Metrics defined by the Metrics Champion Consortium (MCC), a group of experts in clinical research, define how to measure the performance of our clinical trials and makes it easy to see where we are, and where we need to be in our study.
Since the metrics are the same for all clinical studies, we are comparing apples to apples. We can see the number of subjects enrolled, completed, the number of open queries and entered pages. We can see the data by study, by site, or pool site data from multiple studies. Since we are using defined metrics, we know that the definition for ‘average time from CRF submission to verification’ is: Sum (CRF Verified Date - CRF Expected Date) / (Number of CRFs). The definitions remain consistent across different clinical studies and programs.
Image: Example of dashboard showing performance metrics.
By setting targeted goals for each of our clinical trial metrics, we can start to generate indicators that tell us if we are within our target or not.
Let’s take our example in “The Use of Consistently Defined Clinical Trial Metrics - Part 1”: the number of days from a query response until the database is updated. MCC defines this target as 2-3 days, but when using EDC, we may want to shorten that goal to one day.
We can easily create a dashboard to show the data, the metrics, and the performance indicator (green / yellow / red) telling us if we are within our target goal. Pulling together all of this data in one place is the key to the successful use of clinical trial metrics.
The Only Way to Improve Clinical Trial Metrics Is to See Where We Are Outside Our Targets
This sounds very simple, and it is. The challenge has always been measuring the same items in the same way for all studies. The MCC has provided us with the standard clinical trial metrics that can be collected across the studies, individual users can provide their target goals, and all of the data can be shown using tools, such as SharePoint, and shared by all study team members.
By defining standard clinical trial metrics using operational data that is available for every study, and setting targets to show if we are on track, we can easily tell if our study is moving along smoothly and see which areas need some extra attention.
What types of clinical trial metrics do you think are important to collect for your studies?
Jennifer Price is on the MCC ‘Process Improvement Metrics Development Team.’