Clinical Research Data Automation System
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Solution Overview
Problem
Current manual, paper-based systems for managing patient information in clinical research are inefficient, labor-intensive, and prone to errors, posing challenges in ensuring the safety and quality of patient data, which hinders the effectiveness and efficiency of clinical research processes.
Innovation Solution
A computer-implemented system comprising a research participant's computing device, a research site manager's computing device, and a sponsor's computing device, equipped with a research process optimizing module that collects, sorts, and processes patient data using AI and machine learning to streamline clinical research, including enrollment, retention, appointment scheduling, data capture, and financial management, thereby reducing manual labor and enhancing data accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual, paper-based systems are used to manage patient information, then data collection and management can be performed, but the process becomes labor-intensive, inefficient, and error-prone
Solution Approach 1:
The patent replaces manual, mechanical paper-based data collection and management systems with an automated computerized system. The system uses electronic data capture, automated sorting algorithms, and computerized processing to eliminate manual handling of patient information, thereby improving productivity while reducing operational complexity
Solution Approach 2:
The system enables self-service functionality where the computerized system automatically performs data collection, sorting, and management tasks without requiring manual intervention. The automated processes handle routine operations independently, reducing the labor intensity for healthcare providers while maintaining high productivity
2Reliability
If manual, paper-based methods are used to manage patient information, then data can be stored and accessed, but the process requires many checks and balances to ensure accurate processing
Solution Approach 1:
The patent replaces complex manual verification processes with automated computerized validation. The system uses electronic data capture and automated sorting algorithms that inherently ensure accuracy through systematic processing, reducing the need for multiple manual checks and balances while maintaining high reliability
Solution Approach 2:
The system incorporates automated feedback mechanisms where the computerized processing continuously validates and verifies patient information accuracy. The automated sorting and processing systems provide real-time feedback on data quality, ensuring accurate processing without requiring complex manual oversight
3Reliability
If current systems are used to ensure safety and quality of patient information, then data protection can be maintained, but the systems become cumbersome, inefficient, and expensive
Solution Approach 1:
The patent replaces cumbersome manual safety and quality assurance processes with automated computerized systems. The electronic data management system inherently maintains data safety and quality through automated validation, encryption, and secure access controls, eliminating the need for inefficient manual procedures while improving overall productivity
Data Source
AI summary
A method for providing an optimized process in clinical research, comprising enabling research participant, site manager to input research participants' information by enrolment and retention module on research participant computing device, research site manager computing device. Identifying research participants' information stored in database and generating list of qualified research participants by list generating module. Enabling qualified research participants to schedule appointment with site manager by appointment scheduling module and assigning principal investigators to screen research participants. Enabling principal investigators to input screening data by primary source data capture module after screening research participants in real-time. Collecting screening data to calculate accounts receivable from sponsor by financial module and sending screening data to data review and reports generating module. Generating screening reports by data review and reports generating module and sending screening reports to invoice generating module thereby generating invoice. Sending invoice to sponsor computing device and enabling sponsor to review invoice.