Healthcare Data Interchange System for Scalable Patient Record Matching
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Solution Overview
Problem
Current disease management programs rely on labor-intensive, manual, and un-scalable interventions, which are ineffective in addressing the rising healthcare challenges of declining population health and increasing chronic diseases, particularly in ensuring effective data integration and matching with patient records for delivering value-based care.
Innovation Solution
A health data system that integrates scalable technology into local healthcare infrastructure, utilizing a health data server with agent modules to poll health data from various sources, a switch module to match and tag data with unique identifiers, and interface modules for secure access, creating a common information model that includes clinical, laboratory, and remote monitoring data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual, siloed interventions are used for disease management, then labor-intensive care can be provided, but scalability and efficiency deteriorate
Solution Approach 1:
The patent replaces manual, mechanical data integration processes with an automated information model that automatically polls, matches, and integrates data from multiple sources. The system uses automated algorithms to match patient records across different data sources without human intervention, thereby eliminating the labor-intensive nature of manual disease management while enabling scalable operation across large patient populations.
Solution Approach 2:
The patent introduces an information model as an intermediary layer between multiple data sources and the disease management system. This intermediary automatically polls data from various sources, matches records using defined attributes, and integrates information into a unified view. This mediator enables scalable automation while maintaining the ease of operation through standardized interfaces and automated matching algorithms.
2Productivity
If data from multiple sources is integrated into a common information model, then data integration and matching efficiency improve, but system complexity increases
Solution Approach 1:
The patent segments the data integration system into distinct modular components: an information model that defines attributes and matching criteria, pollers that collect data from specific sources, and matchers that compare records. Each component has a specialized function, allowing the system to handle complex multi-source integration through manageable, independent modules that can be developed, maintained, and scaled separately.
Solution Approach 2:
The patent creates a universal information model that can handle multiple data sources and types through standardized attributes and matching criteria. The same matching framework works across different pollers and data sources, providing a multi-functional solution that improves productivity without proportionally increasing complexity, as the core matching logic remains consistent regardless of the number or type of integrated sources.
3Productivity
If automated polling and matching systems are implemented, then scalability and data integration improve, but manual control and simplicity are reduced
Solution Approach 1:
The patent implements a self-service automated system where the information model independently polls data sources, matches patient records, and integrates information without requiring manual control. The system uses predefined matching criteria and attributes to automatically determine record correspondence, enabling scalable operation while reducing the need for manual intervention. Operators can configure matching criteria once, and the system handles ongoing integration autonomously.
Data Source
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AI summary
A health data system that is part of a scalable technology core that can be integrated into local healthcare infrastructure to create a care management framework for delivering patient-centric and value-based care in a community, setting the stage for scalability to targeted communities.