Echo: A Large Display Interactive Visualization of ICU Data for Effective Care HandOffs.

Area of Science:

• Medical Informatics
• Human-Computer Interaction
• Clinical Data Visualization

Background:

• Care transitions in Intensive Care Units (ICUs) lack effective tools for clinicians to manage and transfer patient information.
• Outgoing clinicians struggle to find, filter, organize, and annotate critical data for incoming teams.

Purpose of the Study:

• To develop and evaluate an interactive visual approach to support clinicians during ICU care transitions.
• To enhance the process of information handoff between clinical teams.

Main Methods:

• Characterized the problem domain through observations at University of Illinois Hospital and interviews with biomedical researchers and ICU clinicians.
• Designed a scalable, interactive visualization supporting overview and detail views, anomaly detection, comparison, and data annotation.
• Implemented and demonstrated the visualization on an anonymized ICU dataset using a large display.

Main Results:

• The developed visual approach supports both overview and detailed views of patient data.
• Features include anomaly detection, data comparison, and annotation capabilities.
• Domain expert feedback confirmed the approach meets requirements for effective care transitions.

Conclusions:

• The interactive multivariate visual approach effectively supports clinicians during ICU care transitions.
• This tool addresses the critical need for better information management and handoff during patient transfers.
• The visualization system shows promise for improving patient safety and care continuity in ICUs.