Allergy Event Concept Mapping for Free-Text Deduplication

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Solution Overview

Problem

Existing healthcare systems face challenges in deduplicating allergy event data due to the use of alphanumeric codes and free text, leading to redundant and duplicate information across different healthcare providers, which complicates accurate patient allergy management.

Innovation Solution

A system that utilizes natural language processing to generate vector embeddings for both standard codes and free text, comparing them to recommend candidate standard codes for mapping and deduplicating allergy events, with a synchronization engine to automate the process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If allergy event data is stored using multiple different codes and free text from various sources, then data completeness and information richness are improved, but data redundancy and duplication increase

Engineering Contradiction:

Improvedata completenessVSAvoiddata redundancy

Core Design Contradiction:

Quantity of substanceVSLoss of substance

Solution Approach 1:

The system performs preliminary mapping of allergy free text to standard codes before deduplication occurs. By pre-processing the free text data and associating it with standardized codes in advance, the system enables more effective duplicate detection and elimination, thus reducing redundancy while preserving complete allergy information.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces standard codes as an intermediary between diverse free text representations of allergies. This intermediary standardization layer enables different free text descriptions to be mapped to common codes, facilitating duplicate identification and elimination while maintaining the original detailed information.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Speed

If traditional exact matching methods are used for deduplication, then processing speed is improved, but accuracy in identifying semantically equivalent allergies deteriorates

Engineering Contradiction:

Improveprocessing speedVSAvoiddeduplication accuracy

Core Design Contradiction:

SpeedVSMeasurement precision

Solution Approach 1:

The system transforms the matching parameter from exact string comparison to semantic similarity measurement using embeddings. By changing the parameter from literal text matching to vector-based semantic representation, the system achieves both high-speed processing through efficient vector comparison and high accuracy in identifying semantically equivalent allergies that exact matching would miss.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces the mechanical exact string-matching system with an AI-based semantic embedding system. This substitution enables the system to understand the meaning behind different text representations of the same allergy, achieving superior deduplication accuracy while maintaining processing efficiency through optimized vector operations.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If manual review and verification of allergy data are implemented, then data accuracy is improved, but processing time and operational complexity increase

Engineering Contradiction:

Improvedata accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system implements self-service automated deduplication using AI embeddings and similarity matching. The algorithm autonomously identifies and merges duplicate allergy events without requiring manual review, thereby achieving high data accuracy while eliminating the time loss and operational complexity associated with manual verification processes.

Inventive Principle:

Principle #25Self-service

4Quantity of substance

If diverse data formats from multiple sources are integrated, then information comprehensiveness is improved, but system complexity and interoperability challenges increase

Engineering Contradiction:

Improveinformation comprehensivenessVSAvoidsystem complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The patent implements a universal standard code mapping framework that can handle multiple data formats and sources through a single standardized interface. By mapping diverse free text representations to common standard codes, the system achieves comprehensive information integration from multiple sources while reducing system complexity through standardized processing pathways.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250384013A1Deduplicating And Grouping Allergy Events Using Concept Mapping Of Free Text With Large Language Models

Publication Date: 2025.12.18 CERNER INNOVATION INC

AI summary

Techniques for generating recommendations of standard codes for storing in association with allergy free text to facilitate deduplication of patient allergy events are disclosed. Standard codes are alphanumeric identifiers that represent allergy events. Allergy free text is allergy event information in natural language. The system generates vector embeddings for the standard codes by applying a vector embedding function to a set of attributes associated with the standard codes. The system generates a vector embedding for a target unmapped allergy code by applying the vector embedding function to allergy free text of the target unmapped allergy code. The system compares the target vector embedding for the target unmapped allergy code to the vector embeddings computed for each of the standard codes. The system presents recommended standard codes and groupings of similar standard codes to a user for mapping to the allergy free text.