Using Visual Patient Heart to improve anaesthesia professionals’ ECG Interpretation and Arrhythmia Situation Awareness: A Quantitative Study

Background The Visual Patient concept is a patient monitoring technology that transforms numerical and waveform data into an intuitive, avatar-based representation of the patient’s condition. Previous studies have shown that it enhances care providers’ situation awareness compared to conventional monitoring alone. Rapid recognition and response to cardiac pathologies are essential in acute care settings. Visual Patient Heart (VPH) expands this concept by integrating an established algorithm-based rhythm and ischemia analysis into a novel visual model for cardiac monitoring. Methods In this computer-based study, 75 anaesthesia care providers from four academic university hospitals in Central Europe assessed randomised sequences of standardised 12-lead ECG displays and corresponding VPH visualisations. Each sequence was presented for six seconds, reflecting the average glance duration observed in perioperative settings and simulating real-time constraints in clinical decision-making. The VPH representations were based on detections made by the Philips “ST/AR algorithm” , an automated system for arrhythmia and ST-segment analysis. Quantitative outcomes included diagnostic correctness, self-rated decision confidence and perceived workload, measured using a modified NASA Task Load Index (NASA-TLX) questionnaire. Results VPH significantly improved diagnostic correctness compared to conventional 12-lead ECG interpretation (78% vs. 42%, p < 0.001), with an odds ratio of 6.06 (95% confidence interval, 4.79–7.66) from the mixed logistic model. It also increased decision confidence and reduced perceived workload (both p < 0.001). Conclusion This study demonstrates that the VPH concept may enhance healthcare providers’ ability to recognise cardiac pathologies with greater confidence and lower cognitive burden. The findings support the potential of avatar-based visualisation as a complementary tool in patient monitoring.