Virtual Reality Training Improves Operating Room Performance

Seymour, Neal E.; Gallagher, Anthony G.; Roman, Sanziana A.; O’Brien, Michael; Bansal, Vipin; Andersen, Dana K.; Satava, Richard M.

doi:10.1097/00000658-200210000-00008

Cited by 2,473 publications

(1,555 citation statements)

References 11 publications

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“…Our data support prior work showing that procedural skills that are poor at baseline can be increased significantly using simulation-based training and deliberate practice. [11][12][13][14][15][16][17][18]28 This report on CVC insertion adds to the growing body of literature showing that simulation training complements standard medical education, [11][12][13][14][15][16][17][18][19]28 and expands the clinical application of the mastery model beyond thoracentesis and ACLS. 11,12 Use of the mastery model described in this study also has important implications for patients.…”

Section: Discussionmentioning

confidence: 99%

“…9,10 We previously used simulation-based mastery learning to improve the thoracentesis and advanced cardiac life support (ACLS) skills of internal medicine residents. 11,12 Although a few small studies have linked simulation-based interventions to improved quality of care, [13][14][15][16][17][18][19] more work is needed to show that results from a simulated environment transfer to actual patient care.…”

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confidence: 99%

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Use of simulation‐based mastery learning to improve the quality of central venous catheter placement in a medical intensive care unit

McGaghie

Cohen

Balachandran

et al. 2009

Journal of Hospital Medicine

351

272

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Disclosure: The authors have no financial or other potential conflicts of interest.BACKGROUND: Central venous catheter (CVC) insertions are performed frequently by internal medicine residents.Complications, including arterial puncture and pneumothorax, decrease when operators use fewer needle passes to insert the CVC. In this study, we evaluated the effect of simulation-based mastery learning on CVC insertion skill. DESIGN:This was a cohort study of internal jugular (IJ) and subclavian (SC) CVC insertions by 41 internal medicine residents rotating through the medical intensive care unit (MICU) over a five-month period. Thirteen traditionallytrained residents were surveyed about the number of needle passes, complications, and procedural self-confidence on CVCs inserted in the MICU. Concurrently, 28 residents completed simulation-based training in IJ and SC CVC insertions. Simulator-trained residents were expected to perform CVC insertions to mastery standards on a central line simulator. Simulator-trained residents then rotated through the MICU and were surveyed regarding CVC placement. The impact of simulation training was assessed by comparing group survey results. Central venous catheter (CVC) insertions are commonly performed at the bedside in medical intensive care unit (MICU) settings. Internal medicine residents are required to demonstrate knowledge regarding CVC indications, complications, and sterile technique, 1 and often perform the procedure during training. Education in CVC insertion is needed because many internal medicine residents are uncomfortable performing this procedure. 2 CVC insertion also carries the risk of potentially life-threatening complications including infection, pneumothorax, arterial puncture, deep vein thrombosis, and bleeding. Education and training may also contribute to improved patient care because increased physician experience with CVC insertion reduces complication risk. 3,4 Similarly, a higher number of needle passes or attempts during CVC insertion correlates with mechanical complications such as pneumothorax or arterial punctures. 4-8 Pneumothorax rates for internal jugular (IJ) CVCs have been reported to range from 0% to 0.2% and for subclavian (SC) CVCs from 1.5% to 3.1%. 4,5 The arterial puncture rate for IJ CVCs ranges from 5.0% to 9.4% and for SC CVCs from 3.1% to 4.9%. 4,5 Proper use of ultrasound to assist with IJ CVC insertion has been shown to decrease these mechanical complications. 4,5 However, studies of ultrasound use with SC CVC insertion have mixed results. 4 Simulation-based training has been used in medical education to increase knowledge, provide opportunities for deliberate and safe practice, and shape the development of RESULTS: Journal of Hospital Medicine Vol 4 No 7 September 2009 397clinical skills. 9,10 We previously used simulation-based mastery learning to improve the thoracentesis and advanced cardiac life support (ACLS) skills of internal medicine residents. 11,12 Although a few small studies have linked simulation-based interventions to imp...

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Use of simulation‐based mastery learning to improve the quality of central venous catheter placement in a medical intensive care unit

McGaghie

Cohen

Balachandran

et al. 2009

Journal of Hospital Medicine

351

272

View full text Add to dashboard Cite

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“…To quote [8]; "The benefits of endoscopic training through computer simulation, rather than the traditionally performed one-to-one apprenticeship schemes, are now well accepted in the community" (although supervised practice is still an essential part of training). Such training has been successfully validated [9,10]. Similarly simulators for various teleoperated procedures, such as eye procedures [11], and arthroscopy (including haptic feedback elements) [12][13][14] are available.…”

Section: Introductionmentioning

confidence: 99%

An augmented reality simulator for ultrasound guided needle placement training

et al. 2007

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Details of a low cost augmented-reality system for the simulation of ultrasound guided needle insertion procedures (tissue biopsy, abscess drainage, nephrostomy etc.) for interventional radiology education is presented. The system comprises physical elements; a mannequin, an ultrasound probe and a needle, and software elements; generating virtual ultrasound anatomy and allowing data collection. These two elements are linked by a pair of magnetic 3D position sensors. Virtual anatomy, for image generation, is generated based on full body CT scans of live humans. Details of the novel aspects of this system are presented including; image generation, registration and calibration.

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“…(VR)-based [2,3], optical (LapVR; Immersion Medical, 55 W. Watkins Mill Road, Gaithersburg, MD, USA), and magnetic [4] tracking systems have provided surgeons and their residents with copious data. Thus, although substantial kinematic data are available to judge the competency of a surgeon's performance, distilling useful automated feedback from this information remains difficult.…”

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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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Virtual Reality Training Improves Operating Room Performance

Cited by 2,473 publications

References 11 publications

Use of simulation‐based mastery learning to improve the quality of central venous catheter placement in a medical intensive care unit

Use of simulation‐based mastery learning to improve the quality of central venous catheter placement in a medical intensive care unit

An augmented reality simulator for ultrasound guided needle placement training

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

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