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VIEWER: an extensible visual analytics framework for enhancing mental healthcare.

Tao Wang1, David Codling2, Yamiko Joseph Msosa1

  • 1Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, United Kingdom.

Journal of the American Medical Informatics Association : JAMIA
|January 23, 2025
PubMed
Summary

The Visual & Interactive Engagement With Electronic Records (VIEWER) toolkit enhances clinical data analysis, improving task completion speed and user satisfaction. This system offers a cost-effective solution for better healthcare informatics and patient care.

Keywords:
electronic health recordhealth informaticsmental healthnatural language processingvisual analytics

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Area of Science:

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

Background:

  • Standard clinical information systems often lack advanced capabilities for visualizing and interacting with complex patient data.
  • Effective clinical data analysis is crucial for improving patient monitoring and population health management.

Purpose of the Study:

  • To design, implement, and evaluate Visual & Interactive Engagement With Electronic Records (VIEWER), an open-source toolkit for clinical data visualization.
  • To assess the effectiveness of VIEWER in improving the retrieval, analysis, and visualization of clinical information at the point of care.

Main Methods:

  • Utilized natural language processing and interactive visualization techniques for VIEWER development.
  • Employed a collaborative, participatory design approach within a large UK National Health Services mental health Trust.
  • Assessed clinical utility and effectiveness using quantitative and qualitative methods with over 1000 users.

Main Results:

  • VIEWER offers interactive, comprehensive views of longitudinal patient data (n=409,870) from structured and unstructured sources.
  • Significantly improved performance and task completion speed compared to standard systems, despite a short adoption period.
  • Users reported high satisfaction and strong interest in integrating VIEWER into daily practice.

Conclusions:

  • VIEWER serves as a cost-effective enhancement to standard clinical information systems, improving data accessibility and representation.
  • Collaborative refinement of health informatics solutions like VIEWER is key to optimizing patient care.
  • The toolkit supports diverse healthcare applications, including population health management and patient monitoring.