Slow activation can negatively influence clinical trials before they truly even begin. With all of the steps that must be completed across various groups before you start recruiting subjects, there is a potential for inefficiencies to slow your site down. However, it can be hard to track activation and all of its sub-processes.
To help large research centers gain a better grasp of their cycle times, we share information and metrics that help shed light on activation at your site and get studies started in the shortest time possible.
Depending on your institutional processes, the start and end points of activation may be different than other sites. However, honing in on your processes will give you a clear picture.
Median days to activation
Leadership and operations teams need to understand how they are progressing toward their institution’s activation goals and be able to communicate it to others. They will likely want to know which management groups activate the fastest or slowest and how study activation varies by sponsor type for a better picture of performance.
Change in activation over time
Measuring the change in the study activation process over time lets you know which management groups have improved so you can showcase their progress and learn from them. You can also see if any management groups have gotten worse over time and investigate what’s going on and borrow any applicable best practices from others.
Slow activation can cause many problems, from getting a late start on recruitment efforts to not being selected for future studies. It’s critical for sites to be aware of these delays and know where they occur.
Protocols with the longest activation times
Identify which protocols took the longest to activate. Once you know which ones were troublesome, you can look back into the sub-processes to identify bottlenecks and find the exact problem.
If there aren’t context clues in your CTMS or in other notes, you should talk with the appropriate people to understand what happened. If you’re able to find the root cause, you can apply these lessons learned in the future.
Cycle times of sub-processes
A long activation time could be attributed to a single key sub-process within the overall timeline (e.g., IRB, contracts, PRMC, etc.), even when every other step went according to plan. By drilling down into sub-metrics, you can see how efficient (or inefficient) certain portions of study activation are.
Additionally, you may want to compare certain types of studies (e.g., interventional vs. all treatment-interventional), broken down by management group and/or sponsor type to help find trends, timelines and progress at a more granular level. This type of information can be used in everything from reports for leadership to communicating timelines to study team members, committees and investigators.
It’s very important to know where protocols are getting stuck, but that’s not enough. To make process improvements that address the roadblocks that affect activation, you must be able to identify what contributed to the delay(s) and which of those are in or out of your control.
Know which delays are outside of your site’s control, such as:
Examine the possible reasons for inconsistencies in cycle times that your site may have some control over—at the institution, disease team and PI levels. Consider the following:
For some of these issues, you may not be able to do much as a researcher (if it’s at the IRB or in contracting), or there may not be an easy fix. Yet, if you can identify any low-hanging fruit and optimize as much of what’s in your site’s control as possible, you may be able to improve activation timelines.
Additionally, if your site tracks staff effort, you can use the data to gain a better understanding of how much time activation takes, allocate the appropriate staff needed to complete activation, and ensure the budget covers the effort put forth in activation.
It’s important to proactively identify protocols that are ‘stuck’ in certain stages of the activation process in order to more successfully activate current trials. This prevents them from being added to your ‘longest activation cycle’ list and helps put out fires in the moment.
Knowing if protocols are on track for meeting study activation goals and which portions of the study activation process have been completed will allow you to see which studies need additional resources or help to finish out the activation process. You can then work with the appropriate people to get things moving again.
Activation timelines can vary quite a bit. Each new trial you take on won’t be the quickest to achieve activation, and some studies will take much longer than you’d hope. However, by monitoring activation trends and paying close attention to protocols that are stuck somewhere in the process, your site will not only be able to spot bottlenecks, but help prevent them as well. Utilizing past performance data can also help project future outcomes and make your institution more competitive with activation timelines.
With Nimblify Research Insights, sites that use OnCore as their CTMS can immediately learn where to speed up study activation across sponsor types, therapeutic areas, management groups and more. Its dashboards help you discover how activation has changed over time, identify any bottlenecks where protocols get stuck in the process, and understand how much effort it will take to activate a study – all at a glance.