Medical Variance Analysis Classification System
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Solution Overview
Problem
Current technologies face challenges in efficiently analyzing and refining the causes of variance between clinical pathways and actual medical care practices, failing to provide effective methods for detailed variance analysis and refinement suitable for various analysis purposes.
Innovation Solution
A medical information processing apparatus and method that includes an obtaining unit, an extracting unit, a classifying unit, and a display controlling unit, which obtain and classify data on medical actions and variances, generating association rules and displaying relevant factors for each classification criterion to refine and present the causes of variance effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive medical care data is collected and analyzed to identify variance causes, then the accuracy and detail of variance analysis is improved, but the complexity of the analysis system and processing time increases
Solution Approach 1:
The patent segments the variance analysis process into distinct functional units: an obtaining unit for collecting medical care data, an extracting unit for identifying variance causes, and a classifying unit for categorizing variances. This segmentation allows each unit to handle specific tasks independently, reducing overall system complexity while maintaining comprehensive analysis capability.
Solution Approach 2:
The patent introduces classification criteria as an intermediary mechanism between raw variance data and analysis results. The classifying unit uses predefined classification criteria to systematically categorize extracted variance causes, which simplifies the interpretation of complex medical care data and reduces the cognitive load on users.
2Adaptability or versatility
If detailed classification criteria are applied to categorize variance causes, then the usefulness and actionability of analysis results is improved, but the time required for classification and processing increases
Solution Approach 1:
The patent applies preliminary action by pre-defining classification criteria and categories before the actual variance analysis occurs. The classifying unit uses these predetermined criteria to automatically categorize variance causes as they are extracted, eliminating the need for manual classification and reducing processing time while maintaining detailed categorization capability.
3Adaptability or versatility
If multiple classification criteria are used to characterize clinical pathways, then the ability to address specific medical care challenges is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the classification process by applying different classification criteria to different aspects of variance analysis. Each classification criterion focuses on a specific dimension (e.g., variance type, cause category, clinical pathway phase), allowing the system to handle multiple classification requirements through modular, independent classification rules that reduce overall processing complexity.
Data Source
AI summary
A medical information processing apparatus according to an embodiment includes processing circuitry. The processing circuitry obtains data on medical actions and data on differences between planned medical actions or achievement objectives of treatment and results thereof. The processing circuitry extracts relevant factors associated with the differences based on the data on the medical actions and the data on the differences. The processing circuitry the relevant factors by allocating elements included in classification criteria to the relevant factors. The processing circuitry displays the relevant factors on a display for each of the classification criteria.