Avatar-Based Patient Monitoring With Peripheral Vision: A Multicenter Comparative Eye-Tracking Study

Visual avatar to increase situational awareness in anaesthesia: Systematic review of recent evidence

BACKGROUND

Systematic review focuses on the visual patient avatar (VPA) technology, a tool designed to enhance situational awareness in anesthesia by transforming traditional numerical data into intuitive visual displays.

AIM

To explore how VPA can improve perceptual performance, reduce cognitive load, and increase user acceptance, potentially leading to better patient outcomes.

METHODS

The review is based on 14 studies conducted between 2018 and 2023 in five different hospitals across Europe.

RESULTS

These studies demonstrate that VPA allows clinicians to perceive and recall vital signs more efficiently than conventional monitoring methods. The technology’s intuitive design helps reduce cognitive workload, indicating less mental effort required for patient monitoring. Users’ feedback on VPA was generally positive, highlighting its potential to enhance monitoring and decision-making in high-stress environments. However, some users noted the need for further development, particularly in visualization design and data integration.

CONCLUSION

Review concludes that VPA technology represents a significant advancement in patient monitoring, promoting better situational awareness and potentially improving safety in perioperative care.

Avatar-based versus conventional patient monitoring with distant vision: a computer-based simulation study

Patient monitoring in the perioperative setting can be challenging, especially when monitoring multiple patients simultaneously or managing dynamic situations that require movement around the operating room. We aimed to evaluate whether avatar-based patient monitoring, which presents vital signs in the form of changing colors, shapes and motion, improves remote vital sign recognition compared to conventional monitoring. We conducted a prospective, single-center, computer-based simulation study to evaluate how anesthesia providers recognize vital signs when using the Philips Visual Patient Avatar at different viewing distances (8 and 16 m) compared to conventional monitoring. The primary outcome was the total number of correctly identified vital signs which were compared for the two distances and the two devices using mixed Poisson regression. We analyzed data from 28 anesthesia providers who participated in 112 simulations. The correct recognition rate using the Visual Patient Avatar compared to conventional monitoring at 8 m was increased by 74% (rate ratio 1.74, 95% CI, 1.42 to 2.14, p < 0.001) and by 51% at 16-meter viewing distance (rate ratio 1.51, 95% CI, 1.23 to 1.87, p < 0.001). We observed scenario-specific superior performance for six vital signs at 8 m. The results provide empirical evidence that avatar-based monitoring can significantly improve the perception of vital signs when using distant vision.

The Visual Patient Avatar ICU Facilitates Information Transfer of Written Information by Visualization: A Multicenter Comparative Eye-Tracking Study

Patient monitoring is crucial in critical care medicine. Perceiving and interpreting multiple vital signs requires a high workload that can lead to decreased situation awareness and consequently inattentional blindness, defined as impaired perception of unexpectedly changing data. To facilitate information transfer, we developed and validated the Visual-Patient avatar. Generated by numerical data, the animation displays the status of vital signs and patient installations according to a user-centered design to improve situation awareness. As a surrogate parameter for information transfer in patient monitoring, we recorded visual attention using eye-tracking data. In this computer-based study, we compared the correlation of visually perceived and correctly interpreted vital signs between a Visual-Patient-avatar ICU and conventional patient monitoring. A total of 50 recruited study participants (25 nurses, 25 physicians) from five European study centers completed five randomized scenarios in both modalities. Using a stationary eye tracker as the primary endpoint, we recorded how long different areas of interest of the two monitoring modalities were viewed. In addition, we tested for a possible association between the length of time an area of interest was viewed and the correctness of the corresponding question. With the conventional monitor, participants looked at the installation site the longest (median 2.13-2.51 s). With the Visual-Patient-avatar ICU, gaze distribution was balanced; no area of interest was viewed for particularly long. For both modalities, the longer an area was viewed, the more likely the associated question was answered incorrectly (OR 0.97, 95% CI 0.95-0.99, p = 0.008). The Visual-Patient-avatar ICU facilitates and improves information transfer through its visualizations, especially with written information. The longer an area of interest was viewed, the more likely the associated question was answered incorrectly.

