Tailored Feedback Based on Clinically Relevant Performance Metrics Expedites the Acquisition of Robotic Suturing Skills-An Unblinded Pilot Randomized Controlled Trial

PURPOSE: Previously, we identified 8 objective suturing performance metrics highly predictive of urinary continence recovery after robotic-assisted radical prostatectomy. Here, we aimed to test the feasibility of providing tailored feedback based upon these clinically relevant metrics and explore the impact on the acquisition of robotic suturing skills.

MATERIALS AND METHODS: Training surgeons were recruited and randomized to a feedback group or a control group. Both groups completed a baseline, midterm and final dry laboratory vesicourethral anastomosis (VUA) and underwent 4 intervening training sessions each, consisting of 3 suturing exercises. Eight performance metrics were recorded during each exercise: 4 automated performance metrics (derived from kinematic and system events data of the da Vinci® Robotic System) representing efficiency and console manipulation competency, and 4 suturing technical skill scores. The feedback group received tailored feedback (a visual diagram+verbal instructions+video examples) based on these metrics after each session. Generalized linear mixed model was used to compare metric improvement (Δ) from baseline to the midterm and final VUA.

RESULTS: Twenty-three participants were randomized to the feedback group (11) or the control group (12). Demographic data and baseline VUA metrics were comparable between groups. The feedback group showed greater improvement than the control group in aggregate suturing scores at midterm (mean Δ feedback group 4.5 vs Δ control group 1.1) and final VUA (Δ feedback group 5.3 vs Δ control group 4.9). The feedback group also showed greater improvement in the majority of the included metrics at midterm and final VUA.

CONCLUSIONS: Tailored feedback based on specific, clinically relevant performance metrics is feasible and may expedite the acquisition of robotic suturing skills.

Errataetall:

CommentIn: J Urol. 2022 Aug;208(2):422-423. - PMID 35576149

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:208

Enthalten in:

The Journal of urology - 208(2022), 2 vom: 03. Aug., Seite 414-424

Sprache:

Englisch

Beteiligte Personen:

Ma, Runzhuo [VerfasserIn]
Lee, Ryan S [VerfasserIn]
Nguyen, Jessica H [VerfasserIn]
Cowan, Andrew [VerfasserIn]
Haque, Taseen F [VerfasserIn]
You, Jonathan [VerfasserIn]
Roberts, Sidney I [VerfasserIn]
Cen, Steven [VerfasserIn]
Jarc, Anthony [VerfasserIn]
Gill, Inderbir S [VerfasserIn]
Hung, Andrew J [VerfasserIn]

Links:

Volltext

Themen:

Clinical competence
Education, medical
Formative feedback
Journal Article
Randomized Controlled Trial
Research Support, N.I.H., Extramural
Robotics

Anmerkungen:

Date Completed 15.07.2022

Date Revised 15.07.2022

published: Print-Electronic

CommentIn: J Urol. 2022 Aug;208(2):422-423. - PMID 35576149

Citation Status MEDLINE

doi:

10.1097/JU.0000000000002691

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM339240326