Data Integration – A Valid Concern or a Convenient Excuse?

3rd Global RBM summit in London

Conference season has started! Our first stop was in London last September. Pioneer work and resourceful interactions offered us the right ambiance to interface and share best practices in Risk-based Monitoring (RBM) with peers and other industry experts.

“We were honoured to be one of the main sponsors and be present with a booth for live demonstrations this year.” – Dr Artem Andrianov, CEO Cyntegrity

Data integration – a valid concern or a convenient excuse for organizational change?

Risk-based monitoring in clinical trials is primarily aimed at helping smarter data-driven decisions, efficient risk mitigation as well as improving data quality and patient safety. Reducing the overall monitoring costs could serve as a well welcomed bonus. Despite its promising value proposition, it seems that one of the current concerns holding organizations back from adoption of RBM is being able to achieve data integration from separate sources to allow for an efficient and intelligent decision-making source.

Being an innovative leader in integrated risk-based monitoring services, our Chief Scientific Officer Dr Johann Proeve was invited to join the conversation as a speaker on the topic “Pragmatic Centralized Monitoring – How to get there?”. Johann shares his observations with us:

Johann, within the concept of risk-based monitoring, how does Centralized Monitoring fit in?

Johann: Together with off-site monitoring (by the way, the FDA sometimes speaks of “remote monitoring”), centralized monitoring forms the core of risk-based monitoring. These two mechanisms serve “to monitor important study parameters through a holistic lens” as simply outlined and illustrated by TransCelerate’s RBM model. Risk-based approaches incorporate centralized monitoring mechanisms to turn clinical trial conduct into an integrated, real-time and pro-active activity.

Our task as an RBM service provider is to facilitate Central Monitors with intelligent, integrated technology and insight that enables them to quickly and easily navigate from the big picture to individual risk indicators. With the help of an intuitive visual analytics instrument Central Monitors can navigate through the data and gain meaningful insights into the integrated data.

TransCelerate: Holistic RBM Model

Traditionally, site performance assessments were covered by on-site Monitors through 100% Source Data Verification (SDV), unnecessarily causing clinical trial conduct to be tedious, disparate and reactive. Why is it, despite its benefits and despite the current regulatory guidance, that many organizations are reluctant to make the switch to a risk-based approach?

Johann: Talking to peers and other experts in the field during this summit it became clear that there are a few burning issues that need our attention. Firstly, organizations seem to be very much concerned about data integration and platform compatibility. Secondly, study teams struggle to work with Key Risk Indicators (KRIs) and Quality Tolerance Limits (QTLs); what do they mean, in what way do they differ and how can it be applied? Thirdly, not many realize the value of historical data in future studies. And to add a fourth, there is still no clear-cut idea what the best set up for an organization would be after the application of RBM.

The good thing is, there are answers to these questions and there are solutions to these perceived challenges as we speak!

Okay, let’s zoom in on these four aspects. What is the good news for organizations that are concerned about data integration and platform compatibility?

Johann: There is technology out there that can handle this! Even more important, there is expertise available to support organizations with this major task.

The EarlyBird® platform for example. This real-time business intelligence platform connects to all involved clinical and non-clinical recording systems including the all-time favorite Excel spreadsheets. Its umbrella view goes beyond any EDC system, which is very important, since the early results of our latest RBM study suggest that around 40% of the flagged risk events originated from non-EDC data sources!

“…around 40% of the flagged risk events originated from non-EDC data sources!”

And then there is us, RBM experts at the industry’s disposal. Besides adequate training being a mandatory requirement by the ICH GCP, we see it as THE most significant component of the RBM service solution. As hands-on experts, we understand the implementation of a novel RBM technology is part of a comprehensive program that triggers a change process in an organization. All involved stakeholders and study teams will have to move out of their comfort zones. Therefore, education, training and change management are central to a productive implementation.

EarlyBird connecting to clinical and non-clinical data sources

The second adoption barrier you mentioned, is to do with KRIs and QTLs. Can you elaborate on this?

Johann: We’ve run several webinars around this popular topic and we will continue to put a lot of effort into getting the concepts across. Not only by repeated training sessions and webinars but also by supporting study teams with ready to go tools.

With our team of clinical experts, we’ve been developing a “KRI Wiki”. Currently KRI Wiki holds over 280 KRIs, which can be filtered for categories such as risk type and risk event. In addition, we have taken a similar approach to our Risk Assessment and Categorization Tool (RACT) libraries by developing indication based or therapy focused RACTs, such as Oncology, Diabetes and Medical Devices RACT libraries. Facilitating the study teams understanding the purpose and practical usage of KRIs and QTLs, it is essential to offer relevant and specific instruments requiring little to no tweaking.

Why is historical data of importance to future trials?

Johann: Data that was collected earlier can help you predict what will happen in the future. The immediate advantage is that it enables clinical trial operations to shift from a reactive “trying to catch our shadow” attitude, to a proactive one.

However, there is much more to it. Historical data can help reveal systemic quality threats by comparing current site data to systemic risk thresholds. Instead of comparing current data across study sites, the RBM service can now flag multiple sites struggling in a specific area.

Subsequently these insights can be further leveraged by enhancing study and protocol design. Without doubt, the proper use of historical data contributes to the overall data quality level of subsequent studies. This way of working is in line with the Quality by Design (QbD) concept.

The EarlyBird® platform, that I spoke about earlier, incorporates Artificial Intelligence (AI) driven “Predictive Analytics” as part of its holistic RBM service.

Finally, how does the roll-out of an RBM program impact an organization?

Johann: I will try to summarize the essence. As mentioned before, the roll-out of an RBM program will trigger a change process in an organization requiring change management and experienced change managers. Prior to kicking off any activities in this direction, it is crucial to have the backing of senior management. Without their support, the project is guaranteed to fail.

The next step is to have the right stakeholders and catalysts identified, keeping in mind that RBM implementation is 60% about data and 40% about human processes and related aspects. And be prepared for resistance when trying to move people out of their comfort zone, their daily routine.

The good thing is, that we know change is a process with a start and an end.

Kubler-Ross Change Curve

In my next blog I will continue to detail out the pragmatic approach that we take to RBM program implementations based on our own experience, based on the feedback of our clients and based on the many best practices sharing sessions that we had with our peer group.

Show courage instead of making excuses

In summary you observe that; the biggest stumble blocks that put the industry to a standstill when it comes to adopting a risk-based approach, such as the fear of data source aggregation, the unfamiliarity with KRIs and QTLs, the unknown benefits of historical data in future studies and the inevitable change process that comes along with forming a fit-for-purpose organization, are all solvable and addressable by today’s technology, tools and subject matter expertise. Obviously education and training are the key ingredients of the “change recipe” supported by an indication and therapy oriented toolkit. Basically, it is time for the industry to display courage rather than continuing to make excuses, right?

[Editorial] You might also like: The RBM Consortium – 10 Burning Questions about Risk-Based Study Management

By |2018-10-15T15:10:53+00:00October 11, 2018|Blog, Conferences|Comments Off on Data Integration – A Valid Concern or a Convenient Excuse?
Linda has over 20 years of experience uncovering pain points and strategizing with MedTech organisations in order to secure and retain more clients. Her chief thinking responsibilities include translating insight into strategy and ensure that all project activities meet our clients’ quality expectations.

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