A5.2 The Risk-Based Data Management (RBDM) Revolution

This presentation is part of a full breakout session. To add this presentation to your schedule you must add the full breakout session.

This session will explain how RBQM can protect data quality and participant safety by enabling teams to identify and mitigate the most critical risks to their studies. It will demonstrate how RBQM flags systemic data issues that remain invisible to traditional approaches. 

Risk-based quality management (RBQM) encourages clinical research teams to identify the risks that could most significantly impact on study success, and establish plans on how to control their impact. It requires teams to think before they act and to focus on what matters most.

It is an approach that can help teams to identify and respond to systemic data issues with the potential to threaten data quality or participant safety. By comparing datasets from all sites, RBQM can spot “outliers” that could be indicative of training issues, faulty equipment, or fraud, for example. Unearthing such discrepancies during study conduct, rather than after database lock, allows teams to take early corrective action.This session will define the RBQM model and its value in protecting data quality and participant safety, and explain how teams can identify and mitigate the most critical risks to their studies. It will also use practical examples to demonstrate how RBQM can be used to flag systemic data issues that would have remained undetected using traditional data monitoring approaches.