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RHEA: Real-World Observational Health Data Exploration Application
Soobeen Seol1, Jimyung Park1, Chungsoo Kim1
1Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Republic of Korea.
Studies in Health Technology and Informatics
|January 25, 2024
Summary
We created RHEA, a framework for tracking cancer patient status over time. RHEA visualizes patient data using a standardized format, aiding in comprehensive cancer research and patient management.
Area of Science:
- Oncology
- Health Informatics
- Data Visualization
Background:
- Longitudinal patient data is crucial for understanding cancer progression and treatment efficacy.
- Standardized data representation is needed to facilitate large-scale analysis and collaboration in cancer research.
Purpose of the Study:
- To introduce RHEA, a novel framework for representing and visualizing longitudinal cancer patient data.
- To enable cohort-level and individual-level data visualization for cancer patients.
- To facilitate cohort generation based on standardized data.
Main Methods:
- Development of a standardized framework named RHEA.
- Implementation of data visualization using the Observational Medical Outcomes Partnership-Common Data Model (OMOP-CDM).
- Design of a dashboard with three components: cohort-level visualization, individual-level visualization, and cohort generation.
Main Results:
- RHEA provides a standardized approach to represent longitudinal cancer patient status.
- The RHEA dashboard effectively visualizes patient data at both cohort and individual levels.
- The framework supports the generation of patient cohorts for research.
Conclusions:
- RHEA offers a valuable tool for researchers and clinicians managing longitudinal cancer patient data.
- Standardized visualization through RHEA enhances the understanding of cancer patient characteristics and progression.
- The framework promotes efficient cohort identification and analysis in cancer research.
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