RBQM Ops 2022 - What does Good Central Monitoring Look Like?
What does Good Central Monitoring Look Like?
data, monitoring, central, question, gcp, approach, technology, study, process, errors, primary endpoint, revision, science
Although regulatory guidance advocates for central monitoring, it does little to describe how to go about it. And so a question we're often asked is What does good central monitoring really look like? Our next speaker definitely has good experience and views on that. And I'm delighted to introduce Elaine Heffernan, who is the Associate Director of risk-based quality management worldwide clinical trials. As I mentioned, yesterday, worldwide is a key client for TRI, and our leaders in the application of RBQM, with over 90 studies using the RBQM methodology, Elaine is great to have you here. Thanks, again for sharing your time and insights with us. I'm going to hand over to you now. Thank you.
Great to be here, Duncan, and thanks for that introduction. So, you're absolutely correct, there isn't a lot of guidance in the GCP that we're currently working to. So, revision two from 2016. And if I'm really honest, that's probably what drew me to this area all those years ago. So as a creative scientist, I think I find over-regulation to be a bit of a problem for me. So within this kind of central monitoring and risk based space, there's a much more adaptive, you know, not one size fits all. So that is definitely a real, a real plus for me in this area.
So, to get started, I'm just going to touch on the definitions that we do currently have. So in revision two, we have kind of what statements. So, it's a remote evaluation of accumulating data performed in a timely manner supported by qualified and trained persons. And that part around persons is something I will touch on and in the next couple of slides. And then it also talks about output.
So, the report should be provided to the sponsor, in a timely manner for review and follow up. And that is, what GCP gives us as well as a little bit of detail. They also give us a little bit about the how and provide additional monitoring capabilities that can complement and reduce the extent or frequency of onsite monitoring and help distinguish between reliable data and potentially unreliable data. The types of tasks may be involved around data around errors around trends. So, what we do get in that paragraph in GCP, is talk about outliers and data inconsistencies, missing data, and then for errors, then issues around protocol deviations or manipulation, potential manipulation of data and integrity issues.
Also, in terms of trends, there's, you know, you can question around the range and consistency of the data, again, missing trends, is it is there a higher trend of missing at one site compared to another? For example? Are there issues with variability remembering that variability in itself is normal. So, we're always questioning is that variability, unusual or abnormal? Those components of central monitoring are then used as guidance to make decisions about sites, whether there's intervention needed or not, whether we need more intervention than we currently have, or less...
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