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Increasing Diverse Clinical Populations: Geography

Dallas Miles

Lacking Representation

The lack of representation in medical research reveals a lack of access to trial participation for many segments of the greater human population and can endanger the conclusions drawn from study data. A drug may impact different demographics—by age, race, gender and other factors—in vastly different ways. Therefore, trials need to draw in a similarly diverse group of patients to ensure the drug’s effectiveness. This three-part series will examine the varied challenges and solutions to increasing diverse clinical populations. In our final installment, we’ll look at how geographic barriers can prevent a study from being fully inclusive and ways to mitigate issues of distance.

In general, traditionally designed, site-based studies rely on recruiting patients from a set geography that allows for regular visits to clinics. This mechanism evolved directly from the ways in which people historically obtained medical care. Study sites were also medical offices and all medically related interactions occurred in this space. Since clinical research is functionally executed as an extension of medical practice, it was reasonable to recruit, enroll, and collect data from participants where they received their care. Over the last decade, and particularly in the last 2 years, the relationship between a patient and the site of care has dramatically transformed. This transformation includes the use of video calls for medical evaluations and treatment, dispersed clinical engagement, and the completion of medically related forms via remote applications.

While traditional studies are, at times, designed to recruit more diverse populations, they still struggle with the fundamental economics of geography. There are only so many study sites and these are most likely to be large urban medical practices. As a result, study participants often travel long distances, sometimes across borders, for study visits. Recent industry data shows that 70% of study participants live more than two hours from clinical trial sites. Based on current common driving speed limits and usual traffic in the most common study centers, this likely means trips of just under 100 miles each way. Almost 40% of rare disease patients travel over 60 miles for healthcare. A study by The Oncologist uncovered that patients traveled an average distance of 25.8 miles for their visits and patients in NIH-sponsored studies had to travel 39.4 miles on average. When reviewed by study phase, it was determined that patients in phase 1 studies had to travel the farthest, averaging out at 41.2 miles (1). Even at shorter distances, frequent clinic visits can represent a great burden on participants, their families, and caregivers. And participants’ geographic burden is highly relative depending on each study participant’s unique situation.

Because of this, site-based trials can have numerous negative effects on trial recruitment, protocol adherence and overall results. According to one study, the distance between a patient and location-based study center was an independent predictor of missed in-person visits (2). An in-person approach both limits the pool of potential study participants and also locks studies into whatever level of population diversity (or lack thereof) is prevalent in that set study geography.

How DCTs Can Help

Technology can be leveraged to directly address these fundamental causes of participant inconvenience and exclusions. Decentralized clinical trials (DCTs) and the digital approaches they employ bring research opportunities to a more diverse geographic population. Some data suggest that fully decentralized trials with no onsite visits can recruit and enroll participants at remarkable rates (3)(4). These fully decentralized approaches still represent the minority of studies and are not appropriate for all indications. But, a key takeaway is that Sponsors may no longer need to rely solely on those participants living within reasonable proximity to traditional study sites. There are a range of decentralized methodologies that employ both technology and dispersed in-person care to provide more localized services.

Geographic flexibility means sponsors may also be able to expand their pool of potential trial participants. Expanding beyond the radii of typical study centers with DCTs may enable the industry to make significant strides in conducting patient-centric clinical trials. DCT elements such as sensors, virtual visits, and eCOA allow sponsors to deliver a trial experience that is less disruptive for patients and their families. Ultimately, better access is a win for all parties involved. Participants receive better access to therapies, research-naïve sites and clinicians receive more opportunities to participate in trials, and sponsors receive better, more comprehensive data based on more representative patient cohorts.

Inclusive design means much more than simply achieving a diversity goal. It is about making research more accessible to all people who wish to participate. Sponsors and CRO’s can help lead the way through the use of DCT models and proactive outreach that keeps the needs of diverse populations central to our trial implementation. Read our report How DCTs Make Research More Accessible and Inclusive for Participants and Sites to learn:

  • How DCT elements can help address the barriers to effective enrollment
  • Key ways DCT approaches can reduce the need to exclude patients based on geography
  • Strategies for improving access to research for both participants and sites


(1) https://clin-edge.com/news/study-shows-that-with-clinical-trial-participation-comes-the-burden-of-travel

(2) https://clin-edge.com/news/study-shows-that-with-clinical-trial-participation-comes-the-burden-of-travel

(3) https://www.nejm.org/doi/full/10.1056/nejmoa2016638

(4) https://jamanetwork.com/journals/jama/fullarticle/2773108

Noah Goodson, Ph.D.

Associate Director, Consulting, THREAD

As part of THREAD Consulting, Noah applies practical experience in running trials with a decentralized approach to build more efficient and inclusive studies.