Health Information Processing System for Data Integration
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Solution Overview
Problem
Current health data processing systems are fragmented and siloed, lacking a cohesive platform for individuals to manage and control their health data, leading to inefficiencies and a lack of meaningful insights.
Innovation Solution
A health information processing system that establishes unique accounts for users, connects to multiple health data sources, and standardizes data formats, while also providing data cleaning, sharing preferences management, and personalized health insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system connects to multiple health data sources, then data accessibility is improved, but device complexity increases
Solution Approach 1:
The patent introduces a centralized health information processing system as an intermediary between users and multiple health data sources. This intermediary system automatically manages connections to various data sources (electronic health records, lab results, wearable devices), handling authentication and data retrieval without requiring users to directly interact with each source. The intermediary abstracts the complexity of multiple APIs and authentication mechanisms into a unified interface.
Solution Approach 2:
The system implements a universal data collection framework that can interface with multiple types of health data sources through standardized protocols. The same core system handles diverse data types (structured clinical data, unstructured notes, sensor data) and multiple sources (hospitals, labs, wearables) through a common architecture, eliminating the need for separate specialized systems for each data source.
2Productivity
If the system standardizes data formats, then data processing efficiency is improved, but loss of information may occur
Solution Approach 1:
The patent segments the data standardization process into distinct stages: data collection in original formats, data validation against schemas, transformation to standardized representations, and storage. By separating these functions, the system can preserve original data fidelity during collection and validation while applying standardization only during transformation and storage, minimizing information loss.
Solution Approach 2:
The system creates standardized copies of health data while preserving the original data sources. The standardization process generates normalized representations (copies) that can be efficiently processed and queried, while the original unstandardized data remains accessible for reference and for cases where standardization would lose important nuances or contextual information.
3Reliability
If the system provides data cleaning functions, then data integrity is improved, but processing time increases
Solution Approach 1:
The patent implements data cleaning and validation operations during the data ingestion phase before data is stored and made available for analysis. By performing cleaning actions (removing duplicates, validating formats, correcting obvious errors) upstream during collection, the system prevents dirty data from entering the storage and analysis pipelines, reducing the need for time-consuming cleaning operations later in the data lifecycle.
Solution Approach 2:
The system continuously monitors data quality metrics and performs automated cleaning operations in real-time as data streams in from various sources. Rather than batch processing all data cleaning tasks after collection, the system maintains continuous cleaning operations that run concurrently with data ingestion, minimizing overall processing time while ensuring ongoing data integrity.
4Ease of operation
If the system establishes unique user accounts, then user control over data is improved, but device complexity increases
Solution Approach 1:
The patent implements self-service features where users can independently manage their own health information accounts, grant or revoke access to third-party applications, and control data sharing preferences without requiring administrative intervention. The system provides user-friendly interfaces for data management while automatically handling the technical complexity of authentication tokens, permission scopes, and data routing behind the scenes.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for health information process. In one aspect, a system enables the collection of user specific health data from multiple different sources. —Account logins to multiple different sources are managed by the system. Data are cleaned in an intelligent and efficient manner. Sharing levels for different portions of data are set and the portions of data can be shared according to the share levels. Users can be queried when health metric values deviate from a baseline, and the responses can be used to determine potential causes of the deviations.