Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
11 04 2023
Historique:
received: 12 07 2022
accepted: 06 04 2023
medline: 13 4 2023
entrez: 11 4 2023
pubmed: 12 4 2023
Statut: epublish

Résumé

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.

Identifiants

pubmed: 37041316
doi: 10.1038/s41598-023-33027-z
pii: 10.1038/s41598-023-33027-z
pmc: PMC10088750
doi:

Types de publication

Multicenter Study Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

5908

Informations de copyright

© 2023. The Author(s).

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Auteurs

Lisa Bergauer (L)

Institute of Anaesthesiology, University of Zurich and University Hospital Zurich, Zurich, Switzerland.

Julia Braun (J)

Department of Epidemiology and Biostatistics, University of Zurich, Zurich, Switzerland.

Tadzio Raoul Roche (TR)

Institute of Anaesthesiology, University of Zurich and University Hospital Zurich, Zurich, Switzerland. Tadzioraoul.roche@usz.ch.

Patrick Meybohm (P)

Department of Anaesthesiology, Intensive Care, Emergency and Pain Medicine, University Hospital Wuerzburg, University of Wuerzburg, Wuerzburg, Germany.

Sebastian Hottenrott (S)

Department of Anaesthesiology, Intensive Care, Emergency and Pain Medicine, University Hospital Wuerzburg, University of Wuerzburg, Wuerzburg, Germany.

Kai Zacharowski (K)

Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany.

Florian Jürgen Raimann (FJ)

Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt, Germany.

Eva Rivas (E)

Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.

Manuel López-Baamonde (M)

Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.

Michael Thomas Ganter (MT)

Institute of Anaesthesiology and Critical Care Medicine, Clinic Hirslanden Zurich, Zurich, Switzerland.

Christoph Beat Nöthiger (CB)

Institute of Anaesthesiology, University of Zurich and University Hospital Zurich, Zurich, Switzerland.

Donat R Spahn (DR)

Institute of Anaesthesiology, University of Zurich and University Hospital Zurich, Zurich, Switzerland.

David Werner Tscholl (DW)

Institute of Anaesthesiology, University of Zurich and University Hospital Zurich, Zurich, Switzerland.

Samira Akbas (S)

Institute of Anaesthesiology, University of Zurich and University Hospital Zurich, Zurich, Switzerland.

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