title: VR-based training and assessment in ultrasound-guided regional anesthesia: from error analysis to system design.
abstract: If VR-based medical training and assessment is to improve patient care and safety (i.e. a genuine health gain), it has to be based on clinically relevant measurement of performance. Metrics on errors are particularly useful for capturing and correcting undesired behaviors before they occur in the operating room. However, translating clinically relevant metrics and errors into meaningful system design is a challenging process. This paper discusses how an existing task and error analysis was translated into the system design of a VR-based training and assessment environment for Ultrasound Guided Regional Anesthesia (UGRA).
authors.affiliation: National Digital Research Centre, Ireland. eriklovquist@gmail.com
authors.forename: Erik
authors.initials: E
authors.lastname: Lövquist
authors.forename: Owen
authors.initials: O
authors.lastname: O'Sullivan
authors.forename: Donnchadh
authors.initials: D
authors.lastname: Oh'Ainle
authors.forename: Graham
authors.initials: G
authors.lastname: Baitson
authors.forename: George
authors.initials: G
authors.lastname: Shorten
authors.forename: Nick
authors.initials: N
authors.lastname: Avis
mesh_terms: D000765:Anesthesia, Conduction / Q000295:instrumentation / Q000379:methods*; D000776:Anesthesiology / Q000193:education*; D000777:Anesthetics / Q000008:administration & dosage; D003198:Computer Simulation; D003194:Computer-Assisted Instruction / Q000379:methods*; D006801:Humans; D007267:Injections / Q000295:instrumentation / Q000379:methods*; D008954:Models, Biological; D009339:Needles; D013663:Teaching / Q000379:methods; D018084:Ultrasonography, Interventional / Q000379:methods*; D014584:User-Computer Interface
chemical_list: D000777:Anesthetics