QualDash: Adaptable Generation of Visualisation Dashboards for Healthcare Quality Improvement

Area of Science:

• Health Informatics
• Data Visualization
• Human-Computer Interaction

Background:

• Designing adaptable dashboards for healthcare quality improvement (QI) presents challenges due to diverse metrics, data models, and users.
• Balancing dashboard adaptability with ease-of-use is a key consideration in visualization research.

Purpose of the Study:

• To present QualDash, a novel dashboard generation engine for dynamic configuration and deployment of visualization dashboards in healthcare QI.
• To address the need for adaptable and user-friendly dashboards in complex hospital environments.

Main Methods:

• Conducted a rigorous task analysis involving interviews with healthcare professionals and co-design workshops.
• Developed a metric card metaphor and a Metric Specification Structure (MSS) using JSON for flexible dashboard configuration.
• Deployed and iterated QualDash in cardiology and pediatric intensive care units across five NHS hospitals.

Main Results:

• QualDash enables dynamic configuration and deployment of adaptable visualization dashboards for healthcare QI.
• The metric card metaphor and MSS facilitate concise configuration of unit-specific metric variants.
• Evaluation demonstrated QualDash's adaptability, ease-of-use, and usefulness in real-world hospital settings.

Conclusions:

• QualDash offers a viable solution for generating adaptable and user-friendly dashboards in healthcare quality improvement.
• The metric card metaphor and MSS provide a flexible framework for dashboard customization in diverse clinical contexts.
• The study highlights the successful application of QualDash in NHS hospitals, demonstrating its practical utility.