Dictionary Data Filter for Correcting Misidentified Patient Identifiers
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Solution Overview
Problem
Managing unstructured user data with varying terms across regions and industries leads to inconsistencies in data interpretation, complicating retrieval, analysis, and integration, exacerbated by the growing volume of digital data and the need for real-time processing.
Innovation Solution
An apparatus and method for generating a dictionary data filter using a processor to identify patient identifiers, generate a dictionary data filter, and modify misidentified patient identifiers, leveraging contextual data and localized terms through natural language processing and machine learning to enhance data interpretation and standardization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional data processing methods are used to manage unstructured user data with varying terms across regions and industries, then data processing can be performed with simple methods, but data interpretation consistency deteriorates and retrieval, analysis, and integration become complicated
Solution Approach 1:
The system transforms unstructured data with varying regional and industry terms into structured data by applying standardized parameters and taxonomic classifications. This allows the data to maintain its original diversity while being processed through consistent standardized frameworks, resolving the contradiction between handling diverse terms and ensuring interpretation consistency.
Solution Approach 2:
The patent introduces an intermediary standardized taxonomy system that acts as a bridge between diverse regional/industry terms and uniform data processing requirements. This intermediary layer enables consistent data interpretation without requiring changes to the original diverse data sources, maintaining both ease of operation and reliability.
2Reliability
If sophisticated methods for data structuring and retrieval are implemented to improve data interpretation consistency, then data retrieval and integration improve, but system complexity increases
Solution Approach 1:
The system segments the complex task of data standardization into distinct modular components: term identification, taxonomy mapping, and structured data generation. Each module handles a specific aspect of the standardization process, making the overall system more manageable and less complex while maintaining high data interpretation consistency.
Solution Approach 2:
The patent creates a universal standardized taxonomy framework that can handle multiple types of unstructured data across different regions and industries through a single unified system. This multi-functional approach reduces system complexity by eliminating the need for separate processing systems for different data types.
3Productivity
If real-time data processing is implemented to meet growing data volume requirements, then data processing speed improves, but data interpretation accuracy may deteriorate due to processing complexity
Solution Approach 1:
The system performs preliminary structuring and standardization of unstructured data before main processing operations. By pre-applying taxonomy mappings and structured formats to data in advance, the system enables faster real-time processing without sacrificing interpretation accuracy, as the data is already organized when rapid processing is needed.
Data Source
AI summary
An apparatus for generating a dictionary data filter for data deidentification is disclosed. The apparatus includes at least processor and a memory communicatively connected to the processor. The memory instructs the processor to receive a plurality of user data. The memory instructs the processor to generate contextual data as a function of the plurality of user data. The memory instructs the processor to identify a plurality of patient identifiers and a plurality of localized terms within the plurality of user data. The memory instructs the processor to generate a dictionary data filter as a function of the plurality of localized terms. The memory instructs the processor to identify one or more misidentified patient identifiers within the plurality of patient identifiers using the dictionary data filter. The memory instructs the processor to modify the plurality of patient identifiers as a function of the one or more misidentified patient identifiers.