Contributed Commentary by Victor Wang, Q-Centrix 

September 9, 2022 | The U.S. Food and Drug Administration issued new guidance earlier this year to promote the diversification of clinical trials and recognize its role in achieving health equity. Despite significant variations in treatment efficacy among ethnic and racial groups, clinical trials for pharmaceuticals remain predominantly white.  

While people of color comprise approximately 39% of the U.S. population, they typically only represent 2% to 16% of trial patients. Without patient data representative of the general U.S. population, disparities in treatments and care may continue to widen. However, unlocking the clinical data captured by hospitals and health systems may be the key to closing gaps in care. 

Hospitals and health systems are the most consistent and reliable sources of real-world data—data related to a patient's health status, or the delivery of care routinely collected from various sources. These sources include electronic health records, claims and billing activities, and product and disease registries, and they provide crucial detail on the nuances of a patient’s medical condition and treatment.  

The FDA has recognized real-world data as an invaluable source for clinical trial designs and observational studies. In the absence of representative clinical trial participation, real-world data can be a powerful tool for developing drugs and treatments suitable for people from diverse medical backgrounds. This data collected throughout clinical care can be leveraged to understand results at scale, especially when finding trial participants from a broad range of racial/ethnic, age, and socioeconomic characteristics is infeasible. 

In a Journal of the American Medical Informatics Association study published last year (DOI: 10.1093/jamia/ocaa224), researchers found that, although real-world data has a high potential to augment clinical trials, the “incorporation of real-world data into clinical trials focused on medications and surgical procedures was found to be underused.”  

Hospitals and health systems should not only prioritize working with sponsors to optimize the impact of real-world data but invest in improved data management practices that generate the highest quality real-world data.  

One approach is to establish a modern data management infrastructure that eliminates data silos among hospital departments, allowing for easier transmission of accurate data across networks. This includes training and hiring clinical experts who can abstract data to ensure it is high-quality. By becoming more proactive in managing and distributing the data they produce, health systems are poised to better assist biopharma and hospitals in understanding the treatment modalities best suitable for the true patient population and close gaps in care. 

The wealth of data in hospitals and health systems today will undoubtedly be instrumental in improving patient outcomes and achieving health equity. In fact, a recent report from the National Academies of Sciences, Engineering, and Medicine found a substantial social and financial cost resulting from underrepresentation in clinical trials and research; an improvement could be worth billions of dollars in savings to the United States.  

As hospitals and health systems improve their data management practices, patients will be better supported throughout their medical journeys as their data match clinical trials and new treatments. Additionally, better data management practices allow hospitals to match themselves with clinical trials that are well-suited to their population and accurately represent the demographics of their patient populations. 

In all, the medical community will better understand how treatment modalities affect subpopulations and alter their approaches to providing care by leveraging clinical data. With far-reaching implications for clinical trials, the greatest investment hospitals can currently make is in data management infrastructure. With the proper practices and supporting staff, the health care industry will be able to overcome the obstacles typically associated with collecting and interpreting clinical data.  

Improved data systems allow hospitals to more systematically identify patients eligible for clinical trials, regardless of demographic details, dampening any point-of-care biases in recruiting patients for clinical trials and providing data on what is and is not working in the journey to diversify and expand clinical trials. 

Victor Wang is the senior vice president for real-world data strategy at Q-Centrix, a Chicago-based health care analytics and clinical data management firm. It is the largest exclusive provider of clinical data management solutions to over 1,000 partners nationwide. Before Q-Centrix, Wang was the VP of Data Products at ConcertAI and a founding team member of its predecessor organization. He can be reached at vwang@q-centrix.com.