Structured and Modular Training Pathway for Robot-assisted Radical Prostatectomy (RARP): Validation of the RARP Assessment Score and Learning Curve Assessment.
BACKGROUND
Use of robot-assisted radical prostatectomy (RARP) for prostate cancer is increasing. Structured surgical training and objective assessment are critical for outcomes.


OBJECTIVE
To develop and validate a modular training and assessment pathway via Healthcare Failure Mode and Effect Analysis (HFMEA) for trainees undertaking RARP and evaluate learning curves (LCs) for procedural steps.


DESIGN, SETTING, AND PARTICIPANTS
This multi-institutional (Europe, Australia, and United States) observational prospective study used HFMEA to identify the high-risk steps of RARP. A specialist focus group enabled validation. Fifteen trainees who underwent European Association of Urology robotic surgery curriculum training performed RARP and were assessed by mentors using the tool developed. Results produced LCs for each step. A plateau above score 4 indicated competence.


OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS
We used a modular training and assessment tool (RARP Assessment Score) to evaluate technical skills. LCs were constructed. Multivariable Kruskal-Wallis, Mann-Whitney U, and κ coefficient analyses were used.


RESULTS AND LIMITATIONS
Five surgeons were observed for 42 console hours to map steps of RARP. HFMEA identified 84 failure modes and 46 potential causes with a hazard score ≥8. Content validation created the RARP Assessment Score: 17 stages and 41 steps. The RARP Assessment Score was acceptable (56.67%), feasible (96.67%), and had educational impact (100%). Fifteen robotic surgery trainees were assessed for 8 mo. In 426 RARP cases (range: 4-79), all procedural steps were attempted by trainees. Trainees were assessed with the RARP Assessment Score by their expert mentors, and LCs for individual steps were plotted. LCs demonstrated plateaus for anterior bladder neck transection (16 cases), posterior bladder neck transection (18 cases), posterior dissection (9 cases), dissection of prostatic pedicle and seminal vesicles (15 cases), and anastomosis (17 cases). Other steps did not plateau during data collection.


CONCLUSIONS
The RARP Assessment Score based on HFMEA methodology identified critical steps for focused RARP training and assessed surgeons. LCs demonstrate the experience necessary to reach a level of competence in technical skills to protect patients.


PATIENT SUMMARY
We developed a safety and assessment tool to gauge the technical skills of surgeons performing robot-assisted radical prostatectomy. Improvement was monitored, and measures of progress can be used in future to guide mentors when training surgeons to operate safely.
['Lovegrove|Catherine|C|', 'Novara|Giacomo|G|', 'Mottrie|Alex|A|', 'Guru|Khurshid A|KA|', 'Brown|Matthew|M|', 'Challacombe|Ben|B|', 'Popert|Richard|R|', 'Raza|Johar|J|', 'Van der Poel|Henk|H|', 'Peabody|James|J|', 'Dasgupta|Prokar|P|', 'Ahmed|Kamran|K|']
D001315:Australia D002983:Clinical Competence D003479:Curriculum D004503:Education, Medical, Graduate D004521:Educational Measurement D004522:Educational Status D005060:Europe D006801:Humans D059032:Learning Curve D016014:Linear Models D008137:Longitudinal Studies D008297:Male D008611:Mentors D015999:Multivariate Analysis D011446:Prospective Studies D011468:Prostatectomy D015203:Reproducibility of Results D065287:Robotic Surgical Procedures D013647:Task Performance and Analysis D013663:Teaching D014481:United States
Training Robot-assisted radical prostatectomy Assessment Learning curve Patient safety