Clinical Data Parsing System for EMR Interoperability
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Solution Overview
Problem
Clinical data in natural language form lacks standardized structure, impacting its effective use and interoperability of electronic medical records.
Innovation Solution
A method and system that parse textual medical information into coded phrases by searching a medical database, associating terms with medical diagnoses, and translating them into standardized coded phrases, using a medical vocabulary file and database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If clinical data is stored in natural language form, then ease of data entry and flexibility are improved, but data structure standardization and interoperability deteriorate
Solution Approach 1:
The system segments natural language clinical data into discrete terms and concepts through parsing, then maps each term to standardized medical codes. This segmentation allows the system to maintain the flexibility of natural language input while achieving structured output suitable for interoperability.
Solution Approach 2:
The patent introduces an intermediary processing layer that includes a medical database and vocabulary file. This intermediary translates between natural language input and standardized medical codes, resolving the contradiction by providing a bridge that preserves both ease of entry and structural standardization.
2Manufacturing precision
If clinical data is converted to coded format, then data structure standardization and interoperability are improved, but data processing complexity and time increase
Solution Approach 1:
The system performs preliminary action by pre-building a comprehensive medical database and vocabulary file that contains standardized codes and their relationships. This preliminary preparation reduces processing complexity during actual data conversion, as the mapping infrastructure is already in place and can be queried efficiently.
Solution Approach 2:
The patent uses copying by maintaining a vocabulary file that contains pre-defined mappings between natural language terms and standardized codes. Instead of creating complex transformation logic for each conversion, the system copies and queries from this pre-established vocabulary structure, simplifying the processing complexity.
3Measurement precision
If comprehensive medical database is used for accurate term association, then diagnostic accuracy is improved, but system complexity and resource requirements increase
Solution Approach 1:
The medical database and vocabulary file serve multiple functions: they store term-to-code mappings, define hierarchical relationships between medical concepts, provide diagnostic criteria, and support both parsing and translation operations. This multi-functionality reduces the need for separate specialized systems, managing complexity while maintaining diagnostic accuracy.
Data Source
AI summary
A method, a device and a system for correlating medical information of a first format to medical information of a second format are provided. The method includes parsing an input sequence representing textual information into plural terms; searching a medical database to associate each term with a medical diagnosis; and translating each term into a coded phrase previously associated with the medical diagnosis in the medical database.