Semantic Health Data Integration for Chronic Condition Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current health monitoring systems for chronic conditions fail to effectively integrate and utilize both objective and subjective health data, leading to limitations in data-driven applications, reliability, and explainability of clinical decisions due to the lack of dynamic and personalized capture of subjective health measurements.
Innovation Solution
A computer-based method and system that combines objective and subjective health data using a processor to generate comprehensive assessments and explanations, dynamically triggering ecological momentary assessments based on patient context, enhancing the semantic integration and representation of health data for improved AI-based predictions and user engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only objective health data from sensors is used, then measurement precision is improved, but the reliability and explainability of clinical decisions deteriorate due to lack of subjective context
Solution Approach 1:
The patent combines objective health data from sensors with subjective health data from ecological momentary assessments into a unified health model. This merging allows the system to maintain the precision of objective measurements while incorporating the contextual reliability of subjective patient reports, thereby resolving the contradiction between measurement precision and clinical decision reliability.
Solution Approach 2:
The system introduces an intermediary layer that correlates sensor data with subjective assessments. This intermediary processing layer matches objective measurements with corresponding subjective contexts (e.g., matching step count data with patient-reported energy levels), enabling reliable clinical decisions that preserve measurement precision while adding contextual validity.
2Productivity
If comprehensive health monitoring is implemented, then productivity in health management is improved, but device complexity increases due to integration of multiple data sources
Solution Approach 1:
The patent implements a universal health monitoring system that handles multiple data types (sensor data, subjective assessments, health outcomes) through a single integrated platform. This multi-functional approach improves health management productivity by consolidating diverse monitoring tasks while managing complexity through unified data processing and correlation mechanisms.
3Loss of information
If subjective health assessments are captured dynamically, then the semantic integration of health data is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The system performs preliminary actions by pre-defining assessment triggers and correlation rules before data collection begins. Ecological momentary assessments are triggered based on predetermined conditions (e.g., after sensor-detected events), and the system pre-establishes mapping relationships between objective and subjective data types. This preliminary structuring reduces the difficulty of detecting and measuring subjective health while maintaining high semantic integration quality.
Data Source
AI summary
A method for the semantic understanding of subjective and objective health data in systems for supporting the self-management of a user with at least one chronic condition, said system providing health assessment to the user related to the at least one chronic condition, wherein said method at least involves using a first module for combining user's objective health data and user's subjective health data, a second module for producing an assessment to the user and a third module for generating an explanation to the user, the method carried out by at least one processor, said method comprising: a) receiving by the at least one processor a plurality of first health parameters of a user, wherein said first health parameters denote user's objective health data and wherein at least one of the first health parameters represents data measured by an external device; and b) receiving by the at least one processor a plurality of second health parameters of a user, wherein said second health parameters comprise at least one subjective health measurement; wherein said at least one subjective health measurement denotes a perception of the user's subjective health; and c) combining by the first module in the at least one processor the objective health data and the subjective health data; and d) producing by the second module in the at least one processor, at least one health related assessment to the user comprising content data, said assessment based on the combined objective and subjective health data; and wherein said producing uses artificial intelligence methods; and e) generating by the third module in the at least one processor, at least one explanation to the user, wherein said explanation is related to the produced assessment; and f) providing the at least one assessment and the at least one explanation to the user.