TY  - JOUR
A1  - Bergauer, Lisa
A1  - Akbas, Samira
A1  - Braun, Julia
A1  - Ganter, Michael T.
A1  - Meybohm, Patrick
A1  - Hottenrott, Sebastian
A1  - Zacharowski, Kai
A1  - Raimann, Florian J.
A1  - Rivas, Eva
A1  - López-Baamonde, Manuel
A1  - Spahn, Donat R.
A1  - Noethiger, Christoph B.
A1  - Tscholl, David W.
A1  - Roche, Tadzio R.
T1  - Visual Blood, visualisation of blood gas analysis in virtual reality, leads to more correct diagnoses: a computer-based, multicentre, simulation study
JF  - Bioengineering
N2  - Interpreting blood gas analysis results can be challenging for the clinician, especially in stressful situations under time pressure. To foster fast and correct interpretation of blood gas results, we developed Visual Blood. This computer-based, multicentre, noninferiority study compared Visual Blood and conventional arterial blood gas (ABG) printouts. We presented six scenarios to anaesthesiologists, once with Visual Blood and once with the conventional ABG printout. The primary outcome was ABG parameter perception. The secondary outcomes included correct clinical diagnoses, perceived diagnostic confidence, and perceived workload. To analyse the results, we used mixed models and matched odds ratios. Analysing 300 within-subject cases, we showed noninferiority of Visual Blood compared to ABG printouts concerning the rate of correctly perceived ABG parameters (rate ratio, 0.96; 95% CI, 0.92–1.00; p = 0.06). Additionally, the study revealed two times higher odds of making the correct clinical diagnosis using Visual Blood (OR, 2.16; 95% CI, 1.42–3.29; p < 0.001) than using ABG printouts. There was no or, respectively, weak evidence for a difference in diagnostic confidence (OR, 0.84; 95% CI, 0.58–1.21; p = 0.34) and perceived workload (Coefficient, 2.44; 95% CI, −0.09–4.98; p = 0.06). This study showed that participants did not perceive the ABG parameters better, but using Visual Blood resulted in more correct clinical diagnoses than using conventional ABG printouts. This suggests that Visual Blood allows for a higher level of situation awareness beyond individual parameters’ perception. However, the study also highlighted the limitations of today’s virtual reality headsets and Visual Blood.
KW  - virtual reality
KW  - blood gas analysis
KW  - data display
KW  - point-of-care
KW  - situation awareness
KW  - user-centred design
KW  - diagnostic correctness
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-310979
SN  - 2306-5354
VL  - 10
IS  - 3
ER  - 
TY  - JOUR
A1  - Schweiger, Giovanna
A1  - Malorgio, Amos
A1  - Henckert, David
A1  - Braun, Julia
A1  - Meybohm, Patrick
A1  - Hottenrott, Sebastian
A1  - Froehlich, Corinna
A1  - Zacharowski, Kai
A1  - Raimann, Florian J.
A1  - Piekarski, Florian
A1  - Noethiger, Christoph B.
A1  - Spahn, Donat R.
A1  - Tscholl, David W.
A1  - Roche, Tadzio R.
T1  - Visual Blood, a 3D animated computer model to optimize the interpretation of blood gas analysis
JF  - Bioengineering
N2  - 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.
KW  - blood gas analysis
KW  - medical devices
KW  - point-of-care-testing
KW  - situational awareness
KW  - technology
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-304150
SN  - 2306-5354
VL  - 10
IS  - 3
ER  -