Leveraging customized AI agent solutions to personalize patient engagement and improve retention rates in clinical trials within healthcare systems

Artificial intelligence agents are computer programs that work on their own to do certain jobs by talking with users and using data sources. Unlike simple chatbots, AI agents in clinical trials can do many tasks. They can answer patient questions, schedule visits, remind patients to take medicine, and help guide them through trial steps in real time.

One important improvement is the use of customized AI agent platforms that match the special work routines of healthcare providers. These tools are different from basic AI because they include clinical knowledge and specific processes of the organization. For example, Accenture’s AI Refinery™ for Industry offers clinical trial companion tools that aim to make trials more successful by lowering dropout rates through personal help.

The Challenge of Patient Retention in the U.S. Clinical Trials

Keeping patients in clinical trials is very important for getting good data and successful results. The U.S. healthcare system runs thousands of trials every year with many different types of patients. Even with strong procedures, about 30% of patients leave the trials early. This hurts the trust in the results and makes studies take longer.

Many reasons cause patients to quit: trial steps can be hard, communication may not be clear, it can be hard to get to appointments, and patients may not get enough support. Usual ways to handle these problems, like phone calls and paper reminders, often don’t work well for each patient’s needs.

How Customized AI Agents Improve Patient Engagement and Retention

AI agents built into clinical trial processes help solve many of these problems. They allow personal communication with patients, send reminders on time, answer questions fast, and handle concerns right away. Unlike humans, AI agents work all day and night. They give consistent answers and can manage many questions at once without waiting.

The AI trial companion agents from platforms like Accenture’s AI Refinery use patient data and trial rules to customize messages. This way, messages fit each patient’s needs, respect their time, and use their favorite ways to communicate. Because of this, patients feel more involved, which can keep them in the trial longer.

According to Accenture’s AI Refinery, clinical trial agents help:

• Make trial plans personalized for each patient.
• Give real-time support to patients and clinicians.
• Answer common questions accurately and quickly.
• Explain complex trial steps in simple words.
• Lower patient dropout rates.

These AI agents collect information from clinical systems and outside sources. They quickly combine this information to make patient-focused conversations.

Impact and Evidence: AI Agents in Real-World Clinical Settings

In the U.S., big healthcare providers and research centers have started testing and using AI agent solutions. Early users in clinical trials have seen clear improvements in patient involvement and lower costs for managing patients. For example, AI companions reduce the work for clinical staff by automating patient messages and follow-ups.

Also, Accenture works with NVIDIA, which offers AI tools like NeMo and NIM microservices. This partnership helps healthcare groups set up AI agents much faster, reducing setup time from months to just days. Fast setup is very important to quickly improve trial processes, especially in urgent areas like cancer and chronic diseases.

By giving clinical teams these custom AI agents, U.S. healthcare systems get more efficient trials and better patient experiences. AI agents watch if patients take medicine and keep appointments, offer encouragement that fits them, and alert human staff if problems happen. This keeps patients active in the trials.

AI and Workflow Automation: Enhancing Clinical Trial Operations

Workflow automation is a key part of adding AI agents to healthcare. AI agents can connect with Electronic Health Records (EHRs), Clinical Trial Management Systems (CTMS), and communication tools. This helps run operations smoothly.

For clinic managers and IT staff, custom AI agents can automate tasks like:

• Scheduling appointments and sending reminders.
• Collecting patient-reported results.
• Entering and verifying data.
• Handling questions and support in real time.
• Watching for risks and warning about possible dropouts.

This automation means fewer missed visits, more accurate data, and less manual work for staff. Trials can stay on schedule, which is important to meet rules and keep funding.

Accenture’s AI Refinery platform links AI agents with public and private cloud systems. It offers flexible options for each healthcare facility’s IT setup. These AI agents act like digital team members who work with clinical staff and manage repetitive, important tasks alone.

Benefits for Medical Practice Administrators and IT Managers

Medical practice administrators in the U.S. have to balance patient care, resources, and costs. Adding AI patient-engagement agents to clinical trials fits well with these goals by:

• Improving patient satisfaction through personal follow-ups.
• Lowering trial-related administrative costs.
• Boosting data accuracy with automated collection.
• Reducing dropout rates, which makes trials stronger and faster.
• Allowing staff to work on harder issues and patient care instead of routine messages.

IT managers also benefit because these AI solutions work with existing systems and do not need big changes in infrastructure. The AI Refinery platform uses NVIDIA AI Enterprise technology to support scalable AI agents that can operate on many cloud services. This flexibility helps meet organizational IT rules and security needs, which is very important when handling sensitive patient data.

Future Directions and Expectations for AI in Clinical Trial Management

Accenture wants to grow its AI agent collection to over 100 special agents by the end of 2025. This means more tools will be available to help different health care jobs, including life sciences and clinical research. The goal is to give healthcare providers in the U.S. AI tools that fit specific clinical work and organization goals.

New AI companions for clinical trials might include:

• Better patient education modules.
• Predictive tools to find patients at risk of leaving.
• Support for many languages to help diverse U.S. groups.
• Connection with wearable devices to gather real-time health data during trials.

Healthcare systems with flexible AI agents will be able to improve patient participation and keep them engaged, while also following clinical rules.

Summary

AI agent solutions designed for healthcare workflows help clinical trials in the U.S. Platforms like Accenture’s AI Refinery use AI technology, including NVIDIA software, to quickly create flexible agents that support patients well. These AI agents guide trial participants with personalized steps, answer questions in real time, and manage routine administrative tasks.

With these tools, healthcare providers can lower patient dropout rates, make trials more efficient, and improve data quality. At the same time, they reduce the workload for clinical staff. For U.S. medical practice administrators, clinic managers, and IT teams, using AI automation tools is a step toward improving clinical trial management and healthcare research.

This AI approach offers a practical way for U.S. healthcare systems to improve patient involvement and clinical trial success. This is important for creating new treatments and running research programs well and efficiently.