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Health inequities shedding new light on clinical trials

clinical trials clinic blood test

The importance of Social Determinants of Health

Although chaos seems to be a recurring theme in the world at the moment, the one good thing that is arising from the ashes is inequity awareness. This is an unfortunate theme that I have tried to both question and bring mindfulness to over much of my adult life. I am a physician, a researcher, a veteran, and a patient. I have seen (and tried to help) situations of health disparities for well over a decade. I am happy to report, now that this awareness has been brought into the light- people seem to be much more receptive in learning about social determinants of health (SDoH). Beyond that, even understanding that capturing and addressing SDoH information can help patients, people, and industry to be more successful.  

Lately I find myself speaking to many people in the world of pharma, where it is no wonder that SDoH is a concern. Phase 3 clinical trials are expensive, with odds of 3 out of 5 for successful approval. Not very good odds. Phase 3 clinical trials usually span anywhere between 1 to 4 years, sometimes longer, and can involve 300 to 3,000 people. A lot can happen in that timeframe. That’s why real-world evidence is necessary, and why we must be vigilant to the information that is available in unstructured data. These conversations with pharma have certainly conjured many memories of the days when I was a researcher. 

Past experience under the spotlight

Unintentional bias is an unfortunate norm

I distinctively recall how the cohort was biased, not purposefully, but most clinical trials participation requires hours of “free” time. How many full-time working people do you know to have been a participant in a clinical trial? Not many, I’m almost certain...especially if they would have to take precious vacation time to do so. How does this biased collection of research cohorts represent the population? It doesn’t. Another unfortunate although more often exception from the norm- there are those participants that lack employment and partake in clinical trials as their career

Social Determinants of Health are everywhere

From my experience, most participants had the misfortune of having the actual clinical problem and desperately wanted to find something, anything, that might alleviate the said ailment. Of those participants, many lived alone, lacked social support, had transportation issues, etc. Even if the participants didn’t come into the trial with certain stressors - that doesn’t mean that these won’t develop.  I know plenty of people with an ailment that couldn’t maintain a job or lost social support over the years. Many clinical trials fail because participants drop due to missed appointments; understanding the underlying issues (e.g. potential transportation problems) can help design protocols to ameliorate this problem. 

The sun is shining once again – utilizing NLP to learn from the Data

Natural Language Processing (NLP) is necessary to capture social determinants of health and other relevant data from the visit reports, so you can utilize this knowledge in informed ways. Between my own experience and discussions with colleagues, we can say for certain that these are a few areas where understanding SDoH can make an impact and improve clinical trial recruitment and results: 

  • Determine how to translate observed environmental inequities into clinical research
  • Ensure clinical trial recruitment inequities are addressed, so that the trial cohort is representative of the broader population.   
  • Enable a more granular approach to assess outcomes during clinical trials. For example, did the drug itself fail or were there extenuating circumstances that contributed to lack of efficacy
  • Integrate and assess factors of health inequality within analyses, models, and initiatives


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