Training Surgical Residents With a Haptic Robotic Central Venous Catheterization Simulator

Pepley, David F.; Gordon, Adam; Yovanoff, Mary; Mirkin, Katelin A.; Miller, Scarlett R.; Han, David C.; Moore, Jason Z.

doi:10.1016/j.jsurg.2017.06.003

Cited by 24 publications

(30 citation statements)

References 32 publications

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“…size and depth of the vessels) and through haptic feedback provided through a robotic arm that simulates force changes of different types of tissues (e.g. skin, adipose tissue, vessel), see Pepley et al for full details 9,10 . The DHRT also provides learners with automated feedback on their mechanical performance after each needle insertion attempt without the need of a trained preceptor, including feedback on the number of insertion attempts, average angle of insertion, and the final distance of the needle tip from the center of the vein 11 .…”

Section: Introductionmentioning

confidence: 99%

Looks can be deceiving: Gaze pattern differences between novices and experts during placement of central lines

Chen

Sonntag

Pepley

et al. 2019

The American Journal of Surgery

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Background: The objective of this study was to determine whether gaze patterns could differentiate expertise during simulated ultrasound-guided Internal Jugular Central Venous Catheterization (US-IJCVC) and if expert gazes were different between simulators of varying functional and structural fidelity. Methods: A 2017 study compared eye gaze patterns of expert surgeons (n=11), senior residents (n=4), and novices (n=7) during CVC needle insertions using the dynamic haptic robotic trainer (DHRT), a system which simulates US-IJCVC. Expert gaze patterns were also compared between a manikin and the DHRT. Results: Expert gaze patterns were consistent between the manikin and DHRT environments (p = 0.401). On the DHRT system, CVC experience significantly impacted the percent of time participants spent gazing at the ultrasound screen (p < 0.0005) and the needle and ultrasound probe (p < 0.0005). Conclusion: Gaze patterns differentiate expertise during ultrasound-guided CVC placement and the fidelity of the simulator does not impact gaze patterns.

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Section: Introductionmentioning

confidence: 99%

Looks can be deceiving: Gaze pattern differences between novices and experts during placement of central lines

Chen

Sonntag

Pepley

et al. 2019

The American Journal of Surgery

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“…Although this robotic system is not currently available on the market, our team is working to duplicate and commercialize this patent-pending system. The detailed costs of the system can be found in Pepley et al 19 Lastly, this study focused performance on training simulators, but did not examine skill transfer. Future work will focus on the effect of training in these robotic simulators on central line placement in clinical settings through an on-going longitudinal study in the surgical intensive care unit.…”

Section: Resultsmentioning

confidence: 99%

“…Calculated performance scores are generated based on several variables, including average angle of insertion, distance to center of vein, puncturing the back wall penalties, and more, see Pepley et al for more details. 19 Although previous research has indicated that even experts may have a low ability or no ability to judge their own skill performance, 31–33 providing individuals with feedback during training may improve their ability to accurately assess their own performance. 34 Thus, it was hypothesized that there would be a weak positive correlation between self-ratings of trial performance and scores generated by the DHRT system.…”

Section: Methodsmentioning

confidence: 99%

“…18 Finally, prior work by the authors has shown that participants improved their performance throughout the course of training on the DHRT system and they approached the level of an expert at the end of their training. 19 An advantage of using functionally high-fidelity simulators like the DHRT for IJ CVC trainings is that they can be designed to automatically present feedback in both textual and graphical forms which can improve information retention. 20 For example, the DHRT system provides users with feedback after each insertion trial on the needle angle, final position of the needle tip, number of insertions, and amount of unnecessary movements, see Yovanoff et al 21 for discussion.…”

Section: Introductionmentioning

confidence: 99%

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Investigating the Effect of Simulator Functional Fidelity and Personalized Feedback on Central Venous Catheterization Training

