The U.S. Food and Drug Administration issued new guidance earlier this year to promote the diversification of clinical trials in recognition of 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 make up about 39% of the U.S. population, these groups typically only represent 2% to 16% of patients in trials. Without patient data that is 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, or data that relates to a patient’s health status and/or the delivery of health care routinely collected from various sources. These sources include electronic health records, claims and billing activities, and product and disease registries, which provide crucial detail on the nuances of a patient’s medical condition and treatment. Real world data has been recognized by the FDA as an invaluable source to support clinical trial designs and observational studies. In the absence of representative clinical trial participation, real world data can serve as a powerful tool to develop drugs and treatments suitable for people from a diverse array of medical backgrounds. This data collected throughout clinical care can be leveraged to understand results at scale, especially at times when finding trial participants from a broad range of racial/ethnic, age and socioeconomic characteristics is infeasible.

In a study published last year, 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”. In order to address this shortcoming, hospitals and health systems should prioritize not only working with sponsors to optimize the impact of real world data, but also invest in improved data management practices that generate the highest quality real world data. One approach is by prioritizing the establishment of 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 of high quality. By becoming more proactive in the management and distribution of the data they produce, hospitals and 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 contained by 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 work to improve their data management practices, patients will be better supported throughout their medical journeys as their data is matched to clinical trials and new treatments. Better data management practices allow hospitals to better match themselves with clinical trials that are well-suited to their population, including being able to accurately represent the demographics of their patient populations.

In all, the medical community will be able to better understand the way in which treatment modalities affect subpopulations and alter their approaches to better provide care by leveraging clinical data. With far-reaching implications into clinical trials, the greatest investment hospitals can currently make is in data management infrastructure. With the right practices and supporting staff, the health care industry will be able to overcome the obstacles typically associated with the collection and interpretation of 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 the process of 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 of data and research at Q-Centrix.

Published in Clinical Research News. Read the article here.