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Vandita Tripathi
Portfolio Head, Digital Data Acquisition & Decentralized Trials, TCS ADD™
Manas Saha
Technical Architect, TCS ADD™
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Reimagining reporting and visualization during clinical data management
Clinical data management is an important part of clinical trials involving the monitoring of the study parameter analytics, which might include statistical analysis of the captured patient data and management data such as audit trials and queries. Reports and dashboards enable reviewers to access the required analytics from the clinical trial management system. Access to quality reporting data is the key to efficient data management and study success.
Most of the reports are predefined and offer little or no configuration options to fine tune the report fields and filters. In real-world situations, the users often run into scenarios where they need a specific type of report containing specific fields or filter conditions that may not be available in the clinical trial management system.
The answer to the problem is an AI-based solution that can understand natural language input and translate the same into database queries. The solution accepts a natural language, plain English prompt from the end user specifying the report fields and filter requirements. AI translates the requirements into database queries and executes them to generate and download the required report. Thus, the solution reimagines the reporting solution from traditional user dashboards and canned reports to user-driven, natural language-based intelligent reports along with trend analysis and recommendations.
This solution does not need the user to have low-code/no-code custom report building skills or specialized SQL/CQL skills. On an average, a person needs to grasp the low-code/no-code platform and then learn SQL/CQL along with the database schema which might take months to master whereas with this proposed solution, no upskilling is necessary.
On an average, a custom report development takes weeks to months in the existing clinical trial landscape. Our proposed solution can cut down that turnaround time to minutes by drastically reducing the time and manual effort needed to generate the reports.
To read the complete paper, please click here.
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