Automated Observation Data Extraction for Infectious Disease Monitoring
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Solution Overview
Problem
Existing medical information management systems are inadequate for efficiently and cost-effectively managing the continuous generation of observation data, particularly in the context of monitoring and analyzing the spread of infectious diseases, due to the high human and time costs associated with manual data collection and classification.
Innovation Solution
An information processing apparatus and method that includes a reception section to receive extraction conditions for patient observation data and an extraction section to automatically match and store relevant data in a database, utilizing natural language processing and structured data handling to facilitate efficient data extraction and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data collection and classification is used for continuously generated observation data, then data accuracy can be maintained, but enormous human and time costs are consumed
Solution Approach 1:
The patent replaces the mechanical manual data collection and classification system with an automated information processing apparatus that uses natural language processing and machine learning algorithms to extract and classify observation data from medical records, thereby eliminating human labor while maintaining data accuracy
Solution Approach 2:
The system enables self-service by allowing the information processing apparatus to automatically retrieve, parse, and classify observation data from multiple medical institutions without human intervention, with the capability to autonomously learn from new data patterns and improve classification accuracy over time
2Measurement precision
If manual data collection and classification is used for continuously generated observation data, then data quality can be ensured, but enormous human costs are consumed
Solution Approach 1:
The patent substitutes human operators with an automated information processing apparatus that uses natural language processing and machine learning to ensure data quality through consistent application of classification rules and algorithms, eliminating the need for human labor while maintaining or improving data quality standards
3Productivity
If automated data extraction is implemented, then productivity is improved, but system complexity increases
Solution Approach 1:
The patent introduces an information processing apparatus as an intermediary between medical institutions and analysis systems, which handles the complexity of data extraction, natural language processing, and classification internally while presenting a simple interface for data requests and results, thereby isolating system complexity from users
Data Source
AI summary
To cause observation data to be easily available. An information processing apparatus includes a reception section that receives designation of an extraction condition on observation data and an extraction section that, in a case where the designation is received, starts a process of extracting a piece of observation data which, among observation data that has been stored after reception of the designation, matches the extraction condition and storing the piece of observation data in a database. The observation data stored in the database can be used, for example, for decision making for a countermeasure against an infectious disease.