Clinical Data Viewer for Real-Time CRF Access
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Solution Overview
Problem
Clinical data managers face challenges with outdated summaries and the inability to directly access and modify CRF data in existing CRF data management systems, as denormalized summary versions of normalized data tables are not always up-to-date and do not allow for direct interaction with the normalized transactional data.
Innovation Solution
A system and method that provides a clinical data viewer tool with a viewer logic configured to act on a trial database, allowing users to view and interact with CRF data stored in normalized transactional tables through denormalized summary tables that are automatically updated, enabling users to perform form actions and navigate between views and the transactional database seamlessly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If denormalized summary tables are used for data analysis, then query processing is optimized, but data accuracy and up-to-dateness deteriorate
Solution Approach 1:
The system implements automatic refresh mechanisms that continuously monitor changes in normalized CRF tables and propagate updates to denormalized summary tables. This feedback loop ensures that summary data remains synchronized with source data, resolving the contradiction between optimized query performance and data accuracy.
Solution Approach 2:
The patent introduces an intermediary data layer consisting of denormalized summary tables that act as mediators between normalized transactional data and analytical queries. These intermediary tables maintain up-to-date information while optimizing for analytical workloads, bridging the gap between data accuracy and query efficiency.
2Reliability
If normalized data tables are used for storing CRF data, then data integrity and transaction processing are optimized, but data analysis and summarization become difficult
Solution Approach 1:
The system segments the data architecture into distinct normalized CRF tables for transaction processing and denormalized summary tables for analysis. This segmentation allows each table type to be optimized for its specific function, maintaining data integrity in normalized tables while enabling efficient analysis in denormalized tables.
Solution Approach 2:
The patent creates denormalized summary tables as copies of normalized CRF data, transformed to optimize for analytical operations. These copies preserve the essential information from normalized tables while restructuring it for efficient querying, summarization, and analysis without compromising the integrity of the original transactional data.
3Productivity
If denormalized summary tables are created from normalized CRF data, then analysis performance is improved, but system complexity increases
Solution Approach 1:
The system merges the data storage and data analysis functions into a unified architecture where normalized CRF tables automatically feed into denormalized summary tables. This integration eliminates the need for separate complex ETL processes and manual data transformation, reducing overall system complexity while maintaining analysis performance.
Data Source
AI summary
Systems, methods, and other embodiments associated with a data view for clinical data are described. In one embodiment, a method includes receiving a request from a user to view summarized case report form (CRF) data, where the CRF data corresponds to a plurality case report forms (CRFs) stored in one or more normalized transactional tables. A view query is constructed based, at least in part, on the request and executed on one or more denormalized summary tables to construct a view. The denormalized summary tables store selected CRF data from the normalized transactional tables and are updated concurrently with each update to the transactional tables. The method includes rendering the view for display.