Filter Dictionary for Clinical Data Retrieval
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Solution Overview
Problem
Current thesaurus management systems and dictionaries struggle to efficiently process and analyze freeform text data from clinical studies due to inconsistent terminology, misspellings, and the inability to account for new terms, leading to inaccurate data collection and analysis.
Innovation Solution
A data retrieval tool, referred to as a filter dictionary, is introduced that superimposes a hierarchy of relations on existing dictionaries, allowing for the grouping and classification of terms based on associations, inclusion, and exclusion criteria, enabling the retrieval of data without direct linguistic relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional dictionaries are used to process verbatim terms, then data processing can be performed with simple matching, but the system cannot account for misspellings, term mutations, and new terms leading to incomplete data collection
Solution Approach 1:
The patent implements a hierarchical thesaurus structure where multiple levels of terminology are nested within each other. The system contains a base dictionary, overlays a thesaurus with equivalent and related terms, and further overlays standardized queries. This nested architecture allows the system to handle new terms and variations at different levels without requiring complete system redesign, thereby improving adaptability while managing complexity through organized layers.
Solution Approach 2:
The thesaurus system is designed to be dynamically extensible. New terms, equivalent terms, and related terms can be added to the thesaurus without fixed structural constraints. The system accommodates term mutations and misspellings by allowing flexible additions to the terminology layers, enabling the system to adapt to new medical terminology and variations as they emerge in clinical data.
2Measurement precision
If multiple different terms are searched to ensure complete data collection, then data accuracy improves, but the time and computational resources required increase significantly
Solution Approach 1:
The patent merges multiple search operations into a unified thesaurus-based search system. By combining equivalent terms, related terms, and standardized queries into a single integrated thesaurus structure, the system allows one search operation to simultaneously retrieve data associated with multiple terminology variations. This consolidation maintains comprehensive data collection accuracy while significantly reducing the time and computational resources needed compared to executing separate searches for each term variation.
Solution Approach 2:
The thesaurus system serves multiple functions simultaneously: it acts as a dictionary for term definition, a thesaurus for finding equivalent and related terms, and a query system for standardized data retrieval. This multi-functionality allows the system to handle diverse search requirements through a single unified mechanism, improving data collection accuracy across different term variations without proportionally increasing processing time.
3Ease of operation
If manual ad-hoc queries or custom programming are used to search dictionaries, then specific data retrieval needs can be met, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The patent implements preliminary organization of terminology data into a structured thesaurus with predefined equivalent terms, related terms, and hierarchical relationships. This pre-structuring of data allows users to perform searches without needing to manually construct complex queries or write custom programming. The thesaurus is prepared in advance with all terminology relationships established, enabling straightforward search operations that significantly reduce the time and effort required for data retrieval while maintaining ease of operation.
Data Source
AI summary
A method includes defining a plurality of terms for use in conjunction with a study where the terms are stored according to a series of relations and the relations corresponding to the terms indicate an association from a term to at least one other of the plurality of terms, defining at least one group of terms taken from the plurality of terms and storing at least one group of terms, including the relations corresponding to each term, defining a further level of relations to be applied to the group of terms, the further level of relations defining inclusion and exclusion criteria, and providing a match term defined by the group of terms and querying a memory of data from the study to find occurrences of the match term as defined by the further level of relations.