3 Tips for Better Clinical Trial Representation

A lot is being written and discussed about patient representation in clinical trials. It is obvious that we are not where we need to be as the majority of studies maintain relatively homogenous patient groups. Here’s a snapshot of typical study population demographics: 

  • 83% of research study participants in the U.S. are white 
  • 5% are African American 
  • <1% are Latino 

The traditional model for clinical trials, where patients visit clinical sites to see physicians and allow the clinical study team to collect data, inherently blocks out large groups of patients. Patients living too far away from study centers, those without the economic means or support systems to make regular visits, and those with conditions that inhibit travel (mobility challenges, immunity challenges, etc.) lack access to study opportunities. Add in highly complex studies and a dearth of proven ways to raise awareness of trials in general, huge groups of patients are locked out of clinical research. 

Fortunately, there are now technologies and tools – powered by data-science – that can help. Following are three tips for improving access to studies for more patient communities and increasing study representation. 

#1. Identify Your Patients 

Who are the patients you’re looking for? The data is out there for you to find out. By combining insights from electronic health records (EHR), insurance claims, and/or consumer-use data, Trialbee can help you craft highly accurate personas of patients representative of the disease population. Without divulging identifying data, we can create personas around age, gender, socioeconomic background, and other factors relevant to the disease state. With this information, we can dive into data around where patients are likely to live, what media they use, and what digital communities they might frequent. This allows us to produce highly engaging recruitment materials that draw in more diverse and more qualified patient candidates. 

#2. Meet Patients Where They Are 

That leads us into the next tip – once we know who our patients are, we can reach out to them in the places and through the channels they trust. Understanding where a 50-year-old female patient of Asian ethnicity looks online, in print or in other media to get information about healthcare helps us to deliver educational information about study opportunities to potential candidates who are already in the mindset of looking for healthcare options and/or advice. Similarly, the data-mining technology that helps us identify these patient personas also allows us to alert physicians when one of their patients is a likely match for a study. This is important, as the vast majority of physicians are not regularly involved in clinical research and are so focused on providing care that they have little time to comb through resources like clinicaltrials.gov to seek out potential fits for patients. Data-science can provide a mechanism for alerting these physicians, who have tremendous power as a referral source. 

#3. Simplify the Patient Experience 

Finally, we can all do more to consider the patient perspective on clinical study participation. Forcing patients to travel frequently to clinical sites that are often hours away, along with asking them to meet the requirements of extremely complex study protocols, means that only a small group of patients will have the time, family support, and economic resources necessary to participate. Keeping the patient experience in mind as early as possible – e.g. the protocol design stage – can help to build realistic endpoint data collection plans that allow for the broadest range of patients to take part. For example, designs that use remote data collection technologies can keep patients at home more often.  

While these three tips aren’t the only ways to improve population representation in your studies, they are a good start toward meeting this complicated challenge. For more information on how Trialbee can help, visit www.trialbee.com 

For more information,  request a demo of this solution.


October 12, 2021