How Geographic Location Can Dictate Health Outcomes
Author:
Aracelis Torres, PhD, MPH
SVP of Data & Science
In an ideal world, the quality of healthcare received should not be determined by one’s zip code. Yet, the harsh reality is that socioeconomic status, race, ethnicity, and geographic location often play significant roles in shaping health outcomes. Healthcare disparities are particularly pronounced in rural and underserved areas, which often lack adequate healthcare infrastructure and resources, leading to significant barriers to accessing timely, quality care.
However, there’s hope on the horizon via the transformation of real-world data (RWD) into real-world evidence (RWE), which can offer a promising avenue to dismantle these barriers and foster access and equity for all patients, specifically by improving the inclusivity of medical research and clinical trials.
The Geographic Disparities in Healthcare Access
Understanding the relationship between race and treatment patterns is important in discussions around outcomes and promoting equitable access to healthcare
The impact of socioeconomic status on health is profound, with lower-income communities often facing limited access to quality healthcare services. Furthermore, racial and ethnic minorities bear a disproportionate burden of disease, stemming from systemic inequities in healthcare access, treatment, and outcomes.
This inequality is glaring in conditions such as prostate cancer, where race is a known risk factor. Black men are more likely to present with prostate cancer at a younger age with more aggressive disease than white men, and with a more than two-fold higher rate of metastatic disease at diagnosis. These racial disparities may have deepened during the COVID-19 pandemic, as Black men were significantly less likely to receive surgical treatment for prostate cancer.
Understanding the relationship between race and treatment patterns is important in discussions around outcomes and promoting equitable access to healthcare, but geographic factors and data accessibility can make it difficult to uncover these insights.
The Role of Clinical Trials in Addressing Health Disparities
Clinical trials are essential for developing new treatments and understanding how different patients respond to various interventions. However, it is often challenging to recruit diverse patient populations in studies, especially those from rural and underserved areas. While the industry is making great strides in overcoming these barriers, and technology is making a significant impact, there is still room for improvement.
Additionally, many minority and underrepresented populations hold a certain degree of distrust in the medical research process due to ethical failures in the history of clinical trials. This lack of diversity can lead to findings that do not accurately reflect the broader population, thus affecting how meaningfully and quickly health disparities are addressed.
The Warfarin Case Study
An often-cited example that highlights the impact a lack of diverse representation can have in clinical research involves warfarin, a common anticoagulant used to prevent blood clots.
Initially, most genetic studies of warfarin were conducted with populations of predominantly European ancestry. Early dosing algorithms failed to account for genetic diversity within the U.S. population. For instance, individuals with greater genetic African ancestry typically require higher average daily doses of warfarin, whereas those with greater genetic Asian ancestry often need lower doses.
It took over 60 years post-approval of warfarin for genotype-guided dosing to be recognized as clinically useful. This delay underscores the importance of inclusive research as the lack of diverse data resulted in suboptimal dosing guidelines, increasing the risk of adverse drug events such as bleeding, hospitalization, and death in patients of color.
Real-World Data: A Path to Inclusivity
RWD provides a broader, more inclusive view of patient experiences and outcomes, capturing data from populations across urban and rural geographies, including large academic medical centers, community practices, and those in between
It is critical to learn from examples such as the warfarin case study. In the urologic oncology space, an assessment of phase II and III clinical trials from 2000 through 2017 showed that White patients were continually over-represented. This lack of heterogeneity makes it difficult to understand potential factors that may play a role in treatment effectiveness or adverse effects. Through the power of artificial intelligence and machine learning algorithms, Verana Health has created Qdata® modules, which are research-ready, fit-for-purpose datasets, for prostate cancer and non-muscle invasive bladder cancer. By combining technology and a wide-ranging network of practices, geographically diverse RWD from clinicians in rural and remote areas or from community-based health centers that tend to serve more diverse populations, can be gathered.
RWD provides a broader, more inclusive view of patient experiences and outcomes, capturing data from populations across urban and rural geographies, including large academic medical centers, community practices, and those in between. This plays a crucial role in addressing geographic healthcare disparities and ensuring that medical research and treatments benefit everyone.
By analyzing RWD, Verana Health can translate the data into valuable RWE that provides life sciences teams and clinicians with insights into how treatments perform across various demographics, including for practices that may not have previously been on the radar for clinical trial recruitment.
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