A novel method for training residents in robotic hysterectomy

Validation of a Simulation Model for Robotic Myomectomy

STUDY OBJECTIVE

Several simulation models have been evaluated for gynecologic procedures such as hysterectomy, but there are limited published data for myomectomy. This study aimed to assess the validity of a low-cost robotic myomectomy model for surgical simulation training.

DESIGN

Prospective cohort simulation study.

SETTING

Surgical simulation laboratory.

PARTICIPANTS

Twelve obstetrics and gynecology residents and 4 fellowship-trained minimally invasive gynecologic surgeons were recruited for a 3:1 novice-to-expert ratio.

INTERVENTIONS

A robotic myomectomy simulation model was constructed using <$5 worth of materials: a foam cylinder, felt, a stress ball, bandage wrap, and multipurpose sealing wrap. Participants performed a simulation task involving 2 steps: fibroid enucleation and hysterotomy repair. Video-recorded performances were timed and scored by 2 blinded reviewers using the validated Global Evaluative Assessment of Robotic Skills (GEARS) scale (5-25 points) and a modified GEARS scale (5-40 points), which adds 3 novel domains specific to robotic myomectomy. Performance was also scored using predefined task errors. Participants completed a post-task questionnaire assessing the model's realism and utility.

MEASUREMENTS AND MAIN RESULTS

Median task completion time was shorter for experts than novices (9.7 vs 24.6 min, p = .001). Experts scored higher than novices on both the GEARS scale (median 23 vs 12, p = .004) and modified GEARS scale (36 vs 20, p = .004). Experts made fewer task errors than novices (median 15.5 vs 37.5, p = .034). For interrater reliability of scoring, the intraclass correlation coefficient was calculated to be 0.91 for the GEARS assessment, 0.93 for the modified GEARS assessment, and 0.60 for task errors. Using the contrasting groups method, the passing mark for the simulation task was set to a minimum modified GEARS score of 28 and a maximum of 28 errors. Most participants agreed that the model was realistic (62.5%) and useful for training (93.8%).

CONCLUSION

We have demonstrated evidence supporting the validity of a low-cost robotic myomectomy model. This simulation model and the performance assessments developed in this study provide further educational tools for robotic myomectomy training.

[DeRAS I-German situation of robotic-assisted surgery-an online survey]

Hintergrund

Die robotische Assistenz hat sich in der Chirurgie etabliert, ist aber noch kein Standard. Der aktuelle Stand der klinischen Verbreitung in Deutschland ist weiter unklar. Industrieunabhängige Quellen sind rar.

Ziel der Arbeit

Ziel dieser Umfrage ist es, den aktuellen Stand der robotisch assistierten Chirurgie (RAS) fachübergreifend in Deutschland im Zeitraum von 2014 bis 2018 zu untersuchen.

Materialien und Methoden

Mit einer Internetrecherche wurden Krankenhäuser (KH) und Fachabteilungen (FA) mit Zugang zur RAS identifiziert. Die FA wurden aufgefordert, ihre Daten aus den Jahren 2014 bis 2018 zu teilen. Neben klinischen Daten wurden Daten zu Nutzung, Implementierung, Training und Finanzierung abgefragt.

Ergebnisse

Am 31.12.2018 wurde die RAS an 121 KH in Deutschland angeboten. 383 FA mit Zugang zur RAS wurden identifiziert. 26 % (n = 98) der FA haben geantwortet. Im Mittel verfügte jede FA über zwei Konsolenchirurgen. 10 % der KH verfügten über mehr als 1 RAS-System. 100 % der erfassten RAS-Systeme stammten von der Firma Intuitive Surgical Inc., CA, USA. Die RAS wurde zu 65 % in der Urologie implementiert, zu 12 % in der Viszeralchirurgie (VC). 21 % der Programme erfolgten interdisziplinär und 4 % multidisziplinär (> 3). 83 % der Systeme wurden gekauft, 17 % anderweitig finanziert. Bei den Operationsmehrkosten gaben 74 % der Kliniken an, diese selbst zu tragen. 14 % wählten eine Umlage. Seit 2014 steigerten sich die Eingriffe um den Faktor 4 auf ca. 8000. Der Anteil der VC steigerte sich um das Fünffache seit 2016.

Schlussfolgerung

Die RAS erlebte in Deutschland bis 2018 ein starkes Wachstum. Das Eingriffsspektrum entspricht dem der Laparoskopie. Bei aktuell fehlender Kostenerstattung für den technischen Mehraufwand, wird die RAS überwiegend im mittel- und hochkomplexen Bereich eingesetzt. Der Online-Survey ist eine gute Methode, ohne hohen administrativen Aufwand unabhängige Daten zu erheben.

