Integrated Data Repository for Genomics and Claims Analysis
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Solution Overview
Problem
Existing systems inefficiently and inaccurately analyze unstructured healthcare data, particularly health insurance claims data and genomic data, leading to suboptimal treatment of individuals.
Innovation Solution
An integrated data repository that combines structured health insurance claims data with molecular data, using hash functions and logical links to create anonymized datasets for accurate analysis, enabling precise treatment insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems analyze unstructured healthcare data, then data analysis is performed, but the analysis is inefficient and inaccurate
Solution Approach 1:
The system segments unstructured healthcare data into distinct structured components including patient demographic data, clinical data, billing data, and insurance claims data. Each segment is processed and stored in separate tables within the data warehouse, enabling efficient querying and analysis of specific data types without processing the entire unstructured dataset.
Solution Approach 2:
The patent introduces an intermediary data warehouse layer between the unstructured source systems and the analysis systems. This intermediary structure standardizes and organizes data from multiple sources using consistent schemas and data models, enabling accurate and efficient analysis while isolating the complexity of data integration from the analysis processes.
2Loss of information
If multiple sources of healthcare data are integrated, then comprehensive health information is obtained, but data integration complexity increases
Solution Approach 1:
The system implements a universal data warehouse architecture that can accommodate multiple sources of healthcare data including electronic health records, billing systems, insurance claims, and genomic data. A standardized data model and common schema enable the system to integrate diverse data types through a single unified structure, reducing integration complexity while maintaining information completeness.
Solution Approach 2:
The patent applies parameter changes by transforming data from various sources into a standardized format with consistent data types, schemas, and validation rules. This transformation process converts heterogeneous data into homogeneous structured data that can be efficiently stored and queried, managing integration complexity while preserving comprehensive health information.
3Measurement precision
If health insurance claims data is analyzed, then treatment information is obtained, but data structure limitations reduce analysis accuracy
Solution Approach 1:
The system replaces the mechanical limitation of fixed insurance claims data structures with a flexible relational database schema. This substitution allows the system to capture detailed treatment information including procedures, medications, diagnoses, and outcomes in structured formats that support accurate analysis while managing data structure complexity through standardized tables and relationships.
Data Source
AI summary
An integrated data repository may be generated that includes genomics information and health insurance claims data information for a common group of individuals. A data processing pipeline may be implemented with respect to information stored by the integrated data repository. The data processing pipeline may include a number of sets of data processing instructions that are executable to analyze specified information stored by the integrated data repository and generate different datasets. The datasets may be analyzed to determine an impact of characteristics of individuals and/or an amount of impact of treatments provided to individuals in which a biological condition is present.