Current Standards for Training in Robot-assisted Surgery and Endourology: A Systematic Review.

Endourology Metrics Proficiency-based progression Robotics Simulation Training

Journal

European urology
ISSN: 1873-7560
Titre abrégé: Eur Urol
Pays: Switzerland
ID NLM: 7512719

Informations de publication

Date de publication:
20 Apr 2024
Historique:
received: 05 01 2024
revised: 25 03 2024
accepted: 08 04 2024
medline: 22 4 2024
pubmed: 22 4 2024
entrez: 21 4 2024
Statut: aheadofprint

Résumé

Different training programs have been developed to improve trainee outcomes in urology. However, evidence on the optimal training methodology is sparse. Our aim was to provide a comprehensive description of the training programs available for urological robotic surgery and endourology, assess their validity, and highlight the fundamental elements of future training pathways. We systematically reviewed the literature using PubMed/Medline, Embase, and Web of Science databases. The validity of each training model was assessed. The methodological quality of studies on metrics and curricula was graded using the MERSQI scale. The level of evidence (LoE) and level of recommendation for surgical curricula were awarded using the educational Oxford Centre for Evidence-Based Medicine classification. A total of 75 studies were identified. Many simulators have been developed to aid trainees in mastering skills required for both robotic and endourology procedures, but only four demonstrated predictive validity. For assessment of trainee proficiency, we identified 18 in robotics training and six in endourology training; however, the majority are Likert-type scales. Although proficiency-based progression (PBP) curricula demonstrated superior outcomes to traditional training in preclinical settings, only four of six (67%) in robotics and three of nine (33%) in endourology are PBP-based. Among these, the Fundamentals of Robotic Surgery and the SIMULATE curricula have the highest LoE (level 1b). The lack of a quantitative synthesis is the main limitation of our study. Training curricula that integrate simulators and PBP methodology have been introduced to standardize trainee outcomes in robotics and endourology. However, evidence regarding their educational impact remains restricted to preclinical studies. Efforts should be made to expand these training programs to different surgical procedures and assess their clinical impact. Simulation-based training and programs in which progression is based on proficiency represent the new standard of quality for achieving surgical proficiency in urology. Studies have demonstrated the educational impact of these approaches. However, there are still no standardized training pathways for several urology procedures.

Sections du résumé

BACKGROUND AND OBJECTIVE OBJECTIVE
Different training programs have been developed to improve trainee outcomes in urology. However, evidence on the optimal training methodology is sparse. Our aim was to provide a comprehensive description of the training programs available for urological robotic surgery and endourology, assess their validity, and highlight the fundamental elements of future training pathways.
METHODS METHODS
We systematically reviewed the literature using PubMed/Medline, Embase, and Web of Science databases. The validity of each training model was assessed. The methodological quality of studies on metrics and curricula was graded using the MERSQI scale. The level of evidence (LoE) and level of recommendation for surgical curricula were awarded using the educational Oxford Centre for Evidence-Based Medicine classification.
KEY FINDINGS AND LIMITATIONS UNASSIGNED
A total of 75 studies were identified. Many simulators have been developed to aid trainees in mastering skills required for both robotic and endourology procedures, but only four demonstrated predictive validity. For assessment of trainee proficiency, we identified 18 in robotics training and six in endourology training; however, the majority are Likert-type scales. Although proficiency-based progression (PBP) curricula demonstrated superior outcomes to traditional training in preclinical settings, only four of six (67%) in robotics and three of nine (33%) in endourology are PBP-based. Among these, the Fundamentals of Robotic Surgery and the SIMULATE curricula have the highest LoE (level 1b). The lack of a quantitative synthesis is the main limitation of our study.
CONCLUSIONS AND CLINICAL IMPLICATIONS CONCLUSIONS
Training curricula that integrate simulators and PBP methodology have been introduced to standardize trainee outcomes in robotics and endourology. However, evidence regarding their educational impact remains restricted to preclinical studies. Efforts should be made to expand these training programs to different surgical procedures and assess their clinical impact.
PATIENT SUMMARY RESULTS
Simulation-based training and programs in which progression is based on proficiency represent the new standard of quality for achieving surgical proficiency in urology. Studies have demonstrated the educational impact of these approaches. However, there are still no standardized training pathways for several urology procedures.

Identifiants

pubmed: 38644144
pii: S0302-2838(24)02304-2
doi: 10.1016/j.eururo.2024.04.008
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Auteurs

Giuseppe Basile (G)

Department of Urology, Fundació Puigvert, Barcelona, Spain; Department of Urology, IRCCS San Raffaele Hospital, Milan, Italy. Electronic address: basile.giuseppe@hsr.it.

Andrea Gallioli (A)

Department of Urology, Fundació Puigvert, Barcelona, Spain; Department of Surgery, Autonomous University of Barcelona, Bellaterra, Spain.

Pietro Diana (P)

Department of Urology, Fundació Puigvert, Barcelona, Spain; Department of Surgery, Autonomous University of Barcelona, Bellaterra, Spain; Department of Urology, Humanitas Clinical and Research Institute IRCCS, Rozzano, Italy.

Anthony Gallagher (A)

Faculty of Medicine, KU Leuven, Leuven, Belgium; Faculty of Health and Life Sciences, Ulster University, Coleraine, UK; ORSI Academy, Melle, Belgium.

Alessandro Larcher (A)

Department of Urology, IRCCS San Raffaele Hospital, Milan, Italy.

Markus Graefen (M)

Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany.

Nina Harke (N)

Department of Urology, Hannover Medical School, Hannover, Germany.

Olivier Traxer (O)

Department of Urology, Sorbonne University, Tenon Hospital, AP-HP, Paris, France.

Derya Tilki (D)

Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany; Department of Urology, University Hospital Hamburg-Eppendorf, Hamburg, Germany; Department of Urology, Koc University Hospital, Istanbul, Turkey.

Henk Van Der Poel (H)

Department of Urology, Netherlands Cancer Institute, Amsterdam, The Netherlands.

Esteban Emiliani (E)

Department of Urology, Fundació Puigvert, Barcelona, Spain.

Oriol Angerri (O)

Department of Urology, Fundació Puigvert, Barcelona, Spain.

Christian Wagner (C)

Prostate Center Northwest, Department of Urology, Pediatric Urology and Uro-Oncology, St. Antonius-Hospital, Gronau, Germany.

Francesco Montorsi (F)

Department of Urology, IRCCS San Raffaele Hospital, Milan, Italy.

Peter Wiklund (P)

Icahn School of Medicine, Mount Sinai Health System New York City, NY, USA; Department of Urology, Karolinska Institutet, Stockholm, Sweden.

Bhaskar Somani (B)

Department of Urology, University Hospital Southampton NHS Trust, Southampton, UK.

Nicolò Buffi (N)

Department of Urology, Humanitas Clinical and Research Institute IRCCS, Rozzano, Italy.

Alex Mottrie (A)

ORSI Academy, Melle, Belgium; Department of Urology, OLV Hospital, Aalst, Belgium.

Evangelos Liatsikos (E)

Department of Urology, University of Patras, Patras, Greece.

Alberto Breda (A)

Department of Urology, Fundació Puigvert, Barcelona, Spain; Department of Surgery, Autonomous University of Barcelona, Bellaterra, Spain.

Classifications MeSH