Blog | June 13, 2012

A Simple Way To Improve Diversity In Clinical Trials

Source: Life Science Leader
Rob Wright author page

By Rob Wright, Chief Editor, Life Science Leader
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By Rob Wright

As I prepared to moderate a panel discussion on provider perspectives for improving diversity in clinical trials, I was reminded of the Occam’s Razor principle — “The simplest explanation for some phenomenon is more likely to be accurate than more complicated explanations.” I was also reminded of another famous saying — “Physician, heal thyself.”

It has been widely claimed that racial and ethnic minorities, especially in the United States, are less willing than nonminority individuals to participate in health research. I came across this statement in an academic publication, as well as research which disputes this belief. In the February 2006 issue of PLoS Medicine, Dr. David Wendler, first author of “Are Racial and Ethnic Minorities Less Willing to Participate in Health Research,” conducted a comprehensive literature search to identify all published studies that report consent rates by race or ethnicity. He and eight co-authors identified 20 involving the enrollment decisions of more than 70,000 individuals. They found very small differences in the willingness of minorities, most of whom were African-Americans and Hispanics in the United States, to participate in health research compared to non-Hispanic whites. Most of their findings showed statistical nonsignificant differences between groups — with one exception. For 10 clinical intervention studies, Hispanics had a statically significant higher overall consent rate than non-Hispanic whites, thus contradicting the claim that minorities are less willing to participate in clinical research. If we apply these statistical findings, taking into account the Occam’s Razor principle for simplicity, the conclusion is obvious — physicians need to attend to their own faults, in preference to pointing out the faults of others. Yet, past approaches to improving diversity representation in clinical trials have focused on changing the perception of potential participants, not physicians. This has to change. 

The Unconscious Bias Does Exist
Dr. Augustus White, III, M.D., Ph.D., is the co-author of “Seeing Patients: Unconscious Bias in Healthcare.”  Dr. White identified 13 groups in the United States which receive disparate medical treatment (African-Americans, Native Americans, Asian-Americans, Latinos, prisoners, Appalachian poor, immigrants, disabled individuals, certain religious groups, gays, obese, elderly, and women). Honestly, this should really come as no surprise, when you consider that in the field of medicine about 3% of physicians are African-American, with another 3% being Hispanic. I am sure many clinicians who solicit for clinical trial participation think they are above having an unconscious bias. If this were true, then we wouldn’t have data which shows that minority groups are underrepresented in at least some health research studies.

As a former field sales pharmaceutical representative, I promoted Nuva Ring, a prescription method of birth control. I conducted thousands of presentations to clinicians over the years. One conversation which sticks with me, involved a physician who stated that the product was great, but in the wrong market. In his wisdom, it would be well accepted in Europe. He continued with this assertion even when presented with the study “Multicenter Comparison of the Contraceptive Ring and Patch,” published February 2008 in Obstetrics & Gynecology, popularly known as “The Green Journal” and the bible of practicing OB/Gyns. The study demonstrated the statistically significant preference of the ring over oral contraceptives in the U.S. market. “Well, the study wasn’t done in Beaver Falls [where he was located],” he said. This is true. The study was done in Pittsburgh, of which Beaver Falls is a suburb. Unconscious bias does exist. Conclusion: if you want to increase diversity in clinical trials, focus on clinician training and improving awareness of unconscious bias.