Multilingual Data Processing System for Adverse Event Reporting
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Solution Overview
Problem
Current systems face challenges in efficiently processing and generating individual case safety reports (ICSRs) in multiple languages, leading to delays in adverse event reporting across global health authorities.
Innovation Solution
A multilingual data processing system that includes a provider computing system and a translator computing device connected by a secure network, enabling the generation of case datasets in multiple languages by receiving adverse event data, determining case data based on localization requirements, and providing it to a user interface with duolingual text fields for translation and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate case datasets are generated for each language individually, then translation accuracy is improved, but processing time and system complexity increase
Solution Approach 1:
The patent combines multiple language version inputs into a single integrated case dataset generation process. The system accepts input data containing both first language and second language versions simultaneously, processes them together through a unified algorithm, and generates a single case dataset that contains structured data from both languages. This merging approach maintains translation accuracy by preserving both language versions while reducing processing time by eliminating sequential generation steps.
Solution Approach 2:
The system performs preliminary organization of multilingual data by structuring the input to include both language versions in a standardized format before processing. By pre-arranging the data structure to accommodate multiple languages and pre-defining the field mappings, the system prepares the data in advance for efficient processing, avoiding the need for repeated processing of the same data for each language version.
2Stability of the object's composition
If separate case datasets are generated for each language individually, then data structure integrity is improved, but computing resources and memory requirements increase
Solution Approach 1:
The patent merges the generation of case datasets for multiple languages into a single computational process. Instead of creating separate datasets for each language version, the system generates one unified case dataset that incorporates structured data from both the first and second languages. This approach maintains data structure integrity by using a consistent schema while significantly reducing memory requirements and computing resources by avoiding duplication of data structures.
3Productivity
If centralized multilingual data intake is implemented, then productivity is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal case dataset generation algorithm that can process multiple language versions simultaneously. The system uses a single, multi-functional processing routine that handles both first language and second language inputs through the same computational path. This universal approach increases productivity by enabling parallel processing of multilingual data while managing system complexity through code reuse and standardized processing logic.
Data Source
AI summary
A method for generating a first case dataset in a first language. The method includes receiving adverse event data. The method further includes determining case data including general case data and regional case data and providing the case data to a translator computing device to enable display on a user interface including multiple duolingual text fields with a first language text field including at least a portion of the text data in the first language and a second language text field adjacent the first language text field. The method further includes receiving the text data in the second language from a translator computing device. The text data in the second language is received via the second language text fields of the plurality of duolingual text fields. The method further includes generating and outputting the first case dataset including the text data in the first language.