Virtual reality robotic surgery simulation curriculum to teach robotic suturing: a randomized controlled trial

The objective of this randomized, controlled trial was to assess whether voluntary participation in a proctored, proficiency-based, virtual reality robotic suturing curriculum using the da Vinci(®) Skills Simulator™ improves robotic suturing performance. Residents and attending surgeons were randomized to participation or non-participation during a 5 week training curriculum. Robotic suturing skills were evaluated before and after training using an inanimate vaginal cuff model, which participants sutured for 10 min using the da Vinci(®) Surgical System. Performances were videotaped, anonymized, and subsequently graded independently by three robotic surgeons. 27 participants were randomized. 23 of the 27 completed both the pre- and post-test, 13 in the training group and 10 in the control group. Mean training time in the intervention group was 238 ± 136 min (SD) over the 5 weeks. The primary outcome (improvement in GOALS+ score) and the secondary outcomes (improvement in GEARS, total knots, satisfactory knots, and the virtual reality suture sponge 1 task) were significantly greater in the training group than the control group in unadjusted analysis. After adjusting for lower baseline scores in the training group, improvement in the suture sponge 1 task remained significantly greater in the training group and a trend was demonstrated to greater improvement in the training group for the GOALS+ score, GEARS score, total knots, and satisfactory knots.

Validation of a novel virtual reality simulator for robotic surgery

Objective. With the increase in robotic-assisted laparoscopic surgery there is a concomitant rising demand for training methods. The objective was to establish face and construct validity of a novel virtual reality simulator (dV-Trainer, Mimic Technologies, Seattle, WA) for the use in training of robot-assisted surgery. Methods. A comparative cohort study was performed. Participants (n = 42) were divided into three groups according to their robotic experience. To determine construct validity, participants performed three different exercises twice. Performance parameters were measured. To determine face validity, participants filled in a questionnaire after completion of the exercises. Results. Experts outperformed novices in most of the measured parameters. The most discriminative parameters were “time to complete” and “economy of motion” (P < 0.001). The training capacity of the simulator was rated 4.6 ± 0.5 SD on a 5-point Likert scale. The realism of the simulator in general, visual graphics, movements of instruments, interaction with objects, and the depth perception were all rated as being realistic. The simulator is considered to be a very useful training tool for residents and medical specialist starting with robotic surgery. Conclusions. Face and construct validity for the dV-Trainer could be established. The virtual reality simulator is a useful tool for training robotic surgery.

Trainee performance at robotic console and benchmark operative times

INTRODUCTION AND HYPOTHESIS

It is an ongoing challenge to maintain surgical efficiency while integrating trainee participation. We hypothesize that a program of graduated surgical responsibility for trainees does not hinder operative efficiency.

METHODS

This was a retrospective cohort study of trainee performance times, collected prospectively in real time, for robotic cases performed at one university hospital between September 2008 and August 2011. The primary aim was to compare overall operative times between cases performed by trainees versus attendings. Secondary aims were to compare operative times for major portions of each operation by level of training and to establish benchmark operative times for trainees.

RESULTS

During the study period, 98 cases had recorded trainee performance times. Total robot docked time was longer for trainees than for attendings (155 vs 132 min, p = 0.011), but mean performance times for hysterectomy (70 vs 59 min, p = 0.096) and sacrocolpopexy (76 vs 79 min, p = 0.545) were similar. Within the trainees, there was no correlation between surgical time and rank for each step of the procedures. Utilizing mean performance times for all trainees, benchmark operative times were established for each step of hysterectomy in minutes: right side (21), left side (21), bladder flap (10), colpotomy (15), and cuff closure (19); similarly, for sacrocolpopexy: sacral and peritoneal dissection (12), anterior cuff dissection (10), posterior cuff dissection (8), anterior mesh attachment (15), posterior mesh attachment (18), sacral mesh attachment (12), and peritoneal closure (9).

CONCLUSION

In a program of graduated surgical responsibility, robotic operative efficiency was comparable when trainees were involved as console surgeons.

Training and learning robotic surgery, time for a more structured approach: a systematic review

BACKGROUND

Robotic assisted laparoscopic surgery is growing rapidly and there is an increasing need for a structured approach to train future robotic surgeons.

OBJECTIVES

To review the literature on training and learning strategies for robotic assisted laparoscopic surgery.

SEARCH STRATEGY

A systematic search of MEDLINE, EMBASE, the Cochrane Library and the Journal of Robotic Surgery was performed.

SELECTION CRITERIA

We included articles concerning training, learning, education and teaching of robotic assisted laparoscopic surgery in any specialism.

DATA COLLECTION AND ANALYSIS

Two authors independently selected articles to be included. We categorised the included articles into: training modalities, learning curve, training future surgeons, curriculum design and implementation.

MAIN RESULTS

We included 114 full text articles. Training modalities such as didactic training, skills training (dry lab, virtual reality, animal or cadaver models), case observation, bedside assisting, proctoring and the mentoring console can be used for training in robotic assisted laparoscopic surgery. Several training programmes in general and specific programmes designed for residents, fellows and surgeons are described in the literature. We provide guidelines for development of a structured training programme.

AUTHORS' CONCLUSIONS

Robotic surgical training consists of system training and procedural training. System training should be formally organised and should be competence based, instead of time based. Virtual reality training will play an import role in the near future. Procedural training should be organised in a stepwise approach with objective assessment of each step. This review aims to facilitate and improve the implementation of structured robotic surgical training programmes.