Evidence map›Paper›PMID 42192398›Full record

ArticleBMC medical informatics and decision making2026

Anaesthesia professionals' perspectives on ECG interpretation and arrhythmia situation awareness with Visual Patient Heart: a qualitative multicentre study.

Max Ebensperger, Cynthia A Hunn, Tadzio R Roche, Arend Rahrisch, Achilles Delis, Florian Piekarski, Florian J Raimann, Sayeh Bagheri, Svenja Letz, Gregor Massoth and 2 more

Abstract readMulticenter Study
In one paragraph

Article in BMC medical informatics and decision making, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Max Ebensperger *Department of Anesthesiology and Intensive Care, TUM School of Medicine and Health, Technical University of Munich, Ismaningerstrasse 22, 81675, Munich, Germany.
Cynthia A Hunn *Institute of Anesthesiology and Perioperative Medicine, University of Zurich, University Hospital Zurich, Raemistrasse 100, Zurich, 8091, Switzerland.
Tadzio R RocheInstitute of Anesthesiology and Perioperative Medicine, University of Zurich, University Hospital Zurich, Raemistrasse 100, Zurich, 8091, Switzerland.
Arend RahrischInstitute of Anesthesiology and Perioperative Medicine, University of Zurich, University Hospital Zurich, Raemistrasse 100, Zurich, 8091, Switzerland.
Achilles DelisDepartment of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
Florian PiekarskiDepartment of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
Florian J RaimannDepartment of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Goethe University Frankfurt, University Hospital Frankfurt, Theodor- Stern-Kai 7, 60590, Frankfurt am Main, Germany.
Sayeh BagheriDepartment of Cardiology, University of Zurich and University Hospital Zurich, Raemistrasse 100, Zurich, 8091, Switzerland.
Svenja LetzDepartment of Anesthesiology and Intensive Care, TUM School of Medicine and Health, Technical University of Munich, Ismaningerstrasse 22, 81675, Munich, Germany.
Gregor MassothDepartment of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
Kai ZacharowskiDepartment of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Goethe University Frankfurt, University Hospital Frankfurt, Theodor- Stern-Kai 7, 60590, Frankfurt am Main, Germany.
David W TschollInstitute of Anesthesiology and Perioperative Medicine, University of Zurich, University Hospital Zurich, Raemistrasse 100, Zurich, 8091, Switzerland. david.tscholl@usz.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Visual Patient Avatar concept transforms conventional patient monitoring data into a dynamic, animated representation of the patient, enhancing situation awareness of vital signs and measurement status. Rapid recognition and response to cardiac pathologies are critical in anaesthesia and critical care. Visual Patient Heart (VPH) integrates cardiac data from the Philips "ST/AR algorithm", a feature in Philips patient monitors, into visual design elements inside the heart element of the Visual Patient Avatar, specifically aiming to improve situation awareness of arrhythmias and ST-segment deviations.

methodsParticipants evaluated a randomized series of 12-lead ECGs alongside corresponding VPH visualizations, each shown briefly to assess the speed of information transfer. Immediately after the exercise, they were asked two open-ended questions and encouraged to speak freely about perceived advantages and areas for improvement of the VPH concept. Their verbal responses were transcribed through field notes and analyzed using a template-guided analysis. The analysis of correct responses in the ECG-avatar comparison test is reported separately in a dedicated paper.

resultsAnalysis of 193 statements from 41 participants revealed that participants perceived VPH as intuitive, easy to learn, and cognitively less demanding than conventional ECG interpretation. Benefits reported by participants included improved situation awareness, faster rhythm recognition, and increased decision confidence. Suggestions for improvement addressed visual clarity, the need for more training, and integration with conventional ECG data. Concerns included over-reliance on the system and potential erosion of traditional ECG interpretation skills.

conclusionThe VPH system was well received, with participants highlighting its simplicity, clarity, and potential to enhance situation awareness. Feedback also raised important considerations around explainability, trust, and integration of the visuals with conventional ECGs. These findings support further development and evaluation in more complex, clinically realistic settings.

Indexed as

AnesthetistsArrhythmias, CardiacAttitude of Health PersonnelAwarenessElectrocardiographyAdultAvatarFemaleHumansMaleMiddle AgedQualitative ResearchDiagnosisPatient monitoringQualitative researchSituation awarenessVisual Patient Avatar

Identifiers

PMID42192398
PMCPMC13386552

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.