Return To Blog

GRAPHIC RBM


By Penny Manasco - September 29, 2016


Kudos to Business Insider for its July 26, 2016 article, “The 12 Weirdest Things That Send People To The Emergency Room.”  It is must reading; particularly for the graphs accompanying the article. There is a treasure trove of information waiting to be incorporated as killer slides to perk up your next presentation.
 
My favorite one is pictured beside this blog. It looks impressive with its “big dipper” appearance and bolded words stating “Snowboarding landed more people in the hospital in January, with virtually no accidents during the summer months in the US for obvious reasons.”
 
While many people may think, “Thank you, Mr. Obvious.” there are Risk Based Monitoring (RBM) lessons to learn here. Let’s start with technology vendors offering RBM services.
 
MANA RBM is technology agnostic. The MANA Method for RBM and Remote Trial Management processes can be implemented, regardless of the technology vendor a Sponsor chooses. Sponsors routinely ask us to evaluate its favorite technology vendor(s) or the latest arrival to the RBM technology party.
 
We spend countless hours in RBM technology demos—we consider this part of our unique offering. We see innovation, creativity, and promise in many of the systems. 
 
What we also see are demos too often filled with bright, shiny graphs showing the new system’s capability in an area already filled with similar systems. The slides we see are similar to the “Snowboarding” one – a great visual showing a rather mundane use of technology. 
 
I’m not sure why the systems focus solely on the “Key Risk Indicators” without considering the need to evaluate the study specific High Risk data. If we are to truly manage trials remotely, then we need the ability to review the critical data. While I assume it is much harder to design the flexible systems we need, I also suspect some confusion about the technological tools needed to implement RBM is caused by the myriad ways different organizations use or fail to use technology.
The repository requirements TransCelerate published (Barnes et al. http://dij.sagepub.com/content/48/5/536 ) did not list the need to provide study specific reporting.  I suspect this is because large organizations such as the companies that comprise TransCelerate Biopharma already have reporting tools they use for review. Another potential reason is that the CRO industry  focuses on maintaining onsite visits as part of their model and the performance triggers simply identify when a monitor should go out to a research sitenot how to conduct timely, comprehensive review remotely.
 
Another challenge with “Pretty Little Graphs” is they often miss the critical context and analysis. Just like sending out the Snowboarding graph alone, each graph needs some interpretation—even if it just says, “This graph is meaningless”. 
 
That is why clinical researchers need to be more like scientists—exploring data, in context, and making conclusions. We continually train our staff to look at graphs in context, or normalized—so data can be compared across different sites or studies. For instance, standard graphs of screen failures, deviation numbers, or premature discontinuations must be evaluated in the context of the number of subjects enrolled or randomized at a site. It sounds simple, but that is not how data visualizations are being implemented by much of the industry.
 
For instance, our team was asked to review approximately 10 pages of graphs recently sent to a research site—beautiful graphs with no interpretation or words describing their context. It is wonderful to share performance data with sites—it is the only way they can improve and investigators have a much better idea of how the study and their subjects are progressing in the study. But if the CRO can’t provide an interpretation of the data, how do you expect a research site will be able to do it?
 
The Pharma, Biotech, Device, and CRO industry have a tremendous opportunity to move from paper and checkboxes to evaluating and interpreting data faster—not just the clinical and safety data, but operational data as well. We have the opportunity—no, the remit, to improve our processes and oversight.
 
We are committed to helping our industry better implement RBM and Remote Trial Management. Please see our training webinar on Interpreting data on our MANA RBM You Tube channel under our Training Playlist. It’s free and will increase your ability to provide the interpretation when you send out Pretty Little Graphs.
 
Let me know about your Graphic RBM stories.