Human-centered visualization technologies for patient monitoring are the future: a narrative review

Gasciauskaite, Greta; Lunkiewicz, Justyna; Roche, Tadzio R.; Spahn, Donat R.; Nöthiger, Christoph B.; Tscholl, David W. · 2023 · Crossref

DOI: 10.1186/s13054-023-04544-0

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Summary

This narrative review addresses the challenge of information overload in perioperative and intensive care medicine, where increasing data density from patient-monitoring devices strains clinicians’ cognitive capacity. Traditional monitoring relies on a technology-centered, single-sensor–single-indicator model, displaying parameters as isolated numbers and waves. This approach forces providers to manually integrate disparate data points, leading to high cognitive and emotional loads that can impair situation awareness and patient safety. The paper argues for a shift toward user-centered visualization technologies that integrate multiple data streams into single, intuitive indicators, such as avatars, to align with human sensory perception and cognitive processing capabilities. The authors ground their argument in cognitive psychology and neuroscience, specifically citing Gestalt principles of perception and dual-processing theory. These frameworks suggest that humans process visual information—such as changes in shape, color, and animation—more efficiently than numerical data, engaging fast, associative thinking (System 1) rather than slow, rational reasoning (System 2). The review synthesizes evidence from computer-based simulations, high-fidelity simulations, eye-tracking studies, and retrospective observational studies involving various user-centered technologies. Key systems analyzed include Philips Visual Patient (an avatar-based vital sign monitor), AlertWatch (a decision-support system for intraoperative care), Hamilton Medical’s Dynamic Lung panel, Mindray’s HemoSight, and emerging tools like Visual Clot and Visual Blood developed by the authors’ research group. The findings indicate that user-centered visualization technologies significantly improve clinical performance metrics compared to conventional monitoring. Studies on Visual Patient demonstrated increased diagnostic confidence, reduced perceived workload, and higher rates of verbalizing emergency causes. Eye-tracking data revealed that clinicians detected significantly more vital sign changes using peripheral vision with Visual Patient than with standard monitors. AlertWatch:OR was associated with improved process measures, including better glycemic management and reduced fluid administration. Similarly, Visual Clot enabled anesthetists to identify correct therapies for coagulation issues 2.2 times more likely and with lower cognitive workload than when interpreting standard rotational thromboelastometry results. Visual Blood also showed superior diagnostic accuracy and confidence for arterial blood gas interpretation. The authors conclude that while these technologies enhance situation awareness and decision-making, they currently serve as supplements rather than replacements for standard monitoring due to limitations in data precision and the inability to display trends. The review highlights the need for external validation and studies demonstrating patient outcome benefits. Future directions include integrating these visualizations into holistic models, incorporating machine learning predictions, and utilizing augmented or virtual reality platforms to provide comprehensive, intuitive patient status representations that optimize human-computer interaction in critical care settings.

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