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

Abstract

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

“…In the 3 s scenarios, we found the greatest differences between technologies: participants were able to perceive more than twice as many vital signs with Visual Patient [1,3,6]. In the 10 s scenarios, with and without distraction and in single and multipatient situations, we also found clinically and statistically significant improvements [1,4,5,7]. The only situations where there was no statistically significant difference were the 10 s classroom instruction scenario and the 30 s central monitor scenarios with several patients [5].…”

“…We conducted all studies in series 1 and 2 as two-center studies in Switzerland at the University Hospital of Zurich and the Cantonal Hospital of Winterthur. Additionally, we review a study in which we compared two different methods of training in the technology: individual personal training and training a class in an auditorium [7]. A summary of all studies is provided in Table 2.…”

“…This study was published in 2020 [7]. Although previous studies have shown that Visual Patient is intuitive to understand, we aimed to compare different instruction methods for the novel technology [1,2,58].…”

“…In five separate experiments, we compared the perceptual performance of the participants with Visual Patient and routine patient monitoring [1,[4][5][6][7]. The participants looked at scenarios in randomized order and had to indicate how they perceived the vital signs after the short observation periods.…”

“…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.…”