Can AI Help You Recruit for Your Patient-Centered Clinical Trials?

Patient-centered clinical trials place the participant at the heart of the study process. It seems crazy to think that this has not always been the case – after all, without patients there can be no clinical trials, no data to comb through, and no new discoveries. With patient-centered trials, patients’ needs, preferences, and experiences are prioritized to improve recruitment, participation, and trial outcomes. Patient-centric approaches are designed to increase patient engagement, encourage better plan adherence, and therefore produce more, and more meaningful data. As we seek to create new therapies that work for everyone, we find ourselves striving to make clinical research more accessible to the broadest possible range of people. Patient-centered trial designs are part of any strong strategy here.

However, finding the right patients for new studies remains a challenge. Often, recruitment processes rely on direct-to-consumer marketing or manual chart reviews, which are time-consuming, labor-intensive, and prone to inefficiencies. For clinical trial sites and sponsors, enrolling the right patient at the right time is a critical factor in the success of a trial. Delays in recruitment can have profound implications, both for the cost of the trial and for its ability to generate meaningful data. This is where AI-powered solutions, such as the BEKplatform, come into play.

How Does AI Help?

BEKhealth’s AI-driven BEKplatform is designed to tackle patient recruitment challenges head-on by leveraging advanced algorithms that sift through electronic medical records (EMRs) to identify eligible patients quickly and accurately. Traditionally, recruitment has involved a high degree of manual intervention, with site coordinators tasked with reviewing medical charts to match patients to trial criteria. This laborious process limits scalability and often results in missed opportunities. BEKplatform automates this process, significantly improving both the speed and precision with which patients are identified.

By analyzing both structured and unstructured EMR data, the platform can match patients to clinical trials with a higher degree of accuracy than manual methods. The system generates a longitudinal patient graph—essentially a comprehensive, organized view of patient data—that allows trial coordinators to query and find eligible patients faster than ever before.

Advantages of AI-Powered Recruitment

1. Speed and Accuracy
   One of the platform’s standout features is its ability to identify 10 times more qualified patients and double the number of enrolled patients in clinical trials. This is achieved by the platform’s deep-learning neural network, which interprets patient data with over 90% accuracy. By constantly updating the system with new data, the platform ensures that the pool of potential participants is refreshed daily, excluding those who no longer meet the inclusion criteria and including new eligible patients in real-time.
2. Data-Driven Decision Making
   Beyond identifying eligible patients, BEKplatform provides real-time feasibility reports that help researchers analyze their patient populations and make informed decisions. This feature is particularly valuable in determining trial feasibility—whether the right population exists at a site to conduct a study—before investing significant resources. These insights allow sponsors and sites to avoid costly trial startup delays and misfires, thus optimizing the allocation of time and resources.
3. Time Savings
   The platform’s ability to automate chart review can save hundreds of hours for site coordinators, who would otherwise spend considerable time manually sorting through patient records. By eliminating this tedious task, BEKplatform allows clinical staff to focus on more high-value activities such as patient engagement and trial management.
4. Scalability and Integration
   BEKplatform is designed to integrate seamlessly with existing EMR systems. With over 25 EMR connectors that cover 85% of the market, BEKhealth has built a system that can rapidly implement and operate across different healthcare organizations. This means that new sites can adopt the platform within a matter of weeks, accelerating the entire recruitment process.
5. Human-Powered AI
   While the platform is largely automated, BEKhealth emphasizes a human-in-the-loop approach. Their team of research nurses works closely with sites to ensure that the platform is tailored to meet the specific needs of a trial, providing hands-on support. This collaboration helps ensure that AI-generated outputs are relevant and reliable for the clinical context, further improving the platform’s usability and effectiveness.

The Importance of AI in Enabling Patient-Centered Trials

In a patient-centered clinical trial, the emphasis is on recruiting a population that reflects the diversity and specific needs of the target population. This requires recruitment methods that are inclusive, efficient, and capable of identifying patients who may not respond to traditional marketing campaigns. AI solutions like BEKplatform enhance this process by removing unconscious bias and human error from the recruitment equation, ensuring that all eligible patients, regardless of background or geographical location, have an equal chance of participating in clinical research.

Furthermore, by improving the speed of patient recruitment, AI platforms like BEK can also shorten the overall timeline of clinical trials. This is a significant benefit, as patient recruitment is one of the most common causes of delays in clinical research. Faster recruitment means that patients can receive potentially life-saving treatments sooner and that sponsors can bring their products to market faster.