Lazy Tree Copying for Clinical Database Updates
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Solution Overview
Problem
Implementation of data standards in clinical studies is burdensome and expensive, requiring significant programming efforts and updates, and there is a need for efficient management of clinical research study data to reduce administrative overhead and errors.
Innovation Solution
A digitized framework for clinical development that includes a data model with metadata repository (MDR) to manage regulatory-compliant data exchange, a graphical user interface for study design, and a lean protocol process to accelerate study planning and execution, enabling lazy copying and deleting of database elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data standards are implemented in clinical studies, then data quality and regulatory compliance are improved, but implementation cost and complexity increase significantly
Solution Approach 1:
The system segments clinical study data into standardized domains (e.g., demographics, clinical findings, laboratory tests) with predefined data elements and relationships. This segmentation allows complex clinical data to be organized into manageable, reusable components that can be independently validated and combined, reducing overall implementation complexity while maintaining data quality.
Solution Approach 2:
The system creates reusable data models and templates that can be copied and adapted across different clinical studies. Once a data standard model is developed for one study type, it can be replicated and modified for similar studies, eliminating the need to rebuild data structures from scratch and significantly reducing implementation effort and cost.
2Reliability
If data standards are updated or changed, then regulatory compliance is maintained, but programming efforts and implementation costs increase
Solution Approach 1:
The system employs dynamic, configurable data models that can be modified without requiring complete system reconfiguration. When regulatory standards change, the system allows selective updates to specific data elements, validation rules, and mappings while maintaining the overall structure, enabling rapid adaptation to new requirements without extensive programming efforts.
Solution Approach 2:
The system performs preliminary configuration by pre-defining data models, validation rules, and transformation mappings based on current regulatory standards. This advance preparation creates a foundation that can be quickly adjusted when standards change, as the basic framework is already in place and only specific parameters need modification rather than complete reimplementation.
3Adaptability or versatility
If manual clinical research management is performed, then flexibility is maintained, but efficiency and productivity decrease
Solution Approach 1:
The system provides universal, pre-configured data models and validation rules that automatically apply across multiple clinical studies and domains. This multi-functionality allows the same standardized framework to handle diverse clinical data types and regulatory requirements, maintaining flexibility through configuration rather than custom programming while significantly improving processing efficiency and productivity.
Data Source
AI summary
A computing device comprising a processor is configured to perform the techniques of this disclosure. The processor may duplicate a first node of a tree data structure to create a duplicate node, and create an inbound edge of the duplicate node to a parent node of the first node and an outbound edge to at least one child node of the first node. The processor may receive an update to the at least one child node of the first node. In response to determining that the at least one child node has multiple parent nodes, the processor may duplicate the at least one child node to create a duplicate child node, create an outbound edge of the duplicate node to the duplicate child node, delete the outbound edge of the duplicate node to the at least one child node, and perform the update to the at least one child node.