Information processing device, information processing method, and storage medium
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Solution Overview
Problem
The accuracy of predicting changes in physiological parameters varies depending on the patient's age, disease, and the medical practitioner's experience, leading to inconsistent treatment outcomes in medical institutions.
Innovation Solution
An information processing device and method that analyzes the relationship between patient and medical practitioner information, measurement data, and prediction data to determine the degree of divergence, providing analysis information that reflects the prediction accuracy for each category of patients and practitioners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If medical practitioners predict physiological parameters based on their experience and judgment, then treatment decisions can be made promptly, but prediction accuracy varies significantly depending on practitioner experience and patient characteristics
Solution Approach 1:
The patent segments the prediction accuracy analysis by dividing practitioners into different experience levels (e.g., junior, intermediate, senior) and patients into different categories (e.g., by age, disease type, physiological parameter). This segmentation allows for targeted analysis of prediction accuracy across different groups, identifying specific patterns and tendencies without requiring a single complex universal model.
Solution Approach 2:
The system implements feedback by comparing predicted physiological parameter values with actual measured values over time. The analysis unit calculates prediction accuracy metrics and feeds this information back to identify tendencies in different practitioner-patient combinations. This feedback loop enables continuous improvement of prediction reliability by learning from past performance patterns.
2Loss of information
If detailed subject information including patient and practitioner data is collected and analyzed, then prediction accuracy tendencies can be identified, but information processing complexity and data management burden increase
Solution Approach 1:
The patent extracts only the essential subject information needed for analysis, such as practitioner experience level, patient category, predicted parameter values, and actual measured values. Rather than processing all possible data, the system focuses on extracting and analyzing the specific elements that contribute to prediction accuracy tendencies, reducing data processing complexity while maintaining analytical value.
Solution Approach 2:
The analysis unit is designed with multi-functionality to handle various types of subject information simultaneously. It can analyze prediction accuracy across different practitioner experience levels, patient categories, and physiological parameters using a unified analysis framework. This universal approach reduces the need for separate processing systems for different data types.
Data Source
AI summary
An information processing device includes an acquisition unit configured to acquire subject information including at least one of information about a patient and information bout a medical practitioner, measurement information about a physiological parameter of the patient, and prediction information about the physiological parameter of the patient predicted by the medical practitioner, an analyzing unit configured to analyze a relationship between the subject information and a degree of divergence between the prediction information and the measurement information, and an output that configured to output analysis information representing the relationship between the subject information and the degree of divergence.