Overcoming Barriers in Healthcare Data Aggregation for Value-Based Care
The aggregation of healthcare data is hindered by fragmented systems, poor data quality, and integration issues.
However, solutions such as single data models, lakehouse architecture, AI-driven curation, and real-time processing can help overcome these barriers.
- Preserves original information
- Progressive improvement through curation
- Fast queries for clinical applications
- Handles structured and unstructured data
The data pipeline starts with raw data from source systems, which is refined through multiple stages of sophisticated curation processes.
Raw data becomes actionable through AI analysis.
The final result is a dynamic longitudinal patient record that updates as new information arrives, enabling predictions and implementation of value-based care models.
Author's summary: Advanced curation creates a single longitudinal patient record.