Diagnosis Support System for Patient Information Segmentation
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Solution Overview
Problem
In team medical-care settings, the sheer volume of information collected from multiple healthcare professionals makes it difficult to access and determine important patient data, leading to information overload and challenges in holistic patient understanding.
Innovation Solution
A diagnosis support system that acquires and analyzes medical data using natural language processing to extract biomedical and psychosocial information, calculating an information amount for each item and displaying it in a format that highlights important patient views, preferences, and values, facilitating a comprehensive patient understanding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple healthcare professionals collect information from various viewpoints, then the comprehensiveness of patient understanding is improved, but the quantity of information increases leading to information overload
Solution Approach 1:
The patent segments the large volume of patient information into categorized groups (biomedical information, psychosocial information, treatment information, etc.) and presents them in an organized hierarchical structure. This allows healthcare professionals to access comprehensive patient data while avoiding information overload through systematic categorization and selective display.
2Loss of information
If all collected patient information is gathered together, then the completeness of patient data is improved, but the time required to confirm and access appropriate data increases
Solution Approach 1:
The system performs preliminary organization and categorization of patient information before it needs to be accessed. Information is pre-structured into meaningful categories with key findings highlighted and summarized, allowing healthcare professionals to quickly locate and confirm appropriate data without manually searching through all collected information.
Solution Approach 2:
The patent extracts and highlights key patient information and important findings from the complete dataset, presenting them prominently while making the full detailed information available on demand. This extraction of essential data allows rapid confirmation of critical information while maintaining access to complete patient data when needed.
3Measurement precision
If comprehensive patient information from various sources is integrated, then the accuracy of treatment policy determination is improved, but the complexity of the system increases
Solution Approach 1:
The system segments comprehensive patient information into distinct categorical groups (biomedical, psychosocial, treatment, etc.) with clear organizational structures. This segmentation maintains data integrity and accuracy for treatment policy determination while reducing perceived complexity through systematic arrangement and hierarchical presentation.
Data Source
AI summary
A diagnosis support system includes an acquirer, a calculator, and a display controller. The acquirer acquires diagnosis data. The calculator calculates, based on the medical data, a feature amount in the medical data for a predetermined period. The display controller causes the displayer to display the medical data in a format according to the feature amount.