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Use of eye tracking in analyzing distribution of visual attention among critical care nurses in daily professional life: an observational study.
- Source :
- Journal of Clinical Monitoring & Computing; Dec2021, Vol. 35 Issue 6, p1511-1518, 8p
- Publication Year :
- 2021
-
Abstract
- Patient safety is a priority in healthcare, yet it is unclear how sources of errors should best be analyzed. Eye tracking is a tool used to monitor gaze patterns in medicine. The aim of this study was to analyze the distribution of visual attention among critical care nurses performing non-simulated, routine patient care on invasively ventilated patients in an ICU. ICU nurses were tracked bedside in daily practice. Eight specific areas of interest were pre-defined (respirator, drug preparation, medication, patient data management system, patient, monitor, communication and equipment/perfusors). Main independent variable and primary outcome was dwell time, secondary outcomes were hit ratio, revisits, fixation count and average fixation time on areas of interest in a targeted tracking-time of 60 min. 28 ICU nurses were analyzed and the average tracking time was 65.5 min. Dwell time was significantly higher for the respirator (12.7% of total dwell time), patient data management system (23.7% of total dwell time) and patient (33.4% of total dwell time) compared to the other areas of interest. A similar distribution was observed for fixation count (respirator 13.3%, patient data management system 25.8% and patient 31.3%). Average fixation time and revisits of the respirator were markedly elevated. Apart from the respirator, average fixation time was highest for the patient data management system, communication and equipment/perfusors. Eye tracking is helpful to analyze the distribution of visual attention of critical care nurses. It demonstrates that the respirator, the patient data management system and the patient form cornerstones in the treatment of critically ill patients. This offers insights into complex work patterns in critical care and the possibility of improving work flows, avoiding human error and maximizing patient safety. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13871307
- Volume :
- 35
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Journal of Clinical Monitoring & Computing
- Publication Type :
- Academic Journal
- Accession number :
- 153186682
- Full Text :
- https://doi.org/10.1007/s10877-020-00628-2