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J Surg Educ. 2019 Jan - Feb;76(1):201-214. doi: 10.1016/j.jsurg.2018.06.026. Epub 2018 Aug 8.

Objective Assessment of the Early Stages of the Learning Curve for the Senhance Surgical Robotic System.

Author information

1
Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina. Electronic address: andrew.hutchins@duke.edu.
2
Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina; Department of Surgery, Duke University Medical Center, Durham, North Carolina.
3
Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina.
4
Department of Surgery, Duke University Medical Center, Durham, North Carolina.
5
Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina.

Abstract

OBJECTIVE:

The purpose of this research is to study the early stages of the Senhance learning curve to report how force feedback impacts learning rate. This serves as an exploratory investigation into assumptions that fellows and faculty will adjust faster to the Senhance in comparison with residents, and that force feedback will not hinder skill acquisition.

DESIGN:

In this study, participants completed the peg transfer and precision cutting task from the Fundamentals of Laparoscopic Surgery (FLS) manual skills assessment five times each using the Senhance while instrument motion was tracked.

SETTING:

This study took place in the Surgical Education and Activities Laboratory at Duke University Medical Center.

PARTICIPANTS:

Participants for this study were residents, fellows, and faculty from Duke University Medical Center in general surgery and gynecology specialties (N = 16).

RESULTS:

Postulated linear mixed effects models with participant level random effects showed significant improvement with additional attempts for the peg transfer task after adjusting for surgical experience and force feedback respectively for the primary FLS score metric. The secondary metric of total instrument path length also showed improvement (significant decreases) in path length with additional attempts after respectively adjusting for surgical experience and force feedback.

CONCLUSIONS:

This study investigates the early stages of the learning curve of the Senhance. Exploratory modeling indicates that residents, fellows, and faculty surgeons rapidly adapt to the controls of the Senhance regardless of experience level and force feedback engagement. The results from this study may serve as motivation for future prospective studies that achieve sufficient statistical power with a larger sample size and strict experimental design.

KEYWORDS:

Fundamentals of Laparoscopic Surgery; Learning Curve; Medical Knowledge; Motion Tracking; Practice-Based Learning and Improvement; Robotic Surgery; Surgical Skill Transfer; Systems-Based Practice

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