Visual Cueing with Context Relevant Information for Reducing Change Blindness
| Autor: | Brad Slavin, Joanne Lim, Jacqueline Marie Tappan, Rollin Brant, J. Mark Ansermino, Jeremy Daniels |
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| Rok vydání: | 2009 |
| Předmět: |
Male
medicine.medical_specialty genetic structures Health Informatics Context (language use) Critical Care and Intensive Care Medicine Task (project management) Physical medicine and rehabilitation Anesthesiology Monitoring Intraoperative Intensive care Task Performance and Analysis Computer Graphics Reaction Time medicine Humans Anesthesia Computer Simulation Computer vision Poisson Distribution Sensory cue Monitoring Physiologic business.industry Reproducibility of Results Anesthesiology and Pain Medicine Visual Perception Physiological monitoring Visual cueing Change blindness Female sense organs Artificial intelligence Cues business Psychology Relevant information |
| Zdroj: | Journal of Clinical Monitoring and Computing. 23:223-232 |
| ISSN: | 1573-2614 1387-1307 |
| Popis: | Physiological monitoring is a requisite for optimal care to ensure that the condition of a patient is maintained within safe levels. Monitoring can be jeopardized by the inability of a clinician to recognize important changes in the visual display of data throughout the duration of the monitoring task. We hypothesized that the addition of a visual cue imparting contextual information to a physiological display would improve the detection ability and response time of a clinician to a change in a patient variable.Contextual information based on trend information was added to a physiological display in the form of a visual cue. Following IRB approval, the resulting enhanced display was evaluated by 22 anesthesiologists in a simulated operating room, through the observation of six simulated scenarios using a standard anesthesia display and the enhanced display. Demographic information, response time, accuracy of detection, and usability data were collected.The enhanced display reduced the detection time to a change in the simulated scenarios by 14.4 s (95% CI: -26.4 to -2.38), and reduced the expected number of missed events per scenario by 0.23 (95% CI: -0.439 to -0.0203), based on the repeated measures analysis (Poisson model).The data collected and analyzed in this study supports the addition of a visual cue to future physiological monitors. The graphic representation and the context relevant information that it transmits appears to aid clinicians. While the results indicate that enhanced visualization of context relevant information can lead to a significant improvement in event recognition and identification, further evaluation in clinical settings is required. |
| Databáze: | OpenAIRE |
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