Sync up diversity in clinical trials

Clinical trials are out of sync. They rarely include participants in ethnic proportion to those actually diagnosed with the condition being studied. This shortcoming has created gaps in our understanding of diseases and treatment effectiveness across populations and these gaps in knowledge can impede the quality of healthcare decisions, counseling, treatment, and development of more effective medications or interventions.

HealthVerity recently hosted a webinar that explored a synchronized solution to increasing diversity in clinical trials. If you missed the webinar, here’s a brief recap:

The real-world impact from a lack of diversity

In a study HealthVerity conducted with the Beckman Group, we found that of the 1,262 clinical trials conducted in 2022, over 80% of participants were White/Caucasian, 11% were Asian and less than 7% were Black/African American. In 41 trials conducted for hepatitis B and C treatments, nearly 63% of patients were Asian, but less than 18% of people with hepatitis B or C are Asian. Less than 5% of participants in these trials were Black/African American, but over 29% of people impacted by the conditions are Black/African American.  

Similarly, in analyzing 20 clinical trials for stroke treatments, we found that over 23% of participants were Asian, but only 5.5% of Asian people suffer from strokes, whereas just under 3% of participants were Black/African American, but over 18% of Black/African American people experience strokes.

Race and ethnicity can contribute to interindividual differences in drug exposure and/or response, which may alter the risks and benefits in certain populations. In fact, approximately 20% of new drugs approved in the past six years demonstrated differences in exposure and/or response across racial and ethnic groups, translating to population-specific prescribing recommendations in a few cases.1 

As an example, in a study that looked at dosing requirements needed with Warfarin to maintain a therapeutic INR (standing for International Normalized Ratio, this determines the risk of bleeding or coagulation in patients), it was determined that Asian populations required approximately 25 milligram doses, while Black/African American patients required significantly more at approximately 40 milligrams.2 This demonstrates the need to study broad and diverse populations, particularly with more precise medicines like cell and gene therapies.

When data from diverse populations are lacking, not only can it hinder the right patients from getting the right drug at the right time, additional post-marketing studies may be recommended, creating more expense and delays.

This evidence shows that it’s better for everyone if we have greater inclusivity in clinical trials, but if it was easy, everyone would be doing it. While the FDA has issued guidance on increasing inclusion of underrepresented racial and ethnic groups in clinical trials, the industry hasn’t had the right kinds of tools to be able to study data in a privacy-compliant way in order to increase diversity. It’s time to sync different.

Better medicine through diversity

Historically, to determine the potential diversity of a healthcare providers’ patients, you would look at the racial composition for the zip code in which they practice. But just because a physician practices in that zip code, it doesn’t mean their patient population reflects the diversity of the area. 

By leveraging our privacy expertise and the nation’s largest healthcare and consumer data ecosystem, we developed the HealthVerity Provider Diversity Index (PDI), a nationally-syndicated report that offers a pathway for the inclusion of minority groups in clinical trials by synchronizing medical, pharmacy and social determinants of health (SDOH) data to calculate the racial and demographic composition of patients cared for by each provider, while maintaining HIPAA compliance. 

The PDI provides the following unique patient-level characteristics for each of the over 2 million NPIs captured in the report:

  • Race
  • Gender
  • Age range
  • Payer type (Medicare, Medicaid or commercial)
  • Income range
  • ICD-10 code

This allows you to see which patients with which diseases have which characteristics, providing entirely new and actionable patient insights at the provider level. You can review the demographic profiles for patient populations by NPI and target clinical trial investigators with patients reflective of the population you’re studying, in a HIPAA-compliant way. This saves time and resources by eliminating sites that lack diversity and impede trial success.

PDI in action

A top pharma company was actively recruiting for a phase 4 trial for a treatment for Crohn’s disease and ulcerative colitis. Given FDA guidance, the manufacturer wanted to ensure that the participants mirrored those impacted by the chronic conditions. 

The manufacturer began by mining past efforts, working with their CRO to compile a list of possible investigators based on the number of patients fitting the clinical inclusion and exclusion criteria. Then, using PDI, they matrixed investigators based on patient density and racial mix. Based on their knowledge of the patient populations and SDOH, they were able to direct advertising, education and recruitment efforts accordingly. 

With PDI, the pharma company was better able to align with physicians who served diverse patient populations that could support their recruitment goals, allowing them to run a better study from day one.   

By leveraging the PDI, you can target clinical trial investigators with patient populations reflective of the condition you’re studying to help recruit more diverse and inclusive trial participants, directly addressing FDA guidance, and saving time and money, to advance the science.

Request a PDI data sample

1Ramamoorthy, A., Pacanowski, MA., Bull, J., Zhang, L. (2015). Racial/ethnic differences in disposition and response: Review of recently approved drugs. Clinical Pharmacology & Therapeutics. Volume 97, Issue 3. Pages 263-273. March 2015.

2Johnson, J.A. Differences in Cardiovascular Drug Response. Circulation. Volume 118, Issue 13, Pages 1383-1393, DOI: (10.1161/CIRCULATIONAHA.1070704023)

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