Clinical trial Sponsors are increasingly looking towards a Risk-Based Monitoring strategy in an effort to cut costs and increase data quality. Based on a recent report (from Cutting Edge Information), it may be easy to understand why. According to a market survey report, traditional monitoring can account for up to 60% of a clinical trial budget. Meanwhile, the study has demonstrated that companies using an RBM approach saved up to 43 percent on overall trial costs by reducing site visits.
CROS NT explains how a “Risk-Based Metrics” solution can be your answer to quality data metrics and facilitate a Risk-Based Monitoring strategy.
The Risk-Based Metrics approach can be applied to both RBM and traditional studies, but it is meant to change the way we look at data. The fundamental idea is to monitor data taking into account risk factors and categories in order to track study progression and solve critical situations.
In this case, the role of the Data Manager becomes somewhat fused with that of the CRA, and remote data review and monitoring should be well aligned and well-coordinated in order to avoid duplicate queries (as an example).
In addition to traditional monitoring eating up a large percentage of a clinical study budget, it also produces other alarming facts:
- Human review is estimated to be only 85% accurate
- Source Data Verification (SDV) generates 7.8% queries in all data and 2.4% in critical data
- 95% of data findings could have been identified from the database
- 100% SDV not required or expected by the FDA
- Can be limiting in its ability to provide insight into data trends across time, patients and clinical sites
In a Risk-Based Monitoring approach, data quality, integrity and patient safety should be achieved by combining:
- Supervised Analysis based on risk indicators and definition of thresholds
- Unsupervised analysis including centralized statistical monitoring to identify fraud, trends and correlations
- Sampling of SDV according to data quality
What is Risk-Based Metrics?
Risk-Based Metrics is a clinical data management activity in which the Clinical Data Manager plays an active role in the risk assessment process, central monitoring of data for risk detection and the sharing of study progression with the study team.
The Data Manager defines a Risk-Based Metrics Plan and helps the Sponsors identify metrics that need to be determined using the study EDC system. The Data Manager then reviews the data and tracks the outcomes sharing the tracker with the Sponsor and study team.
Standard and ad hoc reports are available based on individual Sponsor needs. This allows for fast and easy metrics programming within the EDC system and report extraction in a variety of formats. The Sponsor can also have access to the metrics via personal log-in credentials.
How does Risk-Based Metrics Meet RBM Needs?
- Base data control on risk category and factor in line with FDA and EMA guidelines
- Emphasize the use of remote tool for centralized monitoring and the importance of coordination between the study team, data quality and patient safety
- Identification of critical situations that need to be resolved (Plan-Check-Act)
- Evolved role of the Data Manager: the CRA cannot be left alone in data monitoring; the DM should support in the detection of risk.
- Change how data quality checks are performed and apply the FDA/EMA recommended centralized monitoring where the Data Manager is now directly involved in the analysis of data to catch outliers and anomalies
- Perform tailored corrective actions at the site according to risk, category, factors and thresholds
- Analyze and report on periodic risk to keep Monitors and Sponsors informed about the status of their sites and provide them with information concerning a site’s particular needs.
Is your company implementing Risk-Based Monitoring? Could Risk-Based Metrics be an appropriate solution for your company?
Submit an RFI to CROS NT to learn more about our full and basic Risk-Based Metrics packages to enable Risk-Based Monitoring.