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.
BackgroundA 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.MethodsFirst, 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.ResultsWe 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).ConclusionThis 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.Electronic supplementary materialThe online version of this article (10.1186/s12871-018-0650-1) contains supplementary material, which is available to authorized users.
Background Dementia and mild cognitive impairment (MCI) are under-recognized in community settings. This may be due in part to the lack of brief dementia screening tools available to clinicians. We compared two brief, informant-based screening tests: the AD8 and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) in a community-based neurology practice in the Midwestern United States Methods We examined 186 consecutive patients (44 controls, 13 with MCI, and 129 with dementia). Receiver operator characteristic curves were used to examine the ability of AD8 and IQCODE to discriminate between controls and MCI or dementia. Sensitivity, specificity, predictive values, and likelihood ratios were reported. Results AD8 differentiated healthy controls from MCI (p<.001) or dementia (p<.001), as well as MCI from dementia (p=.008). The IQCODE differentiated controls and MCI from dementia (both p<.001), and between controls and MCI (p=.002). Both AD8 (AUC = 0.953, 95% CI: 0.92–0.99) and IQCODE (AUC = 0.930, 95% CI: 0.88–0.97) provided discrimination between controls and patients with dementia; however the AD8 had superior sensitivity detecting dementia (99.2%) and MCI (100%) compared to the IQCODE (79.1% for dementia, 46.1% for MCI) with non-overlapping confidence intervals. Using published cut-offs (AD8 ≥ 2, IQCODE ≥ 3.4), only one case of dementia was missed with the AD8 while the IQCODE failed to detect dementia in 27 individuals. The AD8 detected MCI in all 13 individuals while the IQCODE misclassified 7 individuals. Conclusion Both the AD8 and IQCODE were able to detect dementia in a community setting. The AD8, however, was more successful than IQCODE in detecting MCI. If simple and efficient screening for early cognitive impairment is the goal, particularly in the early stages (e.g., for prevention trials or public screening), the combination of an informant interview (the AD8) and a brief performance measure could be considered as they meet the basic requirements of the Personalized Prevention Plan for Medicare beneficiaries.
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.
Background Continuous patient monitoring has been described by the World Health Organization as extremely important and is widely used in anesthesia, intensive care medicine, and emergency medicine. However, current state-of-the-art number- and waveform-based monitoring does not ideally support human users in acquiring quick, confident interpretations with low cognitive effort, and there are additional problematic aspects such as alarm fatigue. We developed a visualization technology (Visual Patient), specifically designed to help caregivers gain situation awareness quickly, which presents vital sign information in the form of an animated avatar of the monitored patient. We suspected that because of the way it displays the information as large, colorful, moving graphic objects, caregivers might be able to perform patient monitoring using their peripheral vision, which may facilitate quicker detection of anomalies, independently of acoustic alarms. Objective In this study, we tested the hypothesis that avatar-based monitoring, when observed with peripheral vision only, increases the number of perceptible changes in patient status as well as caregivers’ perceived diagnostic confidence compared with a high-fidelity simulation of conventional monitoring, when observed with peripheral vision only. Methods We conducted a multicenter comparative study with a within-participant design in which anesthesiologists with their peripheral field of vision looked at 2 patient-monitoring scenarios and tried to identify changes in patient status. To ensure the best possible experimental conditions, we used an eye tracker, which recorded the eye movements of the participants and confirmed that they only looked at the monitoring scenarios with their peripheral vision. Results Overall, 30 participants evaluated 18 different patient status changes with each technology (avatar and conventional patient monitoring). With conventional patient monitoring, participants could only detect those 3 changes in patient status that are associated with a change in the auditory pulse tone display, that is, 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 <.001) in scenario 1, and more than doubled from 3 to 8 ( P <.001) in scenario 2. Median perceived diagnostic confidence was confident for both scenarios with the avatar and unconfident in scenario 1 ( P <.001), and very unconfident in scenario 2 ( P= .024) with conventional monitoring. Conclusions This study introduces the concept of peripheral vision monitoring. The test performed showed clearly that an avatar-based display is superior ...
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