Human-centered visualization technologies for patient monitoring are the future: a narrative review

Medical technology innovation has improved patient monitoring in perioperative and intensive care medicine and continuous improvement in the technology is now a central focus in this field. Because data density increases with the number of parameters captured by patient-monitoring devices, its interpretation has become more challenging. Therefore, it is necessary to support clinicians in managing information overload while improving their awareness and understanding about the patient's health status. Patient monitoring has almost exclusively operated on the single-sensor-single-indicator principle-a technology-centered way of presenting data in which specific parameters are measured and displayed individually as separate numbers and waves. An alternative is user-centered medical visualization technology, which integrates multiple pieces of information (e.g., vital signs), derived from multiple sensors into a single indicator-an avatar-based visualization-that is a meaningful representation of the real-world situation. Data are presented as changing shapes, colors, and animation frequencies, which can be perceived, integrated, and interpreted much more efficiently than other formats (e.g., numbers). The beneficial effects of these technologies have been confirmed in computer-based simulation studies; visualization technologies improved clinicians' situation awareness by helping them effectively perceive and verbalize the underlying medical issue, while improving diagnostic confidence and reducing workload. This review presents an overview of the scientific results and the evidence for the validity of these technologies.

Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study

Patient monitoring is the foundation of intensive care medicine. High workload and information overload can impair situation awareness of staff, thus leading to loss of important information about patients' conditions. To facilitate mental processing of patient monitoring data, we developed the Visual-Patient-avatar Intensive Care Unit (ICU), a virtual patient model animated from vital signs and patient installation data. It incorporates user-centred design principles to foster situation awareness. This study investigated the avatar's effects on information transfer measured by performance, diagnostic confidence and perceived workload. This computer-based study compared Visual-Patient-avatar ICU and conventional monitor modality for the first time. We recruited 25 nurses and 25 physicians from five centres. The participants completed an equal number of scenarios in both modalities. Information transfer, as the primary outcome, was defined as correctly assessing vital signs and installations. Secondary outcomes included diagnostic confidence and perceived workload. For analysis, we used mixed models and matched odds ratios. Comparing 250 within-subject cases revealed that Visual-Patient-avatar ICU led to a higher rate of correctly assessed vital signs and installations [rate ratio (RR) 1.25; 95% CI 1.19-1.31; P < 0.001], strengthened diagnostic confidence [odds ratio (OR) 3.32; 95% CI 2.15-5.11, P < 0.001] and lowered perceived workload (coefficient - 7.62; 95% CI - 9.17 to - 6.07; P < 0.001) than conventional modality. Using Visual-Patient-avatar ICU, participants retrieved more information with higher diagnostic confidence and lower perceived workload compared to the current industry standard monitor.

Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis

Acid–base homeostasis is crucial for all physiological processes in the body and is evaluated using arterial blood gas (ABG) analysis. Screens or printouts of ABG results require the interpretation of many textual elements and numbers, which may delay intuitive comprehension. To optimise the presentation of the results for the specific strengths of human perception, we developed Visual Blood, an animated virtual model of ABG results. In this study, we compared its performance with a conventional result printout. Seventy physicians from three European university hospitals participated in a computer-based simulation study. Initially, after an educational video, we tested the participants’ ability to assign individual Visual Blood visualisations to their corresponding ABG parameters. As the primary outcome, we tested caregivers’ ability to correctly diagnose simulated clinical ABG scenarios with Visual Blood or conventional ABG printouts. For user feedback, participants rated their agreement with statements at the end of the study. Physicians correctly assigned 90% of the individual Visual Blood visualisations. Regarding the primary outcome, the participants made the correct diagnosis 86% of the time when using Visual Blood, compared to 68% when using the conventional ABG printout. A mixed logistic regression model showed an odds ratio for correct diagnosis of 3.4 (95%CI 2.00–5.79, p < 0.001) and an odds ratio for perceived diagnostic confidence of 1.88 (95%CI 1.67–2.11, p < 0.001) in favour of Visual Blood. A linear mixed model showed a coefficient for perceived workload of −3.2 (95%CI −3.77 to −2.64) in favour of Visual Blood. Fifty-one of seventy (73%) participants agreed or strongly agreed that Visual Blood was easy to use, and fifty-five of seventy (79%) agreed that it was fun to use. In conclusion, Visual Blood improved physicians’ ability to diagnose ABG results. It also increased perceived diagnostic confidence and reduced perceived workload. This study adds to the growing body of research showing that decision-support tools developed around human cognitive abilities can streamline caregivers’ decision-making and may improve patient care.

Anesthesia personnel’s visual attention regarding patient monitoring in simulated non-critical and critical situations, an eye-tracking study

Background

Cognitive ergonomics design of patient monitoring may reduce human factor errors in high-stress environments. Eye-tracking is a suitable tool to gain insight into the distribution of visual attention of healthcare professionals with patient monitors, which may facilitate their further development.

