User perceptions of different monitor modalities during high-fidelity simulation: Visual-Patient-avatar, Split Screen and Conventional - a semiquantitative analysis (Preprint)

Abstract

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 participants' perceptions of three different monitor modalities, including this new technique.

This study was a researcher-initiated, single-center, semiquantitative study. We asked 92 care providers right after finishing three simulated emergency scenarios about their positive and negative opinions concerning the different monitor modalities. We processed the field notes obtained and derived main categories and corresponding subthemes following qualitative research methods.

We gained a total of 307 statements. Through a context-based analysis, we identified the three main categories “Visual-Patient-avatar”, “Split Screen” as well as “Conventional monitor” and divided them into eleven positive and negative subthemes. We achieved substantial inter-rater reliability in assigning the statements to one of the topics. Most of the statements concerned the design and usability features of the avatar or the Split Screen mode.

This study semiquantitatively reviewed the clinical applicability of the Visual-Patient-avatar technique in a high-fidelity simulation study and revealed strengths and limitations of the avatar only und Split Screen modality. In addition to valuable suggestions for improving the design, the requirement for training prior to clinical implementation was emphasized. 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.