Clinical Record Categorization via NLP and Classification Codes
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Solution Overview
Problem
The challenge lies in efficiently categorizing and organizing vast amounts of clinical record data, which is complicated by the complexities of clinical language, limiting the efficacy of text or keyword-based searching in electronic records.
Innovation Solution
A computer-implemented method utilizing a natural language processing engine leveraging a clinical terminology knowledge base to identify and associate user-generated text with pre-existing clinical classification codes, enabling streamlined categorization and searching of clinical records, and allowing users to confirm or reject suggested codes through a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If text or keyword based searching is used for electronic records, then the searching process is simple, but the efficacy is limited due to complexities of clinical language
Solution Approach 1:
The patent introduces a natural language processing engine as an intermediary between the search query and the clinical records database. This engine translates natural language queries into structured search operations, bridging the gap between simple keyword searching and the complex clinical terminology, thereby maintaining ease of operation while improving searching efficacy
Solution Approach 2:
The system transforms the search approach by changing parameters from simple keyword matching to natural language processing with clinical terminology knowledge bases. This parameter change enables the system to understand clinical language complexities while maintaining user-friendly query interfaces
2Measurement precision
If manual categorisation of clinical record data is performed, then accuracy can be maintained, but the task becomes unwieldy and time-consuming for large volumes of data
Solution Approach 1:
The system implements automated categorisation where the natural language processing engine independently analyzes and categorizes clinical records without requiring manual intervention for each record. The engine serves itself by using the clinical terminology knowledge base to autonomously assign classification codes, dramatically improving productivity while maintaining accuracy through the structured approach
Solution Approach 2:
The patent applies preliminary action by pre-processing clinical records through natural language processing and pre-assigning classification codes before formal review. This preliminary categorisation reduces the workload for manual verification and speeds up the overall processing pipeline while maintaining accuracy through the structured classification framework
3Productivity
If automated coding is implemented without user confirmation, then processing speed increases, but subjective errors may occur
Solution Approach 1:
The system implements feedback by presenting the natural language processing engine's suggested classification codes to users for confirmation or correction. This feedback loop allows the automated system to operate at high speed while providing an opportunity for human review to catch and correct any errors, thereby maintaining both productivity and reliability
Data Source
AI summary
The present disclosure relates to frameworks and methodologies for enabling categorisation and/or searching of digitised information, including clinical report data. Embodiments of the invention have been particularly developed to assist categorisation of digitised information, such as clinical report data, in a streamlined manner based on a pre existing set of classification codes. This, in some embodiments, enables the discovery and extraction of meaningful patterns from unstructured clinical reports. Further embodiments of the invention have been particularly developed to assist in the discovery and extraction of meaningful patterns from an unstructured set of digitised information such as unstructured clinical reports. While some embodiments will be described herein with particular reference to those applications, it will be appreciated that the invention is not limited to such a field of use, and is applicable in broader contexts.