Disease-Specific Semantic Model Instance Processing
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Solution Overview
Problem
Existing healthcare systems struggle to create accurate, comprehensive, and relevant clinical documentation that captures a patient's overall health status and progression over time, due to the isolation of data points related to individual episodes of care.
Innovation Solution
A computer-implemented method and system that processes a disease-specific semantic model instance to generate a processed instance, allowing for the integration and analysis of diverse healthcare records to provide a comprehensive understanding of a patient's health.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If isolated data points are logged for individual episodes of care, then data storage and organization are simplified, but the ability to understand the patient's overall health status and disease progression is lost
Solution Approach 1:
The patent merges multiple isolated data points from different episodes of care into a unified disease-specific semantic model that preserves both individual data points and their collective meaning. The model integrates data from multiple sources and time periods while maintaining the ability to query both specific encounters and overall disease progression.
Solution Approach 2:
The patent implements a nested structure where individual episode data points are nested within a broader disease progression model. Each clinical encounter data point is contained within the semantic model instance, which itself is nested within a disease-specific model framework, allowing hierarchical querying from specific to general.
2Quantity of substance
If multiple healthcare records in disparate formats are accumulated over time, then the volume of health information increases, but the difficulty of integrating and analyzing these records increases
Solution Approach 1:
The patent transforms heterogeneous health records into a standardized semantic representation by changing the parameters of data storage from disparate formats to a unified disease-specific semantic model. This allows different data types and formats to be converted into a common framework that preserves meaning while enabling integration.
Solution Approach 2:
The patent introduces a disease-specific semantic model as an intermediary layer between raw healthcare records and analysis systems. This intermediary translates and standardizes data from multiple sources into a unified representation, simplifying integration while preserving the original data's informational content.
3Reliability
If clinical documentation is created to be comprehensive and accurate, then the quality of care and payment accuracy improve, but the challenge of making this information relevant and understandable to consumers and systems increases
Solution Approach 1:
The patent applies local quality by allowing different views and representations of the same data depending on the user's needs. The semantic model can present detailed comprehensive information for clinical accuracy while simultaneously providing summarized relevant information for ease of understanding, with each view optimized for its specific purpose.
Solution Approach 2:
The patent implements dynamic adaptability where the disease-specific semantic model can dynamically adjust its output based on the querying system's needs. The model can provide detailed comprehensive data when needed for clinical accuracy while providing simplified relevant summaries when needed for consumer understanding, making the system adaptable to different users and purposes.
Data Source
AI summary
A computer-implemented method and system are applied to a first instance of a first disease-specific semantic model. The method and system: receive a first request; process the first instance of the first disease-specific semantic model based on the first request to generate a first processed instance of the first disease-specific semantic model; and provide the first processed instance of the first disease-specific semantic model as output.