Three Essential Data Insights for Optimal Trial Site Feasibility, Inclusivity and Selection
Social Determinants of Health & Clinical Trials
When you google the term “clinical trial,” the first thing that comes up is the National Library of Medicine site all about clinical research. It’s a great foray and beginner’s guide to understanding all about how trials are recruited, conducted, and run.
There is a frequently asked questions section and the most interesting question was: “Where are clinical trials conducted?”
Clinical studies can take place in many locations, including hospitals, universities, doctors’ offices, and community clinics. The location depends on who is conducting the study.
Social Determinants of Health (SDOH) are the conditions in which people live, learn, work, and play, which affect health access, outcomes, and overall quality of life. Collectively, SDOH factors contribute significantly “to the social patterning of health, disease, and illness,” according to the Centers for Disease Control & Prevention (CDC).
So, with this knowledge — it begs the question — why are clinical trials not meeting people and recruiting patients where they live, learn, work and play? Shouldn’t we conduct the studies where we find the patients who need the medicine?
Social Factors Impact Care Outcomes
In a recent podcast with two industry veterans, we discussed the role and entry of commercial players into the clinical trial space–retail pharmacies and big box stores.
If we were to pair the two, ideally, we would be able to recruit, educate and reach patients wherever their trusted pharmacist or local store was located. But that’s not the case. At least, not yet.
We keep trials in research triangles; university hospitals and city centers. What about people that don’t live near those locations; lack transportation or live in a rural location?
How would they ever learn about the trials to participate in? The answer is–currently–they don’t.
A 2019 study at the Yale School of Medicine suggests that the social determinants of health may have an impact on clinical trial results, revealing that patients receiving their care in low-income areas face health disparities that patients in higher income areas do not.
The study utilized data from a hypertension clinical trial. The trial enrolled tens of thousands of patients and sought to examine the effectiveness of three hypertension drugs.
What they learned was where a patient receives their care – which can be tied to the societal factors a patient faces every day – will have an impact on their care outcomes, regardless of their treatment plans. Without taking these SDOH factors into consideration when planning trials, we can’t ever really test the full equitable and inclusive efficacy of a drug or therapy.
The Role of Trust and Transparency
The National Brain Tumor Society (NBTS) even launched a brain tumor clinical trial finder to help boost patient participation in treatment development. According to the society, brain tumor clinical trials have seen limited patient engagement in recent years, likely because patients do not know about these trials and cannot access information about clinical trials online.
The answer is — healthcare is sitting on massive amounts of data, all siloed in electronic health records, commercial pharmacies, within health systems or payers, or even the health tech companies themselves. How do we bring it all together?
It starts with trust and doing something with the data — ingest it, surface it, and make it available on an enterprise level for analysis and action.
Trust and transparency are crucial to the future of clinical trials, especially those involving underrepresented groups. Communication through trusted channels ensures that patients understand the value of their participation in clinical trials. And as it stands, the most trusted channel remains to be doctors who serve and are a part of these very communities. In addition to meeting patients where they are, we need to include an education component. Embedding health literacy into clinical trials from the beginning of the process can improve recruitment and retention.
Start with What You Know
This is a challenge we often help our clients with. H1’s Trial Landscape offers users access to comprehensive profiles of currently active and potential investigators. These profiles include details on the academic experience of investigators, such as publication and congress involvement, as well as clinical experience through the patient population access and clinical trial involvement.
So we’ve put together three of our best practices and often most requested data insights that we find helpful:
1. Investigator Profiling
Get a 360º view into the experience, capacity and patient access and potential engagement capabilities of investigators of interest and compare profile details based on access to target patient populations and competing engagements.
2. Site Analysis
Try and analyze sites by understanding the impact of research taking place there and to evaluate their experience, capacity and interest to support clinical trials.
3. Competitive Intel
Understand and keep track of the clinical trials competitive landscape. This capability enables users to assess and visualize which investigators and sites are involved in new trials to diversify your partners, and understand where other life sciences companies are locating their clinical trials.
With a partner like H1, data can help clinical operations teams access insights otherwise unavailable to them such as trial enrollment rates, geographic clinical research hotspots, sponsor affinity by investigators and research sites, access to comprehensive HCP and site profiles mapped to the trials, and unique trial details coming from a multitude of trial sources such as registries, social media and publications.
4. Diversity & Inclusion Metrics
Develop a Diversity plan according to the latest FDA guidelines and we encourage companies to submit a plan that outlines the operational measures that will be implemented to ensure diverse clinical trial participation (based on age, gender and race) to improve the generation of evidence regarding safety and effectiveness across the entire population.
We provide a number of diversity and inclusion metrics on both providers and their consecutive patient populations. This data includes patient age, gender and racial mix, patient income and education level; as well as self-identified ethnicity, languages spoken and gender of providers. Here are a few of our most commonly surfaced metrics to assess diversity.
- Diversity data representation in HCP and Institution profiles
- Patient and provider Diversity filters when searching for HCPs
- Diversity sorting when sorting HCPs of interest
- Patient and provider diversity metrics in raw data exports
It’s not a problem that we can solve overnight — it’ll take the full commitment of site leaders; pharma and life sciences business leaders and a concerted effort on the part of the data providers and platforms like H1 — to surface relevant deep data sets and insights that help move the needle and connect the bench to the bedside for patients who need tomorrow’s medicine today.
Want to learn more about how H1 can help? Talk to one of our experts today.