At Inspirata, we believe that using technology such as Artificial Intelligence (AI) and Natural Language Processing (NLP) to automate clinical trial matching is an important first step in achieving greater diversity and inclusion among patients who enroll for trials. This would lay a solid foundation for the successful expansion of two high-impact initiatives that are rolling across the healthcare system – namely, expanding quotas for more diverse candidates in clinical trials and offering incentives to providers to discuss clinical trials with more diverse groups of patients.
It is a harsh truth that clinical trials often overlook some of the most necessary minorities, and this lack of inclusion is a major flaw in the efficacy of clinical trials. A recent report from the National Academies of Sciences, Engineering, and Medicine titled Improving Representation in Clinical Trials and Research states that a lack of diversity could lead to a variety of negative outcomes such as underrepresented communities receiving insufficient access to effective medical interventions, compromising supposed universality of certain treatments, and compounding health disparities in populations underrepresented in said trials.
While the connection between technology and more diversity and inclusion may not be immediately obvious to everyone, automating clinical trial matching can reduce friction in several key areas where much of the trial diversity is lost or made difficult for clinicians. Leveraging AI and NLP brings more accessibility and efficiency while reducing the strain on the clinicians who screen for trial patients. Automating clinical trial matching allows for many of the suggestions to diversify clinical trials to be realistically and cost-effectively taken from plan to action.
The Improving Representation in Clinical Trials and Research report states that one of the major ways to combat a lack of diversity is Patient and Community Engagement that “involves inclusive participation of people affiliated by geography, sociodemographic characteristics or shared interests.” Many patients simply do not have the time or the means to travel to the places where the clinical trials are being performed. Research presented in a Clinical Trials Roundtable by Pharma Intelligence suggests that individuals with an income of less than $50,000 per year are more than 30% less likely to participate in a clinical trial. In a study performed by EY US, Financial Considerations were among the largest factors repelling clinical trial participants, with a disproportionate difference between White patients (only 9%) and patients of other races (a whopping 19%).
Inspirata attempts to solve the lack of diversity issue by developing solutions that expand the breadth of institutions’ reach within their catchment areas. In partnership with eminent academic medical centers or large hospital systems, Inspirata can bring its technology to small, affiliated practices in distant rural areas. Making the pre-screening process remote would overcome the barrier of accessibility that leaves many minorities physically unable to engage in clinical trials.
An additional issue hampering clinical trial matching is trial coordinators’ inability to pre-screen and sort enough patients into their trials fast enough. By digitizing that part of the clinical trial matching process, trial coordinators could, in theory, pre-screen and sort 100% of the patients that are seen at their facility. In other words, technology makes filtering for certain sociodemographics and creating cohorts of eligible patients that fulfill new quotas an easier and less resource-heavy process.
While automating clinical trial matching will not solve all the issues pertaining to diversity, inclusion, and equity in clinical trials, it can significantly alleviate some of the foundational obstacles that have traditionally contributed to the under-representation of certain sociodemographic groups in clinical studies.
For more information on the technology Inspirata offers in this area, please visit our clinical trial matching solution page.