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A visual interactive analytic tool for filtering and summarizing large health data sets coded with hierarchical
Xia Jing1, Matthew Emerson2, David Masters2
1College of Health Science and Professions, Grover Center W357, Ohio University, Athens, OH, 45701, USA. xia.xjing@gmail.com.
BMC Medical Informatics and Decision Making
|February 16, 2019
Summary
A new tool, VIADS, helps analyze large health datasets coded with terminologies like ICD-10 and MeSH. It filters, summarizes, and visualizes data, aiding clinical and research decisions.
Area of Science:
- Health Informatics
- Data Visualization
- Clinical Decision Support
Background:
- Electronic health records and literature databases generate vast amounts of hierarchical data (e.g., ICD-10-CM, MeSH).
- Current methods for understanding large datasets are limited, challenging human comprehension.
- New tools are needed to effectively filter and summarize complex health data.
Purpose of the Study:
- To develop VIADS (Visual Interactive Analytic Tool for filtering and summarizing large health data sets coded with hierarchical terminologies).
- To create an online, publicly accessible tool for data filtering, summarization, and insight extraction.
- To enable comparison and highlighting of differences between health datasets for informed decision-making.
Main Methods:
- Development of VIADS using Django, Python, JavaScript, Vis.js, Graph.js, JQuery, Plotly, Chart.js, Unittest, R, and MySQL.
- Implementation of six core modules: user account management, data validation, data analytics, data visualization, terminology, and dashboard.
- Support for health datasets coded with ICD-9, ICD-10, and MeSH terminologies.
Main Results:
- Successful development and public accessibility of the VIADS beta version.
- VIADS offers enhanced visualization through interactive features like zoom, customizable layouts, node information display, and 3D plots.
- Efficient screen space utilization in data visualization.
Conclusions:
- VIADS successfully meets its design objectives for filtering, summarizing, comparing, and visualizing large health datasets coded with hierarchical terminologies.
- The tool supports data coded by ICD-9, ICD-10, and MeSH.
- Future usability studies will detail end-user impact on clinical, research, and administrative decision-making.
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