Methods

This prospective, exploratory, high-fidelity simulation study compared anesthesia personnel’s visual attention (fixation count and dwell-time) to 15 areas of interest on the patient monitor during non-critical and critical anesthesia situations. Furthermore, we examined the extent to which participants’ experience influenced visual attention and which vital signs displayed on the patient monitor received the most visual attention. We used mixed zero-inflated Poisson regression and mixed linear models to analyze the data.

Results

Analyzing 23 ten-minute scenarios, we found significantly more fixations to the areas of interest on the patient monitor during critical than non-critical situations (rate ratio of 1.45; 95% CI 1.33 to 1.59; p < 0.001). However, the dwell-time on the areas of interest did not significantly differ between the non-critical and critical situations (coefficient of − 1.667; 95% CI − 4.549 to 1.229; p = 0.27). The professional experience did not significantly influence the visual attention (fixation: rate ratio of 0.88; 95% CI 0.54 to 1.43; p = 0.61 and dwell-time: coefficient of 0.889; 95% CI − 1.465 to 3.229; p = 0.27).

Over all situations, anesthesia personnel paid the most attention to the vital signs blood pressure (fixation: mean [SD] of 108 [74.83]; dwell-time: mean [SD] of 27 [15.90] seconds), end-expiratory carbon dioxide (fixation: mean [SD] of 59 [47.39]; dwell-time: mean [SD] of 30 [21.51] seconds), and the electrocardiogram (fixation: mean [SD] of 58 [64.70]; dwell-time: mean [SD] of 15 [14.95] seconds).

Conclusions

Critical anesthesia situations increased anesthesia personnel’s visual interaction with the patient monitor. Furthermore, we found that their visual attention focused mainly on a few vital signs. To assist clinicians in critical situations, manufacturers should optimize monitors to convey necessary information as easily and quickly as possible and optimize the visibility of less frequently observed but equally critical vital signs, especially when they are in an abnormal range.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12871-022-01705-6.

Improving Visual-Patient-Avatar Design Prior to Its Clinical Release: A Mixed Qualitative and Quantitative Study

Visual-Patient-avatar, an avatar-based visualisation of patient monitoring, is a newly developed technology aiming to promote situation awareness through user-centred design. Before the technology’s introduction into clinical practice, the initial design used to validate the concept had to undergo thorough examination and adjustments where necessary. This mixed qualitative and quantitative study, consisting of three different study parts, aimed to create a design with high user acceptance regarding perceived professionalism and potential for identification while maintaining its original functionality. The first qualitative part was based on structured interviews and explored anaesthesia personnel’s first impressions regarding the original design. Recurrent topics were identified using inductive coding, participants’ interpretations of the vital sign visualisations analysed and design modifications derived. The second study part consisted of a redesign process, in which the visualisations were adapted according to the results of the first part. In a third, quantitative study part, participants rated Likert scales about Visual-Patient-avatar’s appearance and interpreted displayed vital signs in a computer-based survey. The first, qualitative study part included 51 structured interviews. Twenty-eight of 51 (55%) participants mentioned the appearance of Visual-Patient-avatar. In 23 of 51 (45%) interviews, 26 statements about the general impression were identified with a balanced count of positive (14 of 26) and negative (12 of 26) comments. The analysis of vital sign visualisations showed deficits in several vital sign visualisations, especially central venous pressure. These findings were incorporated into part two, the redesign of Visual-Patient-avatar. In the subsequent quantitative analysis of study for part three, 20 of 30 (67%) new participants agreed that the avatar looks professional enough for medical use. Finally, the participants identified 73% (435 of 600 cases) of all vital sign visualisations intuitively correctly without prior instruction. This study succeeded in improving the original design with good user acceptance and a reasonable degree of intuitiveness of the new, revised design. Furthermore, the study identified aspects relevant for the release of Visual-Patient-avatar, such as the requirement for providing at least some training, despite the design’s intuitiveness. The results of this study will guide further research and improvement of the technology. The study provides a link between Visual-Patient-avatar as a scientific concept and as an actual product from a cognitive engineering point of view, and may serve as an example of methods to study the designs of technologies in similar contexts.

