JMIR Publications

ABSTRACT

Background:

In a previous study, we were able to show that a visualization technology that represents the patient's status as an animated patient avatar improves the perception of patient status in anesthesia staff. In the study reported here, we tested whether the patient avatar could also help anesthetists to monitor patients with the peripheral field of vision. Since anesthetists look directly at the patient monitors only for about 5% of the time during anesthesia cases, using peripheral vision would provide a possibility to maintain patient monitoring during the time when care providers do not have the patient monitor in direct sight, meaning in sharp or foveal vision, but only in the peripheral field of vision.

Objective:

We conducted this study to compare participants’ performance in recognizing changes in patient status with peripheral vision using the avatar-based monitoring technology and a high-fidelity simulation of a conventional patient monitoring interface.

Methods:

We conducted a comparative study in which anesthesiologists with their peripheral field of vision looked at patient monitoring scenarios and tried to identify changes in patient status. To assure the best possible experimental conditions we used an eye-tracker, which recorded the eye movements of the subjects and confirmed that they really only looked at the monitoring scenarios with their peripheral vision.

Results:

Thirty subjects evaluated 18 different patient status changes with each technology (avatar and conventional patient monitoring). With conventional patient monitoring, subjects could only detect those three changes in patient status that are associated with a change in the auditory display, i.e., pulse tone, tachycardia (faster beeping), bradycardia (slower beeping) and desaturation (lower pitch of beeping). With the avatar, the median number of detected vital sign changes quadrupled from 3 to 12 (P<0.01) in scenario 1 and more than doubled from 3 to 8 (P<0.01) in scenario 2. Median perceived diagnostic confidence was “confident” for both scenarios with the avatar and “unconfident”, respectively “very unconfident” with conventional monitoring (Scenario 1 P<0.01, Scenario 2 P=0.02)

Conclusions:

Avatar-based monitoring provides a way to make the peripheral field of vision of physicians and nurses available for patient monitoring. Thus, avatar-based monitoring could make much more of the patient monitoring information available to the users through peripheral vision than conventional monitoring and, therefore, for longer time periods per anesthesia case. The optimal information transmission consists of a combination of auditory and avatar-based monitoring.