Achieve Clinical Data Transparency with the 4 Cs of Collaboration

Increasingly, drug development teams are becoming global, while at the same time operating independently from each other. This fragmentation has created a growing need for process improvements that save time, improve quality, increase transparency, and improve communication across study teams.

Coordination of activities can be stressful and take up a lot of valuable time that teams could be spending elsewhere. Streamlining the information about who is working on the data issues across the team is imperative to staying organized and transparent. If all of this is done in one place, any team member can understand immediately what the Status of the Issue is, who the Assignee is, which Sources are involved and whether a Comment or Explanation is required for submission to an agency. Even better, knowing what needs to be fixed first based on urgency means being able to prioritize.

Communication between users and teams is crucial for data quality tech solutions. Efficient triaging of issues via direct communication can be achieved by including in-app comments and tagging of relevant parties. Consolidating all correspondence and information in a single source of truth ensures that nothing is missed between parties when switching between multiple versions of emails or one-off spreadsheets and provides a clear audit log of activity.

Cooperation across teams is key to ensuring that Issues are assigned to the correct person for resolution. Those assigned to an issue need to ensure it is fixed quickly, usually following a swift timeline. It is exceedingly helpful to have a set of recommended Fix Tips for Rules that fire most often in your data. With multiple teams involved, these Fix Tips guide the Assignee on next steps for resolution so that submission flows smoothly without costly delays.

Finally, clarity is the essence of an effective collaboration strategy between teams. Users and your tech solution can either enable this or be a hindrance. Having transparency around how particular issues affect your Projected Score and Recommended Tasks informs your teams about what needs to be fixed according to significance.

It is important to demonstrate the effectiveness of interactive tools that facilitate cross-team collaboration among Biostats and Data Management teams throughout the regulatory submission process.

Following the 4 Cs of Collaboration results in a greater impact on improving your score, while also helping to define your goals and plans. Increased data quality and knowing how many other Data Packages are impacted by a particular issue ensures that your work is improved across studies. Consistency between teams and different programmers can be attained by leveraging Custom Issue Metadata to standardize your organization’s Issue Explanations so that the message is clear and consistent across Studies & Data Packages, no matter who creates them.

Teams who adopt the 4Cs framework can empower data-driven decisions and create transparency through real-time issue management, traceability, and oversight in one location, whether teams are in-house or external vendors.