Anesthesia providers' visual attention in simulated anesthesia emergencies using conventional number-based and avatar-based patient monitoring: a prospective, eye-tracking study

BACKGROUND

Inadequate situational awareness accounts for two-thirds of preventable complications in anesthesia. An essential tool for situational awareness in the perioperative setting is the patient monitor. However, the conventional monitor has several weaknesses. Avatar-based patient monitoring may address these shortcomings and promote situation awareness, a prerequisite for good decision making.

OBJECTIVE

The spatial distribution of visual attention is a fundamental process for achieving adequate situation awareness and thus a potential quantifiable surrogate for situation awareness. Moreover, measuring visual attention with a head-mounted eye-tracker may provide insights into usage and acceptance of the new avatar-based patient monitoring modality.

METHODS

This prospective eye-tracking study compared anesthesia providers' visual attention on conventional and avatar-based patient monitors during simulated critical anesthesia events. We defined visual attention, measured as fixation count and dwell time, as our primary outcome. We correlated visual attention with the potential confounders: performance in managing simulated critical anesthesia events (task performance), work experience, and profession. We used mixed linear models to analyze the results.

RESULTS

Fifty-two teams performed 156 simulations. After a manual quality check of the eye-tracking footage, we excluded 57 simulations due to technical problems and quality issues. Participants had a median of 198 (IQR 92.5 - 317.5) fixations on the patient monitor with a median dwell time of 30.2 (IQR 14.9 - 51.3) seconds. We found no significant difference in participants' visual attention when using avatar-based patient monitoring or conventional patient monitoring. However, we found that with each percentage point of better task performance, the number of fixations decreased by about 1.39 (coefficient -1.39; 95%CI: -2.44 to -0.34; P=.02), and the dwell time diminished by 0.23 seconds (coefficient -0.23; 95%CI: -0.4 to -0.06; P=.01).

CONCLUSIONS

Using eye-tracking, we found no significant difference in visual attention when anesthesia providers used avatar-based monitoring or conventional patient monitoring in simulated critical anesthesia events. However, we identified visual attention in conjunction with task performance as a surrogate for situational awareness.

CLINICALTRIAL

Business Management System for Ethics Committees Number Req-2020-00059.

Situation awareness and the mitigation of risk associated with patient deterioration: A meta-narrative review of theories and models and their relevance to nursing practice

BACKGROUND

Accurate situation awareness has been identified as a critical component of effective deteriorating patient response systems and an essential patient safety skill for nursing practice. However, situation awareness has been defined and theorised from multiple perspectives to explain how individuals, teams and systems maintain awareness in dynamic task environments.

AIM

Our aim was to critically analyse the different approaches taken to the study of situation awareness in healthcare and explore the implications for nursing practice and research as it relates to clinical deterioration in ward contexts.

METHODS

We undertook a meta-narrative review of the healthcare literature to capture how situation awareness has been defined, theorised and studied in healthcare. Following an initial scoping review, we conducted an extensive search of ten electronic databases and included any theoretical, empirical or critical papers with a primary focus on situation awareness in an inpatient hospital setting. Included papers were collaboratively categorised in accordance with their theoretical framing, research tradition and paradigm with a narrative review presented.

RESULTS

A total of 120 papers were included in this review. Three overarching narratives reflecting philosophical, patient safety and solution focussed framings of situation awareness and seven meta-narratives were identified as follows: individual, team and systems perspectives of situation awareness (meta-narratives 1-3), situation awareness and patient safety (meta-narrative 4), communication tools, technologies and education to support situation awareness (meta-narratives 5-7). We identified a concentration of literature from anaesthesia and operating rooms and a body of research largely located within a cognitive engineering tradition and a positivist research paradigm. Endsley's situation awareness model was applied in over 80% of the papers reviewed. A minority of papers drew on alternative situation awareness theories including constructivist, collaborative and distributed perspectives.

CONCLUSIONS

Nurses have a critical role in identifying and escalating the care of deteriorating patients. There is a need to build on prior studies and reflect on the reality of nurse's work and the constraints imposed on situation awareness by the demands of busy inpatient wards. We suggest that this will require an analysis that complements but goes beyond the dominant cognitive engineering tradition to reflect the complex socio-cultural reality of ward-based teams and to explore how situation awareness emerges in increasingly complex, technologically enabled distributed healthcare systems.

Avatar-based patient monitoring in critical anaesthesia events: a randomised high-fidelity simulation study

BACKGROUND

Failures in situation awareness cause two-thirds of anaesthesia complications. Avatar-based patient monitoring may promote situation awareness in critical situations.

