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.

Effects of an Animated Blood Clot Technology (Visual Clot) on the Decision-Making of Users Inexperienced in Viscoelastic Testing: Multicenter Trial.

BACKGROUND: Viscoelastic test-guided coagulation management has become increasingly important in assessing hemostasis. We developed Visual Clot, an animated, 3D blood clot that illustrates raw rotational thromboelastometry (ROTEM) parameters in a user-centered and situation awareness-oriented method. OBJECTIVE: This study aimed to evaluate the applicability of Visual Clot by examining its effects on users that are novices in viscoelastic-guided resuscitation. METHODS: We conducted an investigator-initiated, international, multicenter study between September 16, 2020, and October 6, 2020, in 5 tertiary care hospitals in central Europe. We randomly recruited medical students and inexperienced resident physicians without significant prior exposure to viscoelastic testing. The 7 participants per center managed 9 different ROTEM outputs twice, once as standard ROTEM tracings and once as the corresponding Visual Clot. We randomly presented the 18 viscoelastic cases and asked the participants for their therapeutic decisions. We assessed the performance, diagnostic confidence, and perceived workload in managing the tasks using mixed statistical models and adjusted for possible confounding factors. RESULTS: Analyzing a total of 630 results, we found that the participants solved more cases correctly (odds ratio [OR] 33.66, 95% CI 21.13-53.64; P<.001), exhibited more diagnostic confidence (OR 206.2, 95% CI 93.5-454.75; P<.001), and perceived less workload (coefficient -41.63; 95% CI -43.91 to -39.36; P<.001) using Visual Clot compared to using standard ROTEM tracings. CONCLUSIONS: This study emphasizes the practical benefit of presenting viscoelastic test results in a user-centered way. Visual Clot may allow inexperienced users to be involved in the decision-making process to treat bleeding-associated coagulopathy. The increased diagnostic confidence, diagnostic certainty, reduced workload, and positive user feedback associated with this visualization may promote the further adoption of viscoelastic methods in diverse health care settings.

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.