The Mechanisms Responsible for Improved Information Transfer in Avatar-Based Patient Monitoring: Multicenter Comparative Eye-Tracking Study

Abstract

Background Patient monitoring is central to perioperative and intensive care patient safety. Current state-of-the-art monitors display vital signs as numbers and waveforms. Visual Patient technology creates an easy-to-interpret virtual patient avatar model that displays vital sign information as it would look in a real-life patient (eg, avatar changes skin color from healthy to cyanotic depending on oxygen saturation). In previous studies, anesthesia providers using Visual Patient perceived more vital signs during short glances than with conventional monitoring. Objective We aimed to study the deeper mechanisms underlying information perception in conventional and avatar-based monitoring. Methods In this prospective, multicenter study with a within-subject design, we showed 32 anesthesia providers four 3- and 10-second monitoring scenarios alternatingly as either routine conventional or avatar-based in random sequence. All participants observed the same scenarios with both technologies and reported the vital sign status after each scenario. Using eye-tracking, we evaluated which vital signs the participants had visually fixated (ie, could have potentially read and perceived) during a scenario. We compared the frequencies and durations of participants’ visual fixations of vital signs between the two technologies. Results Participants visually fixated more vital signs per scenario in avatar-based monitoring (median 10, IQR 9-11 versus median 6, IQR 4-8, P<.001; median of differences=3, 95% CI 3-4). In multivariable linear regression, monitoring technology (conventional versus avatar-based monitoring, difference=−3.3, P<.001) was an independent predictor of the number of visually fixated vital signs. The difference was less prominent in the longer (10-second) scenarios (difference=−1.5, P=.04). Study center, profession, gender, and scenario order did not influence the differences between methods. In all four scenarios, the participants visually fixated 9 of 11 vital signs statistically significantly longer using the avatar (all P<.001). Four critical vital signs (pulse rate, blood pressure, oxygen saturation, and respiratory rate) were visible almost the entire time of a scenario with the avatar; these were only visible for fractions of the observations with conventional monitoring. Visual fixation of a certain vital sign was associated with the correct perception of that vital sign in both technologies (avatar: phi coefficient=0.358; conventional monitoring: phi coefficient=0.515, both P<.001). Conclusions This eye-tracking study uncovered that the way the avatar-based technology integrates the vital sign information into a virtual patient model enabled parallel perception of multiple vital signs and was responsible for the improved information transfer. For example, a single look at the avatar’s body can provide information about: pulse rate (pulsation frequency), blood pressure (pulsation intensity), oxygen saturation (skin color), neuromuscular relaxation (extremities limp or stiff), and body temperature (heatwaves or ice crystals). This study adds a new and higher level of empirical evidence about why avatar-based monitoring improves vital sign perception compared with conventional monitoring.

Avatar-based versus conventional vital sign display in a central monitor for monitoring multiple patients: a multicenter computer-based laboratory study

“…The fact that the perceptive performance in the 30-s scenarios was not significantly different between the technologies suggests that avatar-based monitoring might be especially helpful when looking at monitors in short glances, which reflects the reality in clinical work [7,8,21]. The decreased size of the differences between avatar-based and conventional monitoring with increasing observation time, indicated by the smaller observed effect sizes in the 30-s scenarios, was similar to our previous studies, which investigated the effects of avatar-based monitoring for monitoring one patient at a time [23,25,26].…”

“…Additionally, the technology improved perceptive performance in a setting with a distraction [25]. In eye-tracking studies, we found that the technology works because users do not need to read numbers sequentially but can receive information from looking at colorful moving objects, which allows for monitoring using peripheral vision and enables parallel perception of multiple vital signs at the same time [26,27].…”

Situation Awareness-Oriented Patient Monitoring with Visual Patient Technology: A Qualitative Review of the Primary Research

“…Because of the use of colors, shapes, and movements, users can perceive several vital signs simultaneously, according to the results of one of our eye-tracking studies [3].…”

“…We divided the Visual Patient studies published so far into two major series: Visual Patient series 1 and Visual Patient series 2. Series 1 contains the preliminary studies, which aimed at qualitative and quantitative validation, stepwise improvement, and the first comparison of the technology's performance with regular monitoring [1][2][3]. In series 2, we tested the technology in three particular conditions for patient monitoring: using only peripheral vision [4], while being distracted [6], and when monitoring multiple patients at the same time, such as is in an intensive care unit central station monitor [5].…”

“…In early 2020, we will begin a high-fidelity simulation study with a product by Philips (Koninklijke Philips N.V., Amsterdam, the Netherlands) developed from the Visual Patient concept. With this milestone, we move from basic research on our product [1][2][3][4][5][6][7] to clinical application research. This paper contributes a comprehensive overview of the research behind Visual Patient to the current literature.…”