Case Dataset Versioning With Supplemental Data Deprecation
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Solution Overview
Problem
Existing version control systems for case datasets require each piece of supplemental adverse event data to be promoted to a new version, leading to excessive storage and complexity, and lack efficient handling of trusted and non-trusted data sources.
Innovation Solution
A system and method that deprecates non-current supplemental adverse event data and promotes only the most up-to-date versions, utilizing partner preferences to manage data intake from trusted and non-trusted sources, reducing storage and simplifying dataset history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If each piece of supplemental adverse event data is promoted to a new version, then data completeness is improved, but storage requirements and system complexity increase excessively
Solution Approach 1:
The system identifies and deprecates outdated supplemental adverse event data that has been superseded by more recent submissions. When new supplemental data is received for an existing case, the system marks previous supplemental data as deprecated rather than creating new versions, thereby discarding redundant information while preserving data completeness through selective retention of current valid data.
Solution Approach 2:
Instead of promoting each supplemental data submission to a new version (forward progression), the system inverts the approach by deprecating older supplemental data in favor of newer submissions (backward elimination). This inversion reduces version proliferation while maintaining data completeness by keeping only the most current valid supplemental information.
2Loss of information
If all supplemental adverse event data is retained for version control, then data traceability is improved, but data access speed decreases
Solution Approach 1:
The system extracts and removes deprecated supplemental adverse event data from the active dataset. By taking out outdated information that is no longer valid, the system maintains traceability of the data lifecycle while improving access speed to current valid data, as the search space is reduced to only active, non-deprecated records.
3Reliability
If supplemental adverse event data from non-trusted sources is processed through full version control, then data reliability is improved, but processing time and computational resources increase
Solution Approach 1:
The system applies partial version control actions by deprecating only the necessary outdated supplemental data rather than processing through complete version control workflows. This partial action maintains data reliability by ensuring current valid data is retained while improving productivity by avoiding excessive processing of already-superseded information from non-trusted sources.
Data Source
AI summary
A method for version control of a case dataset includes receiving adverse event data and determining case data based on the adverse event data. The method further includes generating the case dataset including the case data and first version data. The method further includes receiving and classifying first supplemental adverse event data and classifying. The first supplemental adverse event data is classified as at least one of: a first classification or a second classification. The method further includes receiving second supplemental adverse event data and classifying the second supplemental adverse event data. The second supplemental adverse event data is classified as at least one of: the first classification or the second classification. The method further includes determining supplemental case data based on the second supplemental adverse event data. The method further includes generating second version data. The method further includes generating and outputting a supplemental case dataset.