Recent conversations with customers have thrown up two really interesting points.
The first is around RBQM in early phase trials. For the second time in less than a fortnight we’ve been asked by a customer “Do we really need to worry about data quality management in Phase I/II trials?” I find this remarkable. My standard reply is “I don’t recall the section in E6(R2) that says ‘you must run quality trials (unless it’s early phase and then you don’t have to bother)’”. Granted there are some specific challenges with early phase trials, like small numbers of patients and shorter timescales. But one significant benefit that RBQM technology can give you is ‘data about data’. For example, the audit functions in OPRA track what data was collected, when and by whom, and importantly, if that data was subsequently changed. Providing data about data is a powerful tool in demonstrating data quality when it comes to auditing and submission.
The second point was around protocol risk assessments and Key Risk Indicators (KRIs). The customer is conducting a study where the protocol requires carers to complete information, not patients. The customer wanted to use standard KRIs, but we had to point out that it wouldn't be sufficient in this case because there are lots of potential risks that the customer hadn’t even thought of. As a simple example, having carers create the data introduces a completely new set of biases in the data. In chatting it through it became clear they needed to better understand exactly how the study would be conducted, what data was required and how it was going to be collected. This is an increasing challenge in Decentralized Clinical Trials (DCTs) and hybrid trials where new approaches and technology bring new types of risk that teams hadn't previously encountered.
Helping customers work through problems like this to create better clinical trials is one of the more satisfying aspects of our job.