How COVID-19 has changed interest in the use of eSource [3:35]
The value of [eSource] has not changed. What has changed is the environment, the dynamic of trying to run clinical trials in a COVID or in a pandemic crisis. And that’s really why we’ve seen the increase interest in eSource. And I think this will definitely continue as we move forward not just because of the pandemic, and patients, and site coordinators, and even doctors can’t get to clinics. It’s just a better way of running a clinical trial. It’s much more efficient. It has many value propositions that make it ideal for running a clinical trial.
What is the benefit of using eSource or Direct Data Capture in a clinical trial? [4:15]
What eSource, and direct data capture, enable is the ability to change that process and only capture data once electronically. And then, be able to reuse and repurpose that information for the various constituents that need to see that, whether it’s all the data that the site needs to see for the source, or a subset of that data, the ECRF fields that the data managers, or the sponsors need to see. That’s the concept behind eSource and direct data capture.
Medrio and Quartesian are partnering right now on a COVID-19 trial. [12:20]
Quartesian has developed a bridge mapping software, basically, a middleware that can take data from one system, transform it and then load it into another system. It’s an ETL or extraction transform and load technology. And we’re able to do it independent of what the source systems are. So, in this case, data’s coming out of an EMR system, and it’s being pushed out of the system to a file store, secure file store. We’re then grabbing that data, transforming it, and then using the Medrio API popping that right into the Medrio forms.
On how Quartesian is working to cleanse that data as it goes between systems. [15:30]
So, we’re going to get the data model and data structures from the EMR system, as well as any information we need about that data that might need to be transformed into the EDC data base, the Medrio database. So, that comes out, we have a powerful scripting language that we use to take that data, to manipulate it, transform it to make sure we’re putting a proper data in the proper location at Medrio. And some of that involves some calculations because, again, your EMR or EHR systems don’t necessarily store data. They don’t understand what a visit is because that’s a concept we have in clinical trials. So, we have to do some of that on the front side to map it. And that’s where we come in.
