Preventing Patient Dropouts with AI-Based Outreach: How AI Enhances Patient Retention in Clinical Trials

Patient retention is a major challenge in clinical trials. High dropout rates not only increase costs but can also delay results, complicate data analysis, and even jeopardize the success of a study. To address this, artificial intelligence (AI) is emerging as a powerful tool for improving patient engagement and retention by offering real-time insights and tailored outreach. BEKHealth’s AI-powered platform, combined with its partnership with Areti Health, helps clinical researchers monitor engagement and reduce patient dropout rates by addressing concerns and barriers in real time.

The Cost of Patient Dropouts in Clinical Trials

When patients drop out of clinical trials, the consequences are severe. For each participant lost, a significant amount of time, money, and resources go to waste. Moreover, patient dropouts can:

• Compromise study results: Inconsistent data or reduced sample sizes make it harder to draw meaningful conclusions.
• Increase trial duration: Finding and enrolling replacement participants takes time, delaying trial completion.
• Drive up costs: Every patient dropout requires additional recruitment, which significantly increases overall trial expenses.

Given these stakes, preventing patient dropouts is critical. That’s where AI-driven patient engagement strategies come into play.

How AI Improves Patient Retention

AI offers unique capabilities for monitoring patient behavior, identifying early signs of disengagement, and tailoring outreach efforts to keep participants on track. Here’s how AI can transform patient retention in clinical trials:

• Real-Time Monitoring of Patient Engagement
• AI platforms like BEKplatform can track patient interactions with trial materials, responses to communications, and engagement with study protocols in real time.
• By monitoring these behaviors, AI can detect when a participant is becoming less engaged—whether it’s skipping check-ins, missing appointments, or delaying data submission.
• Predictive Analytics to Flag At-Risk Patients
• AI uses predictive algorithms to analyze patient data and identify patterns that indicate a higher likelihood of dropout.
• This could include social determinants of health (such as access to healthcare or transportation issues) or behavioral data (such as delayed responses or missed communications).
• By flagging at-risk patients early, clinical teams can intervene before dropouts happen.
• Personalized, Automated Outreach
• AI-driven systems can automate personalized outreach campaigns to re-engage participants.
• For example, if a patient hasn’t checked in as expected, the platform can send a reminder or offer resources tailored to that participant’s specific concerns (e.g., transportation assistance, additional support).
• This personalized approach ensures that participants feel supported and heard, reducing the likelihood of disengagement.
• Adjusting Strategies in Real Time
• With AI, patient engagement strategies don’t have to be one-size-fits-all. Instead, AI systems can adjust outreach in real time based on individual patient behavior.
• If a participant is flagged as disengaged, the platform can automatically trigger a different communication strategy—whether that’s offering extra information, changing the frequency of contact, or shifting the tone of the messaging.

5 Ways that AI-Based Outreach Helps Prevent Patient Dropouts

There are several key advantages to using AI-based outreach for patient retention in clinical trials:

• Proactive Engagement
• AI allows clinical teams to proactively engage participants before they even consider dropping out. By identifying potential issues early, AI helps prevent problems before they escalate.
• Tailored Support
• Every patient is different, and so are their challenges. Whether it’s logistical support like transportation or emotional reassurance about the trial process, AI enables highly personalized outreach that addresses individual concerns.
• Scalable Solutions
• AI-powered platforms can handle patient engagement at scale. Rather than relying on manual processes, AI automates outreach for hundreds or thousands of participants, ensuring that everyone receives timely and relevant communication.
• Reduced Staff Burden
• With AI handling much of the routine communication and engagement, clinical staff are free to focus on more complex tasks that require human interaction. This leads to more efficient trial management overall.
• Real-Time Adaptability

• • AI doesn’t just offer insights after the fact—it adapts in real time. This means that outreach strategies can evolve based on patient behavior, making retention efforts more dynamic and effective.

Addressing Barriers to Enrollment and Retention with AI

For many patients, barriers to clinical trial participation are not just medical care, they’re logistical, financial, or emotional. AI can help overcome these barriers by providing tailored solutions:

• Transportation issues: If a patient is struggling to attend in-person appointments, AI-driven outreach could offer information about telehealth options or reimbursement for travel expenses.
• Financial concerns: Some patients may worry about the costs associated with participating in a trial, such as taking time off work. AI-based communication can provide reassurance and clarity about compensation or other forms of support.
• Mistrust or confusion: In some cases, patients may be unsure or skeptical about the clinical trial process. AI can automatically send educational materials or arrange for a study coordinator to answer their questions, helping to build trust and alleviate concerns.

The Future of Patient Retention in Clinical Trials with AI

As AI continues to advance, its role in preventing patient dropouts will only grow. AI-based outreach is already demonstrating its ability to revolutionize patient engagement and retention, offering personalized, real-time support that keeps participants involved in the study. BEKhealth is partnering with Areti Health for this reason, to combine Areti Health’s AI-driven patient outreach and engagement with our AI patient identification models.

In conclusion, AI-based outreach isn’t just about recruitment — it’s about creating a seamless, supportive experience for participants from start to finish. Working with our partners at Areti Health, we are building solutions to help clinical research teams find and retain patients more successfully, ultimately leading to faster, more efficient studies and better outcomes for all.