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

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.

It's not you, it's the design - common problems with patient monitoring reported by anesthesiologists: a mixed qualitative and quantitative study.

BACKGROUND: Patient monitoring is critical for perioperative patient safety as anesthesiologists routinely make crucial therapeutic decisions from the information displayed on patient monitors. Previous research has shown that today's patient monitoring has room for improvement in areas such as information overload and alarm fatigue. The rationale of this study was to learn more about the problems anesthesiologists face in patient monitoring and to derive improvement suggestions for next-generation patient monitors. METHODS: We conducted a two-center qualitative/quantitative study. Initially, we interviewed 120 anesthesiologists (physicians and nurses) about the topic: common problems with patient monitoring in your daily work. Through deductive and inductive coding, we identified major topics and sub themes from the interviews. In a second step, a field survey, a separate group of 25 anesthesiologists rated their agree- or disagreement with central statements created for all identified major topics. RESULTS: We identified the following six main topics: 1. "Alarms," 2. "Artifacts," 3. "Software," 4. "Hardware," 5. "Human Factors," 6. "System Factors," and 17 sub themes. The central statements rated for the major topics were: 1. "problems with alarm settings complicate patient monitoring." (56% agreed) 2. "artifacts complicate the assessment of the situation." (64% agreed) 3. "information overload makes it difficult to get an overview quickly." (56% agreed) 4. "problems with cables complicate working with patient monitors." (92% agreed) 5. "factors related to human performance lead to critical information not being perceived." (88% agreed) 6. "Switching between monitors from different manufacturers is difficult." (88% agreed). The ratings of all statements differed significantly from neutral (all p < 0.03). CONCLUSION: This study provides an overview of the problems anesthesiologists face in patient monitoring. Some of the issues, to our knowledge, were not previously identified as common problems in patient monitoring, e.g., hardware problems (e.g., cable entanglement and worn connectors), human factor aspects (e.g., fatigue and distractions), and systemic factor aspects (e.g., insufficient standardization between manufacturers). An ideal monitor should transfer the relevant patient monitoring information as efficiently as possible, prevent false positive alarms, and use technologies designed to improve the problems in patient monitoring.

User perceptions of avatar-based patient monitoring: a mixed qualitative and quantitative study.

BACKGROUND: A new patient monitoring technology called Visual Patient, which transforms numerical and waveform data into a virtual model (an avatar) of the monitored patient, has been shown to improve the perception of vital signs compared to conventional patient monitoring. In order to gain a deeper understanding of the opinions of potential future users regarding the new technology, we have analyzed the answers of two large groups of anesthetists using two different study methods. METHODS: First, we carried out a qualitative analysis guided by the "consolidated criteria for reporting qualitative research" checklist. For this analysis, we interviewed 128 anesthesiologists, asking: "Where do you see advantages in Visual Patient monitoring?" and afterward identified major and minor themes in their answers. In a second study, an online survey with 38 anesthesiologists at two different institutions, we added a quantitative part in which anesthesiologists rated statements based on the themes identified in the prior analysis on an ordinal rating scale. RESULTS: We identified four high-level themes: "quick situation recognition," "intuitiveness," "unique design characteristics," and "potential future uses," and eight subthemes. The quantitative questions raised for each major theme were: 1. "The Visual Patient technology enabled me to get a quick overview of the situation." (63% of the participants agreed or very much agreed to this statement). 2. "I found the Visual Patient technology to be intuitive and easy to learn." (82% agreed or very much agreed to this statement). 3. "The visual design features of the Visual Patient technology (e.g., the avatar representation) are not helpful for patient monitoring." (11% agreed to this statement). 4. "I think the Visual Patient technology might be helpful for non-monitor experts (e.g., surgeons) in the healthcare system." (53% of the participants agreed or strongly agreed). CONCLUSION: This mixed method study provides evidence that the included anesthesiologists considered the new avatar-based technology to be intuitive and easy to learn and that the technology enabled them to get an overview of the situation quickly. Only a few users considered the avatar presentation to be unhelpful for patient monitoring and about half think it might be useful for non-experts.