Public Health Data: The Key to Building More Inclusive Clinical Trials

In 2020, as COVID-19 death and hospitalization rates continued to climb, it became clear that a vaccine needed to be created – and fast. While immunizations can often take years to develop, COVID-19 researchers, thankfully, weren’t starting with a completely blank slate. Real-world data, like infection rates and hospitalization patterns, helped researchers create a more efficient trial process that accelerated vaccine development, was inclusive of diverse populations, and laid the groundwork for strong public confidence.

Effectively utilizing public health data represents the future of clinical trials: when researchers and trial sponsors can deliver safe solutions to patients faster, and with more accuracy for all populations, everyone wins.

Why Public Health Data Matters

Policy makers and government bodies (including the FDA) often use public health data, also known as real-world data (RWD), to improve community health and allocate resources effectively. But RWD can also be incredibly useful to clinical researchers and trial sponsors. Collected outside of the highly-controlled clinical research process, public health data captures real-world outcomes and patterns that may not be apparent in a lab setting. Benefits to utilizing public health data in clinical research include...

Targeted recruitment that better reflects patient populations:

Certain populations, like Black, Asian, and Hispanic Americans, as well as individuals over the age of 65, are often underrepresented in clinical trials. By integrating real-world patient data into the recruitment phase, researchers can design studies that better reflect actual patient populations, leading to more accurate trials and stronger health outcomes. 

Knowing your target population well can also lead to higher levels of participant trust and higher participant retention. For example, in using RWD to establish targeted recruitment, contract research organization (CRO) Rubix LS reduced participant dropouts by 30% in underserved communities.

Understanding everyday challenges:

Traditional research models may omit the factors that shape health in daily life. Public health data, on the other hand, helps to uncover social determinants — such as cost, access, and lifestyle — that influence both health outcomes and patients’ ability to receive care. It’s important to have these barriers in consideration during clinical trials.

For instance, Rubix LS compiles datasets spanning clinical, genomic, environmental, and social factors, delivering a full overview of patient health that enhances discovery, clinical trials, and real-world evidence. Examples include...

• DoE (Department of Energy) data on how exposure to environmental factors, like radiation, pollution, and more, affects health.

• USDA (United States Department of Agriculture) data highlighting patterns in nutrition, food availability, and consumption that can correlate with metabolic disorders, cardiovascular disease, and cancer risk.

• Geographic Risk Models, which assess disease risk factors like air quality, heat sinks, and soil contamination.

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Relevant goals and benchmarking:

Real-world results help researchers choose trial goals that will actually improve patients’ lives. For example, if RWD shows that a particular population experiences more frequent hospital visits, trial endpoints can be designed to measure whether a treatment reduces those visits.

This creates benchmarks that reflect actual patient needs, rather than abstract clinical targets, and makes sure that study outcomes will be meaningful in everyday care.

Challenges When Using Public Health Data in Clinical Research

There are several challenges researchers may face when accessing or utilizing public health data that can delay or interrupt the clinical research process. Researchers and trial sponsors should understand these common barriers, such as..

How to Integrate Public Health Data into Clinical Research

There are a few best practices that clinical researchers can lean on to ensure that they make the most of public health data, including:

• Collaborate with data experts: Trial sponsors should consider involving data experts, like CROs, early on in the trial design process. This can ensure public health insights are properly utilized from the start. 

Rubix LS, for instance, is a CRO powered by 18M patient data sets and 369 M patient data points spanning clinical, genomic, environmental, and social factors, prioritizing data from underserved populations traditionally left out of clinical research studies. Recently, Rubix LS partnered with Kiffik Biomedical to develop a revolutionary rapid colorectal cancer test.

Together, they will leverage real-world, diverse patient datasets, evidence-based frameworks derived from real-world observations, and intentional deployment of research tools in public health contexts. The goal is to create a personalized diagnostic tool that improves healthcare outcomes for diverse patient populations.

• Invest in relevant technology: In today’s digital world, utilizing RWD without the right tools can be time-consuming, labor-intensive, and expensive. 

Emerging AI tools can transform vast amounts of RWD, like electronic health records, into a format that’s more succinct and easy for researchers to understand. For example, Rubix LS’s AI and machine learning tool, Patient X, analyzes extensive datasets like medical records, genetic information, and environmental factors to identify trends, risk factors, and treatment opportunities that are often overlooked in traditional healthcare models.

• Stay up to date with RWD regulations: Researchers should be aware of regulatory best practices when leveraging public health data. For example, the FDA has issued guidance for researchers submitting documents using real-world data and real-world evidence for drug and biological products. Trial sponsors should keep a close eye on these regulations, as they can change over time.

  
  

What Researchers Need to Know: Key Questions and Answers

1. Why should trial sponsors care about public health data?

Public health data helps to bridge the gap between controlled trial conditions and real-world outcomes.

Clinical trials are conducted in highly-controlled environments, and may not always reflect real-world outcomes. Public health data can help fill in some of those gaps, showing researchers how treatments perform across diverse populations, in everyday settings, and under varying conditions.

2. How can public health data positively impact clinical trial research?

There is a wide range of benefits that public health data can offer to those conducting clinical trials. RWD can help researchers facilitate more targeted recruitment that better reflects patient populations, identify research goals that are most relevant to real patient populations, and better shed light on everyday challenges, like SDOH needs.

3. Where does public health data come from?

Public health data can come from a number of sources, ranging from electronic health records to product and disease registries, national health surveys, hospital records, and more. CROs like Rubix LS compile this diverse range of inputs into datasets that are simple to understand and analyze. In fact, Rubix LS has built one of the largest and most inclusive datasets in the industry, growing from 12 million to 18 million records in just two years.

Using RWD To Design More Representative, Inclusive Clinical Trials

When researchers use RWD in clinical trials, it’s a win-win for everyone involved. RWD can help researchers better understand the needs of diverse populations, the barriers that they’re facing, the outcomes they need most, and where the opportunities lie. Ultimately, this can result in more accurate and inclusive results, plus better outcomes for patients. 

At Rubix LS, our proprietary blend of emerging technologies, like AI, plus a robust rolodex of 18M patient data sets, helps researchers build more representative clinical trials, faster.

You can find more information on our diverse, integrated datasets and how they drive equitable health outcomes here.