A Visual Analytic Tool (VIADS) to Assist the Hypothesis Generation Process in Clinical Research: Mixed Methods...

Area of Science:

• Health Informatics
• Data Visualization
• Clinical Research

Background:

• Hierarchical data visualization aids comprehension and hypothesis generation.
• Overwhelming data can hinder effective visualization.

Purpose of the Study:

• Evaluate the usability of the Visual Interactive Analytic Tool for Filtering and Summarizing Large Health Data Sets (VIADS).
• Assess VIADS's effectiveness in visualizing patient diagnoses and procedures coded in ICD-9-CM.

Main Methods:

• Mixed-methods study involving 12 clinical researchers.
• Participants used VIADS for hypothesis generation within a 3-hour session (1-hour training, 2-hour study).
• Think-aloud protocol, remote recording, System Usability Scale (SUS), and open-ended surveys were employed.

Main Results:

• The mean SUS score for VIADS was 71.88 (SD 14.62), with a median of 75.
• 100% of participants agreed VIADS offers new perspectives; 75% found it facilitates data understanding and interpretation.
• Positive feedback highlighted VIADS's utility, aligning with design goals; suggestions for improvement were incorporated.

Conclusions:

• VIADS is a usable tool for analyzing secondary health data, offering good usability and favorable utility.
• Key appreciated functionalities include filtering, summarizing, comparing, and visualizing hierarchical data.
• While currently supporting specific use cases, VIADS provides valuable new perspectives and ease of use for data analysis.