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BACKGROUND Viscoelastic hemostatic assays, such as ROTEM or TEG, enable prompt diagnosis and accelerate targeted treatment. However, the complex interpretation of the results remains challenging. Visual Clot - a situation awareness-based visualization technology - was developed to assist clinicians in interpreting viscoelastic tests. OBJECTIVE Following a previous high-fidelity simulation study, we analyzed users' perceptions of the technology to identify its strengths and limitations from clinicians' perspectives. METHODS This is a mixed qualitative-quantitative study consisting of interviews and an online survey. After solving coagulation scenarios using Visual Clot in high-fidelity simulations, we interviewed anesthesia personnel about the perceived advantages and disadvantages of the new tool. We used a template approach to identify dominant themes in interview responses. Out of these themes, we then defined five main statements, which were rated on Likert scales in the online questionnaire. RESULTS We interviewed 77 participants and 23 completed the online survey. We identified nine frequently mentioned topics by analyzing interview responses. The most common themes were ``positive design features``, ``intuitive and easy to learn`` and ``lack of a quantitative component ``. In the online survey, 70% of participants agreed that Visual Clot is easy to learn and that a combination of Visual Clot and ROTEM would help manage complex hemostatic situations. CONCLUSIONS A group of anesthesia care providers found Visual Clot well-designed, intuitive and easy to learn. Participants highlighted its usefulness in emergencies, especially for clinicians inexperienced in coagulation management. However, the lack of quantitative information is an area for improvement.

BACKGROUND Patient safety during anesthesia is crucially dependent on the monitoring of vital signs. However, the values obtained must also be perceived and correctly classified by the attending care providers. To facilitate these processes, we developed Visual-Patient-avatar, an animated virtual model of the monitored patient, which innovatively presents numerical and waveform data following user-centered design principles. After a high-fidelity simulation study, we analyzed the participants’ perceptions of 3 different monitor modalities, including this newly introduced technique. OBJECTIVE The aim of this study was to collect and evaluate participants’ opinions and experiences regarding 3 different monitor modalities, which are Visual-Patient-avatar, Split Screen (avatar and Conventional monitor alongside each other), and Conventional monitor after using them during simulated critical anesthetic events. METHODS This study was a researcher-initiated, single-center, semiquantitative study. We asked 92 care providers right after finishing 3 simulated emergency scenarios about their positive and negative opinions concerning the different monitor modalities. We processed the field notes obtained and derived the main categories and corresponding subthemes following qualitative research methods. RESULTS We gained a total of 307 statements. Through a context-based analysis, we identified the 3 main categories of “Visual-Patient-avatar,” “Split Screen,” and “Conventional monitor” and divided them into 11 positive and negative subthemes. We achieved substantial interrater reliability in assigning the statements to 1 of the topics. Most of the statements concerned the design and usability features of the avatar or the Split Screen mode. CONCLUSIONS This study semiquantitatively reviewed the clinical applicability of the Visual-Patient-avatar technique in a high-fidelity simulation study and revealed the strengths and limitations of the avatar only and Split Screen modality. In addition to valuable suggestions for improving the design, the requirement for training prior to clinical implementation was emphasized. The responses to the Split Screen suggest that this symbiotic modality generates better situation awareness in combination with numerical data and accurate curves. As a subsequent development step, a real-life introduction study is planned, where we will test the avatar in Split Screen mode under actual clinical conditions.