Centralized Clinical Trial Data Management System
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Solution Overview
Problem
Conventional methods for managing clinical trials face challenges such as data integration complexity, quality issues, and incomplete data due to multiple systems involved, which complicates the evaluation of progress and decision-making.
Innovation Solution
A system and method that utilize a processor-based platform for managing clinical trials, including a consent recorder, data collectors, randomizer, and centralized trial manager, to streamline data collection, validation, and analysis across different stages of a clinical trial, enabling real-time interaction and automated notifications, and integrating with Electronic Health Records for comprehensive data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple separate systems are used for data collection at different clinical trial sites, then data collection can occur independently at each site, but data integration complexity and quality issues increase
Solution Approach 1:
The patent merges multiple separate data collection systems into a single centralized data collection system that can serve multiple clinical trial sites. The centralized system includes a server that receives data from various sites through a network, eliminating the need for separate independent systems at each site while maintaining data collection independence through standardized interfaces.
Solution Approach 2:
The centralized data collection system is designed with multi-functionality to handle various types of clinical trial data from different sites through a unified platform. The system can collect, validate, and process diverse data types including patient demographics, clinical measurements, and treatment responses, serving multiple purposes within a single system architecture.
2Reliability
If manual data validation is performed at each clinical trial site, then data quality can be monitored locally, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary data validation automatically at the point of data entry through standardized validation rules and checks. This preliminary validation occurs before data leaves the collection site, ensuring data quality is monitored locally without requiring time-consuming manual review processes at each site.
Solution Approach 2:
The centralized system implements automated feedback mechanisms that immediately notify site personnel of data quality issues through validation error messages and alerts. This real-time feedback enables rapid correction of data entry errors without delaying the overall trial timeline, maintaining both data quality and efficiency.
3Ease of operation
If data is collected and stored in distributed systems at each site, then local data access is improved, but data synchronization and completeness become problematic
Solution Approach 1:
The system implements a nested data architecture where local site databases are embedded within the broader centralized database structure. Each site maintains local access to its own data through nested database tables that are part of the unified centralized system, enabling both local data access and centralized data completeness through hierarchical data organization.
4Productivity
If real-time data analysis is implemented across all clinical trial sites, then trial progress monitoring is improved, but system complexity and computational requirements increase
Solution Approach 1:
The data analysis function is segmented into hierarchical levels: local preliminary validation at site level, centralized aggregation and validation at server level, and high-level trial progress analysis at management level. This segmentation enables real-time monitoring capabilities without requiring all sites to implement complex analysis systems, reducing overall system complexity while maintaining productivity.
Data Source
AI summary
A system and a method for managing a clinical trial of patients. The method includes obtaining consents of the patients undergoing the clinical trial and storing consent data of the patients. Consent data of the patients is validated before progressing onto any stage of the clinical trial. Data associated with at least one clinical trial site is collected for performing the clinical trial. The patients are randomly grouped into two or more groups for performing one or more of a single blinded study and a double blinded study during the clinical trial. Clinical data and non-clinical data of the patients is collected during the clinical trial. Timelines, progress, compliance, and data associated with different stages of the clinical trial are managed.