Dear Clinical Data Reviewer, Listing Reviews Don't Have to Be Painful.

For Medical Monitors and Data Managers, listing reviews are a crucial part of ensuring data consistency and clinical feasibility. However, these reviews often feel burdensome, especially when it involves ensuring consistency across aggregate vendor files and log forms such as ConMeds, Adverse Events, and Medical Histories. Thankfully, due to advancements in SaaS technology and collaborative workflows, this process doesn’t have to be so painful and time consuming. By leveraging digital tools to support targeted and collaborative review workflows, you can reduce cycle times and improve data quality. Keep reading to learn how the ThoughtSphere platform can help streamline your review process.

Incremental Listing Reviews

Typically, listing reviews involve going through aggregate reports, often re-reviewing data that hasn’t changed since the last cycle. This can be both time-consuming and frustrating. Our platform offers a more efficient approach through incremental listing reviews. Here’s how it works:

• Automatic Data Comparison: The platform automatically detects and highlights new or changed data since the last review cycle. This allows you to focus your attention precisely where it’s needed, without wasting time on unchanged data.
• Snapshot Functionality: Once you complete a listing review, the system captures a snapshot of the data at that moment. When the next review cycle begins, the system compares the current data to the last snapshot, highlighting any changes or new entries.

This targeted approach not only speeds up the review process but also enhances quality by ensuring no critical updates are missed.

Cross-Source Discrepancy Reviews
Performing reviews across sources can be another time-consuming task. Our platform automates and streamlines complex discrepancy reviews, traditionally performed through exception listings:

• AI/ML Configured Data Checks: Auto-configure data rules that look across domains and sources to generate discrepancies and perform vendor reconciliation
• EDC Query Writeback: Generate queries within the platform and have the system automatically push them to the EDC for the site to address so that data reviewers don’t have to work between two systems.
• Auto-Close Functionality: Discrepancies automatically close once non-conformant data points are updated to conform with check conditions. This automation reduces the need for manual follow-up, saving significant time.
• Acceptable Discrepancies: If a discrepancy is confirmed as acceptable, it can be marked as such in the platform with a comment, preventing it from refiring on subsequent data refreshes unless the source data changes and becomes non-conformant again.

This ensures discrepancies are managed efficiently, reducing the administrative burden on reviewers and maintaining data integrity.

Enhanced Collaboration with Action Tracking

Collaboration is key to efficient and thorough data reviews. Our platform’s Collaborative Action Tracker and Query Listing View make it easier for your team to work together seamlessly:

• Integrated Review Workflows: Each listing and discrepancy review performed in the platform includes related actions, queries, and an action history, all accessible within the review screen. This centralized view helps prevent duplicate effort and ensures that all team members are aware of prior actions taken.
• Efficient Query Management: With a clear view of related queries and their statuses, you can avoid duplicating questions to the site or taking actions already addressed by other team members. This fosters better collaboration and enhances the overall efficiency of the review process.

These tools ensure that everyone on your team is on the same page, improving communication and reducing review times.

Conclusion

Listing reviews don’t have to be painful. By leveraging SaaS technology and collaborative workflows, you can transform traditional listing reviews into a more efficient, accurate, and less burdensome process. Our platform’s incremental listing review capabilities, integrated collaboration tools, and automated discrepancy management save you time, reduce cycle times, and improve data quality.

Embrace these innovations to make your listing reviews more manageable and less stressful. Happy reviewing!

Are you interested in learning more about optimizing Clinical Data Management in your organization? If so, feel free to check out these additional resources:

• Clinical Data Management
• ICH E6 (R3): Take a Holistic & Automated Approach to Defining, Protecting, and Monitoring Critical to Quality Factors
• Repositioning Your CDM Team to Meet Digital Trial Demands