Failure mode and effects analysis in designing a virtual reality-based training simulator for bilateral sagittal split osteotomy
Article first published online: 18 JAN 2013
Copyright © 2013 John Wiley & Sons, Ltd.
The International Journal of Medical Robotics and Computer Assisted Surgery
Volume 9, Issue 1, pages e1–e9, March 2013
How to Cite
Sofronia, R. E., Knott, T., Davidescu, A., Savii, G. G., Kuhlen, T. and Gerressen, M. (2013), Failure mode and effects analysis in designing a virtual reality-based training simulator for bilateral sagittal split osteotomy. Int. J. Med. Robotics Comput. Assist. Surg., 9: e1–e9. doi: 10.1002/rcs.1483
- Issue published online: 6 MAR 2013
- Article first published online: 18 JAN 2013
- Manuscript Accepted: 11 DEC 2012
- virtual reality;
- medical simulators;
- orthognathic surgery;
- bilateral sagittal split osteotomy;
- system design;
- error analysis
Virtual reality-based simulators offer a cost-effective and efficient alternative to traditional medical training and planning. Developing a simulator that enables the training of medical skills and also supports recognition of errors made by the trainee is a challenge. The first step in developing such a system consists of error identification in the real procedure, in order to ensure that the training environment covers the most significant errors that can occur. This paper focuses on identifying the main system requirements for an interactive simulator for training bilateral sagittal split osteotomy (BSSO).
An approach is proposed based on failure mode and effects analysis (FMEA), a risk analysis method that is well structured and already an approved technique in other domains.
Based on the FMEA results, a BSSO training simulator is currently being developed, which centres upon the main critical steps of the procedure (sawing and splitting) and their main errors.
FMEA seems to be a suitable tool in the design phase of developing medical simulators. Herein, it serves as a communication medium for knowledge transfer between the medical experts and the system developers. The method encourages a reflective process and allows identification of the most important elements and scenarios that need to be trained. Copyright © 2013 John Wiley & Sons, Ltd.