demonstrated fewer positive surgical margins than surgeons from laparoscopic-related fellowships (24% vs 34.6%; p=0.05) and reduced time (132 vs 152min; p=0.0003). Five studies examined nonstructured training pathways (clinical practice). Experience correlated with fewer complications (p=0.007), improved continence (p=0.049), and reduced time (p=0.002).CONCLUSIONS: RAS training methods include dry and wet lab, mentored training, and nonstructured pathways. Limited available evidence suggests that they affect LCs differently and are rarely used alone. The different methods of training appear effective when combined. Their benefits must be explored to facilitate validated acceptable training with educational impact.PATIENT SUMMARY: Robot-assisted training encompasses several methods used in combination, but more evidence is required to gain the greatest benefit and formulate future training pathways.
KW - Dry lab
KW - Mentorship
KW - Robot-assisted surgery
KW - Simulation
KW - Training
KW - Wet lab
U2 - 10.1016/j.euf.2016.01.006
DO - 10.1016/j.euf.2016.01.006
M3 - Review article
C2 - 28720354
SN - 2405-4569
VL - 3
SP - 102
EP - 116
JO - European Urology Focus
JF - European Urology Focus
IS - 1
ER -