For too long, rural and underserved communities have been left behind in medical research, clinical trials, and access to the latest medicines. While more accessible urban populations participate in clinical trials, research continues to lag significantly in rural areas with fewer academic research centers and participating physicians. Real-world data provides powerful tools to generate insights to bridge this gap and improve health equity for the most isolated populations.
By collecting data from electronic medical records, insurance claims, and patient wearables, researchers can now study treatment effects and outcomes across a wide range of demographics without geographic limitations. For example, real-world analysis shows that factors largely outside the control of rural residents, such as lack of access to healthy food, limited infrastructure, lack of health care providers, and demographic and socio-economic disparities, , provides insight into how it impacts health status and access to medical care. .
Identify gaps in quality care
In the Appalachian region of the United States, researchers at the National Cancer Institute have been working with communities for more than 30 years to address disparities in cancer incidence, using real-world data to improve local cancer screening rates. We've been working on ways to improve and testing those methods.
In the Appalachian program, researchers surveyed community leaders and residents about their motivations and barriers to seeking health care, particularly preventive care such as vaccinations. Identifying ways to penetrate different communities in ways that are culturally resonant and sensitive to social nuances is key to increasing participation rates.
Enrollment in clinical trials is one of the biggest challenges we face in ensuring adequate representation of rural patients. We learned this with COVID-19. Initially, trials were held in large cities with easy access for patients, and most of the patients were elderly, white, and middle class. COVID-19 is new and of course not limited to these demographics. As an industry, we have had to quickly pivot to ensure we include patients of all races, ages, and socio-economic statuses. I think it's fair to say that the COVID-19 clinical trial was the most important and widely observed clinical trial in human history. Patients were identified and efforts were made to include rural patients. This collaborative approach has provided a global solution to change the trajectory of the virus and has saved countless lives.
Empowering remote communities
Additionally, real-world data research positions clinical trials more effectively. Retrospective and prospective studies provide objectively interpreted data to those who approve and control the results of these efforts.
By analyzing these real-world data assets, specifically electronic health records, we can analyze the prevalence of nutrition-related diseases, utilization of preventive care, availability of specialty care, and transportation faced by rural populations. Understand barriers etc. These data sources can also reveal disparities in health outcomes and mortality based on rural socioeconomic status.
Identify effective solutions
The only costs required for such real-world data analysis are the costs of data acquisition and analysis. This is a fraction of the cost required to investigate these topics through new clinical trials and primary data collection. Real-world evidence allows researchers to maximize limited access to rural medical patients and gain data-driven insights into the environmental, systemic, and socio-economic factors underlying rural health challenges can do. Evidence can inform policy changes and resource allocation to improve equity and access.
Research shows that rural areas have higher uninsured rates than urban areas. Research shows that this is partly due to a lack of insurers participating in rural markets. (In fact, about 10% of local participants in the Affordable Care Act market had access to only one participating insurance company.) In response, many states It strengthened coverage and waived many cost requirements for state Medicaid programs and state-regulated insurance plans.
Dealing with delicate challenges
Other efforts support the use of real-world data to improve conditions that contribute to rural health problems. For example, the Robert Wood Johnson Foundation provides grants to rural communities to develop creative solutions to health care challenges. Funded projects have addressed issues such as food insecurity, transportation barriers, health care provider shortages, and mental health.
In addition to addressing the needs of entire rural communities, many other efforts leverage real-world data to address challenges specific to specific cohorts. The Veterans Administration's Office of Rural Health has partnered with several outside organizations to examine important issues affecting rural veterinarians, including barriers to mental health treatment, risks of substance abuse, and care coordination challenges. We are partnering with. This effort aims to improve access to veteran care for this underserved group by examining the lived experiences and distinct barriers faced by rural veterans through data analysis and community-based research. We continually provide tailored policies and programs to improve quality and outcomes.
Capturing experiences and results
Real-world data provides a valuable glimpse into the reality of people's daily lives, their ups and downs, and everything in between. Controlled studies allow us to see only a small part of the participants' experiences. However, real-world data is much more widespread. We document all kinds of health journeys, not just prescribed paths laid out by researchers. Therefore, real-world data is essential for a holistic understanding of health outcomes.
The real-world data is also comprehensive in ways that are not common in previous studies. It is drawn from populations often left behind in research: people with multiple chronic conditions, the elderly, and patients from rural and low-income areas. Real-world data also allows specific challenges to be considered and studied. This is important because it democratizes the benefits of medical research so that it reaches more people than just a few groups.
Randomized trials continue to play an important role. But don't underestimate real-world data. It provides his 360-degree perspective on health that research in controlled environments lacks. This broad lens makes real-world data a powerful asset as we work to promote health equity and optimal well-being for all people. Guided by real-world evidence, we can build a future where your health status is no longer determined by your postcode or bank account – a future where everyone has a fair chance to live the healthiest life possible. Masu.
Photo: Malekliás, Getty Images
Stuart Green is senior vice president and general manager of Veradigm's life sciences business. He is well-versed in the life sciences information services and clinical research industries and is recognized for consistently delivering profitable growth against targets. He has also been successful in increasing client satisfaction and expanding relationships to form long-term, mutually beneficial business partnerships. Stuart has held senior leadership roles at IQVIA, Symphony Health, and Si.
