Clinical trials have usually been done in very controlled settings. These strict rules can sometimes make it hard to apply the results to real life. Real-world data (RWD) helps by giving information collected during normal healthcare visits. This includes electronic health records (EHRs), pharmacy records, insurance claims, lab test results, and patient registries. Unlike traditional trials, RWD shows what actually happens with different patients. This makes the research more useful for everyday medical care.
In the United States, companies like TriNetX, OMNY Health, Datavant, and Briya have created platforms that collect and organize large amounts of real-world data from many healthcare providers. For instance, TriNetX has a network with clinical data from over 40 million patient records worldwide. This helps researchers find groups of patients quickly, check treatment patterns, and speed up recruiting people for trials. Their system links trial sponsors, such as drug companies, with healthcare providers and allows them to ask real-time questions. This improves how studies are designed and how patients are recruited.
By letting healthcare groups work together using shared real-world data, these platforms lower the problems often found in clinical research. These problems include setting up data-sharing agreements and handling different types of data systems. They also help sponsors find the best places to conduct studies. This can lead to faster enrollment in trials and better results.
Hospitals and clinics in the United States gain several benefits by joining clinical trials that use real-world data. One obvious benefit is better patient recruitment. For example, the University Hospitals of Leicester in the UK worked with TriNetX since 2021 and went beyond their goal of recruiting 30 patients for a study called REDEFINE 3. They found eligible patients more quickly using real-world data. Although this example is from the UK, hospitals in the U.S. face similar recruitment challenges and can apply the same ideas.
Being part of good clinical trials gives patients more treatment options and helps healthcare providers build a reputation as research-active centers. Participating in research also helps hospitals get sponsored trials, which can bring extra funding and resources. Real-world data platforms let providers show their patient populations and care abilities clearly. This builds trust and long-term partnerships with sponsors.
Moreover, studies using real-world evidence (RWE) help healthcare providers add to medical knowledge about how well drugs work, their safety, and long-term effects. This way, their clinical data becomes more than just routine care information. It turns into data that supports medical progress. Providers can also share diverse patient data, which helps address issues of diversity and fairness in research—a topic noted by experts like Dr. Mitesh Rao, CEO of OMNY Health.
Sharing data in healthcare is complicated because of strict privacy laws like HIPAA in the U.S. Real-world data platforms handle these issues using advanced methods that remove patient identifiers while keeping the data useful. For example, Briya uses a three-step process to keep data anonymous and uses smart contracts that make sure data-sharing rules are followed automatically.
Network systems run by companies like TriNetX let healthcare providers join research without sending their raw data outside their own systems. Instead, queries run on connected systems, and only combined, anonymous results are shared. This reduces data exposure and makes managing data across many groups easier.
These privacy-focused methods meet legal rules and build trust with patients and healthcare providers. This encourages more healthcare groups to join research networks.
AI and workflow automation play a big role in using real-world data in clinical trials efficiently. These technologies make work simpler, cut down manual tasks, and improve data accuracy.
AI systems quickly analyze complex data sets and find patients who qualify for trials based on specific criteria. This cuts the long manual review done by research staff. For healthcare IT managers, using AI means faster patient screening and quicker trial enrollment, which helps speed up trial timelines.
Workflow automation helps by handling repetitive jobs like scheduling follow-up appointments, sending reminders, and keeping records up to date. Automated phone systems can answer patient questions about trials, so front-office staff can focus on more important work. For example, companies like Simbo AI offer phone automation that fits into healthcare operations and helps improve communication during the trial process.
Also, AI assists with cleaning, sorting, and combining data from many sources. This includes organized data like lab results and unorganized data like doctor’s notes. This work is important for turning raw clinical data into research-ready sets. Companies like Datavant and OMNY Health specialize in making EHR data anonymous, standardized, and linked across providers.
By using AI and automation, hospitals and clinics not only make clinical trial work easier but also improve everyday office tasks. This leads to better use of resources and a better experience for patients.
Collaboration in clinical trials involves more than just sharing data. The Clinical Trials Transformation Initiative (CTTI) is a group in the United States that works to improve trial quality and efficiency using research-based methods. CTTI brings together healthcare providers, sponsors, regulators, patients, and payors to find solutions that support using real-world data in research.
One goal of CTTI is to involve patients early in designing trials to make sure research meets their needs. They also support decentralized trial models that use digital tools to make participation easier no matter where patients live.
This cooperation encourages healthcare groups to be active partners in clinical research rather than just sites where trials happen. It promotes responsibility, openness, and communication across different stakeholders, which helps healthcare administrators who manage clinical trial programs.
The use of real-world data and new technology is changing how clinical trials are done in the U.S. Healthcare providers who take part in these networks can get faster access to research, enroll more patients, and improve patient outcomes.
As more healthcare groups join these networks, clinical studies will represent more diverse populations. This makes findings more useful for everyone and helps with fairness in healthcare. Collaboration platforms also create new ways for medical centers to get funding through sponsored trials.
New AI and automation tools will keep reducing the workload linked to research work. Tools that find patients, check eligibility, and handle follow-ups lower the burden on busy staff. This can help smaller medical practices take part in research more easily.
Overall, real-world data and related technology offer an effective way for U.S. health systems to connect with sponsors and help improve drug development and medical care.
Healthcare organizations in the United States that want to improve their involvement in clinical trials should think about using real-world data networks and AI-driven workflow automation. These approaches support better teamwork with trial sponsors, make research easier, and help patients get new treatments faster.
TriNetX envisions a future where data and intelligence accelerate innovation across the global healthcare ecosystem, enabling enhanced patient care and medical advancements.
TriNetX’s mission is to operate the world’s broadest federated network of real-world data in partnership with healthcare providers, applying intelligence to accelerate innovation across the healthcare ecosystem.
TriNetX offers end-to-end support throughout the drug development lifecycle, enhancing clinical trial designs and refining post-market safety measures using real-world data.
Real-world data enhances study feasibility, evaluates criteria and comparators, and facilitates connections between sponsors and healthcare organizations for improved clinical trial collaborations.
TriNetX utilizes real-world data to identify potential clinical trial sites, fostering connections that allow sponsors to engage with healthcare organizations actively caring for patients.
Real-world evidence answers questions surrounding safety, efficacy, and value, providing critical insights for stakeholders including patients, regulators, and researchers.
TriNetX combines harmonized drug safety data from public sources, electronic health records, and claims to enhance signaling algorithms and improve pharmacovigilance.
The TriNetX LIVE™ platform allows users to query millions of de-identified patient records, analyze treatment patterns, and enroll patients in clinical trials efficiently.
TriNetX employs epidemiologists and clinical science consultants who leverage extensive real-world data to generate evidence for better patient outcomes and insights.
TriNetX enables healthcare organizations to conduct more informed research, optimize protocol goals, and remain at the forefront of clinical research advancements.
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