Health Plan System Mining Unstructured Narratives
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Solution Overview
Problem
Current health care systems for individuals with chronic diseases rely on limited structured data, failing to capture nuanced responses and alternative treatments, leading to incomplete health improvement plans.
Innovation Solution
A system that mines crowd-sourced structured and unstructured health data, including medical narratives and internet usage patterns, to create individualized treatment plans through an information management system with data extraction and analysis applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If only structured data from medical records and questionnaires is used, then data collection is simple and systematic, but the health improvement plans are incomplete and miss nuanced responses
Solution Approach 1:
The patent merges structured data from medical records and questionnaires with unstructured data from internet blogs and narratives. The system combines these diverse data sources into a unified analysis framework, allowing comprehensive health improvement plans that capture both systematic medical information and nuanced patient experiences from unstructured sources.
Solution Approach 2:
The system performs multiple functions: it collects structured medical data, extracts unstructured information from internet sources, analyzes both types of data, and generates personalized health plans. This multi-functional approach allows a single system to address both data collection simplicity and information completeness.
2Reliability
If crowd-sourced unstructured data is incorporated, then treatment plan comprehensiveness improves, but data processing complexity increases
Solution Approach 1:
The patent introduces an intermediary data extraction and analysis system that bridges unstructured crowd-sourced data and structured treatment planning. This intermediary layer processes raw unstructured information from blogs and narratives, extracting relevant health insights and transforming them into actionable treatment recommendations, thereby reducing the complexity burden on the overall system.
Solution Approach 2:
The system replaces manual analysis of unstructured data with automated computational methods. Natural language processing and data mining algorithms automatically extract meaningful information from crowd-sourced narratives and blogs, substituting manual review processes with scalable computational analysis that improves reliability without proportionally increasing complexity.
3Measurement precision
If multiple data sources are integrated, then individualized treatment accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the information management system into distinct functional modules: data collection from multiple sources, data extraction, data analysis, and treatment plan generation. Each module handles specific tasks independently, allowing the system to integrate multiple data sources for accurate personalization while managing complexity through modular architecture where each segment can be developed and maintained separately.
Data Source
AI summary
Embodiments of the invention include systems and methods for developing individualized health improvement plans including a system for data mining personal health data, structured health related information and unstructured medical narratives and storytelling to identify treatment plans and general techniques that individuals with chronic diseases/symptoms can use to improve their general health and well being.