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Br J Anaesth ; 121(3): 662-671, 2018 Sep.
Article in English | MEDLINE | ID: mdl-30115265

ABSTRACT

BACKGROUND: Maintaining situation awareness of monitored patients can be challenging because care providers must continually read and integrate multiple waveforms and numerical vital sign values into a mental model of the patient's situation. We developed and evaluated a technology designed to improve perception of vital sign information by presenting patient status as an animated patient avatar. METHODS: After step-wise improvement of the avatar, anaesthesia professionals from two hospitals participated in a comparative study of conventional monitoring. Participants observed identical monitoring scenarios via the two technologies for brief time intervals and afterwards recalled patient status. RESULTS: Overall, 150 anaesthesia professionals participated in the validation process and 32 participated in the comparative study, completing 128 scenarios, which allowed for 64 direct comparisons. The avatar's inter-rater reliability was high, with Fleiss' kappa of 0.98 (95% confidence interval 0.96-0.99, P<0.001). With the avatar, participants recalled almost twice as many vital signs correctly as with conventional monitoring (9 vs 5, P<0.001). Perceived confidence was improved (2=certain vs 1=uncertain, P<0.001) and perceived workload lowered (task load index 60 vs 76, P<0.001). Participants obtained these results only after watching an educational video explaining the avatar and suggesting quick learnability and potential for real-life usability. CONCLUSIONS: This study provides empirical evidence that an animated avatar offers the opportunity to transmit vital sign information significantly more quickly than conventional monitoring and with improved confidence and reduced cognitive effort. This could help care providers gain situation awareness more efficiently.


Subject(s)
Anesthesia, General/methods , Awareness , Computer Graphics , Monitoring, Intraoperative/methods , Vital Signs/physiology , Adult , Anesthesia, General/standards , Clinical Competence , Diagnosis, Computer-Assisted/methods , Female , Humans , Male , Monitoring, Intraoperative/standards , Observer Variation , User-Computer Interface , Workload/statistics & numerical data
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