METHODS

We conducted a prospective, randomised, high-fidelity simulation study powered for non-inferiority. We used video analysis to grade anaesthesia teams managing three 10 min emergency scenarios using three randomly assigned monitoring modalities: only conventional, only avatar, and split-screen showing both modalities side by side. The primary outcome was time to performance of critical tasks. Secondary outcomes were time to verbalisation of vital sign deviations and the correct cause of the emergency, perceived workload, and usability. We used mixed Cox and linear regression models adjusted for various potential confounders. The non-inferiority margin was 10%, or hazard ratio (HR) 0.9.

RESULTS

We analysed 52 teams performing 154 simulations. For performance of critical tasks during a scenario, split-screen was non-inferior to conventional (HR=1.13; 95% confidence interval [CI], 0.96-1.33; not significant in test for superiority); the result for avatar was inconclusive (HR=0.98; 95% CI, 0.83-1.15). Avatar was associated with a higher probability for verbalisation of the cause of the emergency (HR=1.78; 95% CI, 1.13-2.81; P=0.012). We found no evidence for a monitor effect on perceived workload. Perceived usability was lower for avatar (coefficient=-23.0; 95% CI, -27.2 to -18.8; P<0.0001) and split-screen (-6.7; 95% CI, -10.9 to -2.4; P=0.002) compared with conventional.

CONCLUSIONS

This study showed non-inferiority of split-screen compared with conventional monitoring for performance of critical tasks during anaesthesia crisis situations. The patient avatar improved verbalisation of the correct cause of the emergency. These results should be interpreted considering participants' minimal avatar but extensive conventional monitoring experience.

Physicians' Perceptions of a Situation Awareness-Oriented Visualization Technology for Viscoelastic Blood Coagulation Management (Visual Clot): Mixed Methods Study

Background

Viscoelastic tests enable a time-efficient analysis of coagulation properties. An important limitation of viscoelastic tests is the complicated presentation of their results in the form of abstract graphs with a multitude of numbers. We developed Visual Clot to simplify the interpretation of presented clotting information. This visualization technology applies user-centered design principles to create an animated model of a blood clot during the hemostatic cascade. In a previous simulation study, we found Visual Clot to double diagnostic accuracy, reduce time to decision making and perceived workload, and improve care providers’ confidence.

Objective

This study aimed to investigate the opinions of physicians on Visual Clot technology. It further aimed to assess its strengths, limitations, and clinical applicability as a support tool for coagulation management.

Methods

This was a researcher-initiated, international, double-center, mixed qualitative-quantitative study that included the anesthesiologists and intensive care physicians who participated in the previous Visual Clot study. After the participants solved six coagulation scenarios using Visual Clot, we questioned them about the perceived pros and cons of this new tool. Employing qualitative research methods, we identified recurring answer patterns, and derived major topics and subthemes through inductive coding. Based on them, we defined six statements. The study participants later rated their agreement to these statements on five-point Likert scales in an online survey, which represented the quantitative part of this study.

Results

A total of 60 physicians participated in the primary Visual Clot study. Among these, 36 gave an interview and 42 completed the online survey. In total, eight different major topics were derived from the interview field note responses. The three most common topics were “positive design features” (29/36, 81%), “facilitates decision making” (17/36, 47%), and “quantification not made” (17/36, 47%). In the online survey, 93% (39/42) agreed to the statement that Visual Clot is intuitive and easy to learn. Moreover, 90% (38/42) of the participants agreed that they would like the standard result and Visual Clot displayed on the screen side by side. Furthermore, 86% (36/42) indicated that Visual Clot allows them to deal with complex coagulation situations more quickly.

Conclusions

A group of anesthesia and intensive care physicians from two university hospitals in central Europe considered Visual Clot technology to be intuitive, easy to learn, and useful for decision making in situations of active bleeding. From the responses of these possible future users, Visual Clot appears to constitute an efficient and well-accepted way to streamline the decision-making process in viscoelastic test–based coagulation management.

Comparing Classroom Instruction to Individual Instruction as an Approach to Teach Avatar-Based Patient Monitoring With Visual Patient: Simulation Study

BACKGROUND

Visual Patient is an avatar-based alternative to standard patient monitor displays that significantly improves the perception of vital signs. Implementation of this technology in larger organizations would require it to be teachable by brief class instruction to large groups of professionals. Therefore, our study aimed to investigate the efficacy of such a large-scale introduction to Visual Patient.