Yovanoff

Chen

Pepley

et al. 2018

Journal of Surgical Education

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OBJECTIVE To compare the effect of simulator functional fidelity (manikin vs a Dynamic Haptic Robotic Trainer [DHRT]) and personalized feedback on surgical resident self-efficacy and self-ratings of performance during ultrasound-guided internal jugular central venous catheterization (IJ CVC) training. In addition, we seek to explore how self-ratings of performance compare to objective performance scores generated by the DHRT system. DESIGN Participants were randomly assigned to either manikin or DHRT IJ CVC training over a 6-month period. Self-efficacy surveys were distributed before and following training. Training consisted of a pretest, 22 practice IJ CVC needle insertion attempts, 2 full-line practice attempts, and a posttest. Participants provided self-ratings of performance for each needle insertion and were presented with feedback from either an upper level resident (manikin) or a personalized learning system (DHRT). SETTING A study was conducted from July 2016 to February 2017 through a surgical skills training program at Hershey Medical Center in Hershey, Pennsylvania. PARTICIPANTS Twenty-six first-year surgical residents were recruited for the study. Individuals were informed that IJ CVC training procedures would be consistent regardless of participation in the study and that participation was optional. All recruited residents opted to participate in the study. RESULTS Residents in both groups significantly improved their self-efficacy scores from pretest to posttest (p < 0.01). Residents in the manikin group consistently provided higher self-ratings of performance (p < 0.001). Residents in the DHRT group recorded more feedback on errors (228 instances) than the manikin group (144 instances). Self-ratings of performance on the DHRT system were able to significantly predict the objective score of the DHRT system (R2 = 0.223, p < 0.001). CONCLUSION Simulation training with the DHRT system and the personalized learning feedback can improve resident self-efficacy with IJ CVC procedures and provide sufficient feedback to allow residents to accurately assess their own performance.

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“…A baseline profile was used for the first and last needle insertion during each of the three robotic training sessions. This baseline scenario was used in a previous study which showed that the robotic trained novices in the 2016 residency cohort showed significant improvement in performance between the first and last needle insertion – which were both the baseline 27 . The manikin training condition was used in a larger study to compare the effectiveness of the DHRT system and current manikin simulators 18 and thus will not be considered for this study.…”

Section: Methodsmentioning

confidence: 99%

Can Haptic Simulators Distinguish Expert Performance? A Case Study in Central Venous Catheterization in Surgical Education

Chen¹,

Yovanoff²,

Pepley³

et al. 2019

Sim Healthcare

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Introduction: High-tech simulators are gaining popularity in surgical training programs due to their potential for improving clinical outcomes. However, most simulators are static in nature and only represent a single anatomical patient configuration. The Dynamic Haptic Robotic Training (DHRT) system was developed to simulate these diverse patient anatomies during Central Venous Catheterization (CVC) training. This paper explores the use of the DHRT system to evaluate objective metrics for CVC insertion by comparing the performance of experts and novices. Methods: Eleven expert surgeons and thirteen first-year surgical residents (novices) performed multiple needle insertion trials on the DHRT system. Differences between experts and novices on performance on 5 metrics were assessed using a MANOVA: path length (PL), standard deviation of deviations (SDoD), average velocity (AV), distance to the center of the vessel (DtCV), and time to complete (TtC) the needle insertion. A regression analysis was performed to identify if expertise could be predicted using these metrics. Then, a curve fit was conducted to identify if learning curves were present for experts or novices on any of these five metrics. Results: TtC the insertion and SDoD of the needle tip from an ideal path were significantly different between experts and novices. Learning curves were not present for experts, but indicated a significant decrease in PL and TtC for novices. Conclusion: The DHRT system was able to identify significant differences in TtC and SDoD between experts and novices during CVC needle insertion procedures. In addition, novices were shown to improve their skills through DHRT training.

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Training Surgical Residents With a Haptic Robotic Central Venous Catheterization Simulator

Cited by 24 publications

References 32 publications

Looks can be deceiving: Gaze pattern differences between novices and experts during placement of central lines

Looks can be deceiving: Gaze pattern differences between novices and experts during placement of central lines

Investigating the Effect of Simulator Functional Fidelity and Personalized Feedback on Central Venous Catheterization Training

Can Haptic Simulators Distinguish Expert Performance? A Case Study in Central Venous Catheterization in Surgical Education

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