Abstract
Patient safety is a critical area of concern within healthcare and medical errors are a well-known problem that can have fatal ramifications (Kohn et al. 2000). Lack of knowledge and skill with clinical tasks and procedures, as well as decision-making can be significant factors with many of the errors that are reported in healthcare (Zhang et al. 2002). Many healthcare tasks can be simulated using computer and web technology for training purposes and provide trainees (students and practicing) with a way to improve or maintain their knowledge and skills (Persson et al. 2014; Cant & Cooper 2014). The concept of visual attention during a task has been tested in medical and healthcare task studies (O’Meara et al. 2015; Zheng et al. 2011; Breen et al. 2014) with an aim of finding discriminative differences between competency levels. The study of this previous work led us to hypothesise that eye tracking metrics exclusively have a relationship with specific task performance and can discriminate between performance level. We found the duty of patient monitoring with interpreting vital signs monitors in nursing earmarked in the literature for improvement in available simulation-based training. We sought to use eye-tracking with the task of nurses interpreting simulated patient vital signs from a monitor. The objective was to determine if eye-tracking technology can be used to develop biometrics for automatically classifying the performance of nurses whilst they interact with computer-based simulations.
Original language | English |
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Title of host publication | Unknown Host Publication |
Publisher | Cambridge Environmental Research Consultants |
Number of pages | 4 |
Publication status | Published (in print/issue) - 1 Sept 2016 |
Event | Collaborative European Research Conference - Cork Duration: 1 Sept 2016 → … |
Conference
Conference | Collaborative European Research Conference |
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Period | 1/09/16 → … |
Keywords
- Eye tracking
- human-computer interaction
- patient safety
- clinical decision making
- vital signs
- simulation based assessment