Clinical Data Validation via Consistency Requirement Evaluation
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Solution Overview
Problem
Clinical data validation is challenging due to inconsistencies across different applications and systems, leading to potential misdiagnosis and inefficiencies, as metadata is often separated from core clinical data and lacks standard validation mechanisms, especially across multiple applications from different vendors.
Innovation Solution
A clinical data validation system that includes a validation component to evaluate data claims based on consistency requirements, using a consistency requirement input component, a data claim input component, and an alert component to notify users of inconsistencies, with data claims stored as (name, value) pairs and optionally including digital signatures for verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If metadata is stored separately from core clinical data to enable flexible data management, then ease of operation is improved, but reliability deteriorates due to risks of data separation and misidentification
Solution Approach 1:
The patent introduces a validation component as an intermediary between the metadata and core clinical data. This component receives data claims about the clinical data, evaluates them against consistency requirements, and ensures that separately stored metadata remains reliably associated with the correct clinical data through systematic validation rather than direct coupling.
2Reliability
If explicit coding is implemented in each application to verify data consistency, then reliability is improved, but device complexity worsens due to error-prone manual verification
Solution Approach 1:
The validation component performs self-service by automatically receiving data claims, evaluating them against predefined consistency requirements, and identifying inconsistencies without requiring explicit verification coding in each application. The system serves itself by maintaining data consistency through automated validation rather than manual intervention.
3Adaptability or versatility
If multiple applications from different vendors are integrated to provide comprehensive clinical data, then adaptability is improved, but reliability deteriorates due to consistency problems across applications
Solution Approach 1:
The validation component serves as a universal mechanism that can validate data claims from multiple different applications and vendors against a common set of consistency requirements. It performs multiple functions including receiving claims from various sources, evaluating them against standardized criteria, and ensuring cross-application consistency through a single unified validation approach.
Data Source
AI summary
Certain embodiments of the present invention provide a method for validating clinical data including receiving a consistency requirement, receiving a data claim associated with clinical data, and evaluating the data claim based at least in part on the consistency requirement. Certain embodiments of the present invention provide a clinical data validation system including a consistency requirement input component adapted to receive a consistency requirement, a data claim input component adapted to receive a data claim, and a validation component adapted to evaluate the data claim based at least in part on the consistency requirement. The data claim is associated with clinical data.