Curating and Integrating Data from Multiple Sources to Support Healthcare Analytics

Area of Science:

• Health Informatics
• Data Science
• Bioinformatics

Background:

• Growing volume and variety of healthcare data present challenges for analysis.
• Effective data collection, curation, and integration are crucial for healthcare analytics.

Purpose of the Study:

• To describe the development of a robust infrastructure for healthcare data management.
• To highlight experiences in building a system supporting healthcare analytics.

Main Methods:

• Developed a data collection, curation, and integration infrastructure.
• Applied the system to diverse data types: EHR, observational, genomic, microbiomic, survey, and wearable device data.
• Processed data from over 600 subjects.

Main Results:

• Successfully processed a wide range of healthcare data types.
• The infrastructure supports the integration of disparate data sources.
• The curated data is ready for advanced analytical applications.

Conclusions:

• The developed infrastructure is effective for managing diverse healthcare data.
• This system enables advanced healthcare analytics, including visualization, patient stratification, and predictive modeling.
• Robust data infrastructure is key to unlocking the potential of healthcare data.