Transforming RBQM into Proactive Quality Actions
When the journey began, the focus was clear: monitoring. The goal was to eliminate inefficiencies, optimize resource use, reduce costs, and preempt quality issues that could jeopardize clinical trials. This was the genesis of “focus on what really matters,” a principle that brought Risk-Based Monitoring (RBM) to life. RBM is a methodology that leverages centralized analytics and targeted oversight to prioritize monitoring efforts based on potential impact. Risk-Based Quality Management (RBQM) applies the principles of RBM to all areas of quality management.
As the industry matures, it’s no longer a challenge to convince RBM study teams of the value in adopting a risk-based approach. This shift is largely thanks to early adopters who transparently shared both successes and setbacks, paving the way for broader implementation. What once felt abstract has become foundational. Industry leaders reimagined outdated processes, introduced new roles, and deployed innovative tools to strengthen and streamline monitoring efforts. Now, they’re expanding their focus beyond monitoring.
Beyond Monitoring: A Broader Risk-Based Approach
Since its release, ICH E6 (R2) has been pivotal in redefining how Sponsors and CROs approach clinical trial oversight. No longer is RBQM confined to monitoring alone. The guideline explicitly calls for a systematic approach to quality management across the entire trial lifecycle, including the identification of critical data and processes, ongoing risk assessment, and the implementation of appropriate controls. With the introduction of E6(R3), these expectations are further expanded, placing even greater emphasis on flexibility, proportionality, and critical thinking to support a more adaptive and fit-for-purpose quality framework across all stakeholders.
As a result, organizations are now extending RBQM principles beyond monitoring to encompass broader aspects of study execution. Data Management and Data Review are emerging as prime candidates for this evolution—functions that, while traditionally handled through rigid, checklist-driven processes, are now being reimagined through a risk-based lens. These domains play a crucial role in safeguarding data integrity and patient safety, and therefore stand to benefit significantly from more targeted, data-driven strategies.
The key takeaway is this: when initiating a new clinical trial, and as you identify, assess, and mitigate risks, the focus shouldn’t be limited to how monitoring alone will address those risks. Several other activities, often unrelated to monitoring, can be critical in preventing or detecting potential issues earlier in the process. The principle of resource optimization and the mantra to “focus on what really matters” are equally valuable in:
- Prioritizing edit checks that focus on critical outcomes
- Implementing risk-based query strategies to reduce manual workload
- Applying targeted medical and safety reviews, leveraging automation
- Focusing data cleaning and protocol deviation tracking on what truly impacts quality or safety
At CluePoints, we’ve worked with customers who chose not to reduce Source Data Verification (SDV) yet still embraced the principles of RBM. Their primary focus was on adopting a risk-based, targeted approach to better identify where risks reside, implement mitigation strategies, and use algorithmic techniques to continuously monitor the data and uncover unexpected issues. Rather than scaling back SDV, they optimized their resources by focusing on atypical sites, patients, or regions, letting the data “speak” for itself.
The 3 Pillars of a Risk-Based Approach
In our experience, a strong risk-based approach is built on three core pillars: risk, signal, and action.
- Risk: A potential issue—something that might happen during the course of a trial.
- Signal: What has happened—an observable anomaly or deviation that requires attention.
- Action: The outcome of evaluating risks and signals. It can take several forms:
- Taking preventive action based on identified risks to avoid issues
- Investigating a signal to determine if it represents a true issue
- Implementing corrective action when a signal is confirmed to be a problem
This cycle of identifying risks, detecting signals, and taking informed action is the engine of an effective risk-based quality strategy. It’s not just about reducing SDV; it’s about driving smarter oversight through data-driven decision-making.
From a strategic standpoint, risk management is the ideal foundation for authoring your functional plans—not just your monitoring plan. At its core, a functional plan answers the questions: who does what, when, and why. And that’s exactly what risk assessment and mitigation processes provide:
- The risk defines the why—the rationale behind your actions.
- The action defines the what, who, and when for the tactical execution.
Consider a high safety risk scenario: The monitor visits the site every 12 weeks, with a focused Source Data Review (SDR) on Serious Adverse Events (SAEs). The data manager runs AE/concomitant medication reconciliation reports every 4 weeks. The medical reviewer dedicates additional time to the 5% of patients with atypically high or low AE counts flagged in their profiles. The central monitor applies statistical data monitoring to detect unusual safety reporting patterns at the site level.
Of course, a plan alone isn’t enough. You must execute it and assess its real-world impact:
- Did your mitigation strategies detect or prevent problems?
- Were those issues aligned with the risks you had anticipated?
- How did you uncover unexpected issues, and could they become predictable in future trials?
- Which predefined actions provided value?
Closing the Loop with the Site Profile & Oversight Tool (SPOT)
This is where CluePoints’ Site Profile & Oversight Tool (SPOT) becomes essential. SPOT brings risk-based planning to life by enabling adaptive site monitoring. Instead of relying on static schedules, study teams can use SPOT to:
- Centralize site-level data across systems (EDC, CTMS, IRT, etc.)
- Visualize site workload and risk in a single dashboard
- Prioritize visits and resources based on evolving data-driven insights
- Trigger and track actions in response to statistical, operational, or safety signals
Whether responding to a spike in protocol deviations or reassigning CRA time toward higher-risk locations, SPOT ensures that planned actions are executed efficiently, consistently, and transparently. The operational engine powers the “action” in the risk-signal-action loop. By integrating SPOT into your clinical trial monitoring strategy, you’re not just identifying and planning around risks—you’re actively managing them in real time, optimizing trial oversight and performance at every step. Get a more detailed overview of SPOT in CluePoints’ comprehensive guide to adaptive site monitoring.
