Literature DB >> 16784940

Simulators in catheter-based interventional radiology: training or computer games?

D A Gould1, D O Kessel, A E Healey, S J Johnson, W E Lewandowski.   

Abstract

Training in interventional radiology (IR) relies on a traditional apprenticeship; to protect patients, expert supervision is mandatory until knowledge, attitudes and practical skills have been certified as satisfactory. However, the current quality of IR training is threatened by reduced time for trainees to learn, as well as a loss of basic diagnostic, training cases to non-invasive imaging. At the same time, IR techniques are becoming a focus of interest to a range of other clinical specialities. To address this training shortfall there is a need to develop novel training alternatives such as simulator models. Few simulator models in any medical field have been successfully validated to show improved clinical skills in treating patients. To date no endovascular simulator has met this standard. A good simulator must be based around key performance measures (metrics) derived from careful analysis of the procedure to be replicated. Metrics can be determined by trained psychologists from a direct analysis of the content of the job or task to be tested. The identification of these critical measures of performance is a complex process which must be tailored to a training curriculum to be effective. Simulators based on flawed metrics will invariably lead to unsatisfactory assessment. It follows that simulator development must involve the statutory licensing authorities. Equally it is essential that we do not assume that training on a particular simulator will correlate with the ability to perform the task in the real world. This "transfer of training" must be rigorously proven by validation studies.

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Year:  2006        PMID: 16784940     DOI: 10.1016/j.crad.2006.01.013

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  6 in total

1.  Using simulation for interventional radiology training.

Authors:  D Gould
Journal:  Br J Radiol       Date:  2010-07       Impact factor: 3.039

2.  An augmented reality simulator for ultrasound guided needle placement training.

Authors:  D Magee; Y Zhu; R Ratnalingam; P Gardner; D Kessel
Journal:  Med Biol Eng Comput       Date:  2007-07-26       Impact factor: 2.602

3.  Improving education on C-arm operation and radiation protection with a computer-based training and simulation system.

Authors:  Oliver Johannes Bott; Markus Wagner; Christopher Duwenkamp; Nils Hellrung; Klaus Dresing
Journal:  Int J Comput Assist Radiol Surg       Date:  2009-05-13       Impact factor: 2.924

4.  Assessment of surgical skills of trainees in the UK.

Authors:  Jonathan D Beard
Journal:  Ann R Coll Surg Engl       Date:  2008-05       Impact factor: 1.891

5.  Endovascular image-guided interventions (EIGIs).

Authors:  Stephen Rudin; Daniel R Bednarek; Kenneth R Hoffmann
Journal:  Med Phys       Date:  2008-01       Impact factor: 4.071

6.  Do Video Games Predict an Early Advanced Capacity to Learn Interventional Radiology Skills?

Authors:  Caleb Busch; Austin Fehr; Aaron Rohr; Brandon Custe; Zachary Collins
Journal:  J Med Educ Curric Dev       Date:  2021-02-04
  6 in total

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