Development and validation of a comprehensive program of education and assessment of the basic fundamentals of laparoscopic surgery

Peters, Jeffrey H.; Fried, Gerald M.; Swanström, Lee L.; Soper, Nathaniel J.; Sillin, Lelan F.; Schirmer, Bruce D.; Hoffman, Kaaren I.

doi:10.1016/s0039-6060(03)00156-9

Cited by 573 publications

(316 citation statements)

References 7 publications

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“…The surgical tasks recorded for this study were based on a set of previously validated laparoscopic training tasks [8][9][10][11]. The participant used a grasper instrument (Ethicon Endo-Surgery, Inc., 4545 Creek Road, Cincinnati, OH, USA) in the left hand and a needle driver (Karl Storz Endoscopy-America, Inc., 600 Corporate Pointe, Culver City, CA, USA) in the right hand, operating in a standard training box.…”

Section: Evaluation Tasksmentioning

confidence: 99%

Support vector machines improve the accuracy of evaluation for the performance of laparoscopic training tasks

et al. 2009

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Background Despite technological advances in the tracking of surgical motions, automatic evaluation of laparoscopic skills remains remote. A new method is proposed that combines multiple discrete motion analysis metrics. This new method is compared with previously proposed metric combination methods and shown to provide greater ability for classifying novice and expert surgeons. Methods For this study, 30 participants (four experts and 26 novices) performed 696 trials of three training tasks: peg transfer, pass rope, and cap needle. Instrument motions were recorded and reduced to four metrics. Three methods of combining metrics into a prediction of surgical competency (summed-ratios, z-score normalization, and support vector machine [SVM]) were compared. The comparison was based on the area under the receiver operating characteristic curve (AUC) and the predictive accuracy with a previously unseen validation data set. Results For all three tasks, the SVM method was superior in terms of both AUC and predictive accuracy with the validation set. The SVM method resulted in AUCs of 0.968, 0.952, and 0.970 for the three tasks compared respectively with 0.958, 0.899, and 0.884 for the next best method (weighted z-normalization). The SVM method correctly predicted 93.7, 91.3, and 90.0% of the subjects' competencies, whereas the weighted z-normalization respectively predicted 86.6, 79.3, and 75.7% accurately (p \ 0.002). Conclusions The findings show that an SVM-based analysis provides more accurate predictions of competency at laparoscopic training tasks than previous analysis techniques. An SVM approach to competency evaluation should be considered for computerized laparoscopic performance evaluation systems.

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Section: Evaluation Tasksmentioning

confidence: 99%

Support vector machines improve the accuracy of evaluation for the performance of laparoscopic training tasks

et al. 2009

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“…This particular issue highlights the importance of training and credentialing that should be in place with any new technology and, in many ways, it echoes the issues involved in the transvaginal mesh debacle. In 2004, the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) launched the validated Fundamentals of Laparoscopic Surgery (FLS) curriculum and, together with the American College of Surgeons (ACS), promoted the FLS as a minimum standard before a surgeon should be allowed to perform laparoscopic procedures independently [2]. Similarly, expert robotic surgeons and numerous surgical societies and certifying organizations have advocated the need for the creation of a unified approach and standardized curriculum for basic training and certification in robotic surgery skills.…”

Section: The Presentmentioning

confidence: 99%

Patents running out: time to take stock of robotic surgery

O’Reilly

2014

Int Urogynecol J

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“…51 These box trainers have been studied and validated extensively and have progressed into the Fundamentals of Laparoscopic Surgery training course and evaluation system (FLS). 52 Box trainers do not instantly provide feedback on performance. Therefore, educators (most often experienced surgeons) must evaluate skill parameters when using a box trainer.…”

Section: Box Trainersmentioning

confidence: 99%

“…The FLS includes educational material, mechanisms for assessment, and a didactic instruction. 52 Within the FLS, five training modules are combined, including peg transfer, pattern cutting, ligating loop, and intracorporeal and extracorporeal knot tying. 48,49 The FLS exam is a combination of a written exam and a timed and scored laparoscopic skills evaluation in the box trainer.…”

Section: 36mentioning

confidence: 99%

Mapping the Maze of Minimally Invasive Surgery Simulators

Empel

Veer

Rijssen

et al. 2012

Journal of Laparoendoscopic & Advanced Surgical Techniques

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Background: Conforming to, among other considerations, legal and ethical concerns for patient safety, there is an increasing demand to assess a surgeon's skills prior to performance in the operating room in pursuit of higherquality treatment. Training in minimally invasive surgery (MIS) must therefore be intensified, including team training. New methods to train and assess minimally invasive surgical skills are gaining interest. The goal of this review is to provide instructors with an overview of available MIS training tools. In this review, we discuss currently available simulators for MIS training. Applicability, validity, and construction of simulators are reviewed. Also, some of the leading training programs and assessment methods in MIS are reviewed. Methods: A literature search was performed on studies evaluating surgical task performance on a simulator, reviewing satisfaction with laparoscopic training programs, or validating simulators or assessment methods. Results: Simulators may be divided into simple box trainers and computer-based systems, such as virtual and augmented simulators. All have advantages and disadvantages. An overview is provided of currently available training systems, validity, trainee assessment, and the importance of training programs in MIS. Conclusions:No simulator yet provides the ability to train the entire set of required psychomotor skills or procedures for MIS. A multiyear training program combining various simulators for multiple-level training, including team training, should be constructed.

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Development and validation of a comprehensive program of education and assessment of the basic fundamentals of laparoscopic surgery

Cited by 573 publications

References 7 publications

Support vector machines improve the accuracy of evaluation for the performance of laparoscopic training tasks

Support vector machines improve the accuracy of evaluation for the performance of laparoscopic training tasks

Patents running out: time to take stock of robotic surgery

Mapping the Maze of Minimally Invasive Surgery Simulators

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