Clinical Data Mapping for Unified Multi-Site Trial Metrics
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Solution Overview
Problem
Clinical trials across multiple sites and countries face challenges in correctly mapping, interpreting, and analyzing data with varying biases, leading to issues in transparency, risk profile data integrity, and efficiency in data monitoring.
Innovation Solution
A clinical data management system utilizing a digital data processor with user interfaces and databases that imports data from disparate sources, maintains data models, and maps data through a mapper to ensure uniform refresh intervals and compliance with recognized standards, providing real-time site performance metrics and maintaining an audit trail.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is imported from disparate clinical site sources, then data coverage is improved, but data mapping complexity increases
Solution Approach 1:
The patent introduces a data mapping layer that acts as an intermediary between disparate clinical site sources and the unified data model. This mapping layer includes transformation rules, data type conversions, and schema mappings that automatically bridge different data formats and structures, enabling the system to handle diverse data sources without increasing operational complexity for users.
Solution Approach 2:
The system dynamically adjusts data mapping parameters based on source data characteristics. The mapping engine can adapt transformation rules, data types, and validation criteria according to the specific requirements of each clinical site source, allowing flexible handling of varied data structures while maintaining consistent output formats.
2Reliability
If data is mapped through multiple models, then data integrity is improved, but processing time increases
Solution Approach 1:
The patent implements preliminary data validation and transformation rules that are established before data import. Data mapping templates and validation schemas are pre-configured, allowing data to be automatically transformed and validated against expected formats upon import, reducing processing time while maintaining integrity through predetermined checks.
Solution Approach 2:
The system maintains continuous data processing through batch operations that run at scheduled intervals. The data mapping process operates continuously as data arrives from clinical sites, with the mapping engine processing data in continuous batches rather than discrete batches, improving throughput while maintaining transformation accuracy through persistent application of mapping rules.
3Stability of the object's composition
If uniform refresh intervals are used, then data consistency is improved, but system resource consumption increases
Solution Approach 1:
The patent implements periodic data refresh operations that execute at uniformly spaced time intervals. The system schedules automated data import and mapping cycles that run at consistent intervals (e.g., daily or weekly), ensuring data consistency through regular updates while allowing the system to optimize resource allocation based on the periodic nature of these operations rather than continuous processing.
Data Source
AI summary
A clinical data management system (1) has databases (20), processors in servers (2-4) which are programmed to process clinical data and communicate with user interfaces and external systems interfaces, and at least one database. The system imports source data from disparate clinical site sources into staging databases at refresh intervals, maintains data models, and maps data from the staging databases into the data models, and feeds data from the data models into data delivery databases. There is a uniform refresh frequency for the staging databases. The system output is regularly updated data for clinical site performance, quality and risk metrics to a clinical study team. The data mapper servers identify each of a plurality of source data stages, and transform data from each stage to one or more data models according to one or more mapsets, each mapset defining a transformation.