OBJECTIVE

In this study, we aimed to compare 2 different educational methods, one-on-one instruction and class instruction, for training anesthesia providers in avatar-based patient monitoring.

METHODS

We presented 42 anesthesia providers with 30 minutes of class instruction on Visual Patient (class instruction group). We further selected a historical sample of 16 participants from a previous study who each received individual instruction (individual instruction group). After the instruction, the participants were shown monitors with either conventional displays or Visual Patient displays and were asked to interpret vital signs. In the class instruction group, the participants were shown scenarios for either 3 or 10 seconds, and the numbers of correct perceptions with each technology were compared. Then, the teaching efficacy of the class instruction was compared with that of the individual instruction in the historical sample by 2-way mixed analysis of variance and mixed regression.

RESULTS

In the class instruction group, when participants were presented with the 3-second scenario, there was a statistically significant median increase in the number of perceived vital signs when the participants were shown the Visual Patient compared to when they were shown the conventional display (3 vital signs, P<.001; effect size -0.55). No significant difference was found for the 10-second scenarios. There was a statistically significant interaction between the teaching intervention and display technology in the number of perceived vital signs (P=.04; partial η²=.076). The mixed logistic regression model for correct vital sign perception yielded an odds ratio (OR) of 1.88 (95% CI 1.41-2.52; P<.001) for individual instruction compared to class instruction as well as an OR of 3.03 (95% CI 2.50-3.70; P<.001) for the Visual Patient compared to conventional monitoring.

CONCLUSIONS

Although individual instruction on Visual Patient is slightly more effective, class instruction is a viable teaching method; thus, large-scale introduction of health care providers to this novel technology is feasible.

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

Visual Patient technology is a situation awareness-oriented visualization technology that translates numerical and waveform patient monitoring data into a new user-centered visual language. Vital sign values are converted into colors, shapes, and rhythmic movements-a language humans can easily perceive and interpret-on a patient avatar model in real time. In this review, we summarize the current state of the research on the Visual Patient, including the technology, its history, and its scientific context. We also provide a summary of our primary research and a brief overview of research work on similar user-centered visualizations in medicine. In several computer-based studies under various experimental conditions, Visual Patient transferred more information per unit time, increased perceived diagnostic certainty, and lowered perceived workload. Eye tracking showed the technology worked because of the way it synthesizes and transforms vital sign information into new and logical forms corresponding to the real phenomena. The technology could be particularly useful for improving situation awareness in settings with high cognitive demand or when users must make quick decisions. This comprehensive review of Visual Patient research is the foundation for an evaluation of the technology in clinical applications, starting with a high-fidelity simulation study in early 2020.

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.

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

BACKGROUND

Maintaining adequate situation awareness is crucial for patient safety. Previous studies found that the use of avatar-based monitoring (Visual Patient Technology) improved the perception of vital signs compared to conventional monitoring showing numerical and waveform data; and was further associated with a reduction of perceived workload. In this study, we aimed to evaluate the effectiveness of Visual Patient Technology on perceptive performance and perceived workload when monitoring multiple patients at the same time, such as in central station monitors in intensive care units or operating rooms.

METHODS

A prospective, within-subject, computer-based laboratory study was performed in two tertiary care hospitals in Switzerland in 2018. Thirty-eight physician and nurse anesthetists volunteered for the study. The participants were shown four different central monitor scenarios in sequence, where each scenario displayed two critical and four healthy patients simultaneously for 10 or 30 s. After each scenario, participants had to recall the vital signs of the critical patients. Perceived workload was assessed with the National Aeronautics and Space Administration Task-Load-Index (NASA TLX) questionnaire.

RESULTS

In the 10-s scenarios, the median number of remembered vital signs significantly improved from 7 to 11 using avatar-based versus conventional monitoring with a mean of differences of 4 vital signs, 95% confidence interval (CI) 2 to 6, p < 0.001. At the same time, the median NASA TLX scores were significantly lower for avatar-based monitoring (67 vs. 77) with a mean of differences of 6 points, 95% CI 0.5 to 11, p = 0.034. In the 30-s scenarios, vital sign perception and workload did not differ significantly.

CONCLUSIONS

In central monitor multiple patient monitoring, we found a significant improvement of vital sign perception and reduction of perceived workload using Visual Patient Technology, compared to conventional monitoring. The technology enabled improved assessment of patient status and may, thereby, help to increase situation awareness and enhance patient safety.