AI System Boosts Rare Disease Trial Enrollment Efficiency and Diversity

Cleveland Clinic and Dyania Health study shows AI-powered medical chart review can identify more eligible patients, including underrepresented groups, for rare disease clinical trials.

Published on Mar. 4, 2026

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A new study published in The Journal of Cardiac Failure demonstrates how a medically trained AI system developed by Cleveland Clinic and Dyania Health can accurately and efficiently screen electronic medical records to identify patients eligible for a rare disease clinical trial. The AI system reviewed 1,476 patient records in one week, identifying 46 potential matches - 29 of whom had not been found through traditional recruitment methods. The AI achieved 96.2% accuracy on trial-specific questions and a 99% negative predictive value, while also surfacing a more diverse patient population compared to standard screening.

Why it matters

Clinical trials often struggle with slow enrollment and lack of diversity among participants. This study shows how AI-powered medical chart review can help address these challenges by rapidly identifying high-quality trial candidates across a large health system, including patients from underrepresented backgrounds who may have otherwise been missed through traditional recruitment methods. Improving the efficiency and equity of trial enrollment has the potential to accelerate the development of new treatments for rare diseases.

The details

The AI system used a combination of structured EMR data and natural language processing to analyze complex clinical notes and lab reports, providing detailed justifications for each inclusion or exclusion decision. It correctly identified 29 out of 30 eligible patients that had not been found through standard screening, and accurately excluded 198 out of 200 non-eligible patients. Importantly, the AI-driven process resulted in a more diverse patient population, with 36.6% of the 30 AI-identified patients being Black, compared to just 7.1% identified through routine screening.

  • The study was published on March 3, 2026.
  • In one week, the AI system reviewed 1,476 patient records.

The players

Cleveland Clinic

A nonprofit multispecialty academic medical center that integrates clinical and hospital care with research and education. Cleveland Clinic has pioneered many medical advances and is consistently recognized for its expertise and care.

Dyania Health

A company transforming healthcare by deploying cutting-edge, medically specialized AI to automate electronic medical record review, enabling more efficient clinical research, reporting, and quality, while empowering clinicians to optimize patient care.

Trejeeve Martyn, M.D.

The lead study investigator and director of Heart Failure Population Health at Cleveland Clinic.

Eirini Schlosser

The CEO and Co-founder of Dyania Health.

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What they’re saying

“This study shows how medically trained AI can support chart review at scale, transforming what has traditionally been a labor-intensive process. By rapidly identifying high-quality trial candidates across a large health system, we can increase enrollment efficiency and increase enrollment of patients from different backgrounds and from a broader geographical area. We are optimistic that this technology can be used across our health system and are looking at how the platform can help accelerate observational research, disease registries and evidence-based implementations of approved therapies that are underutilized.”

— Trejeeve Martyn, M.D., Lead study investigator and director of Heart Failure Population Health at Cleveland Clinic (The Journal of Cardiac Failure)

“Clinical research is often limited by how efficiently and equitably we can match patients to trials. This study provides compelling evidence that AI can help solve that bottleneck – not just by improving workflow efficiency, but by helping surface eligible patients who may otherwise be missed, especially those from historically underrepresented groups.”

— Eirini Schlosser, CEO and Co-founder of Dyania Health (The Journal of Cardiac Failure)

What’s next

Cleveland Clinic has invested in Dyania and may benefit financially from the sale of this technology. The real-world implementation of AI in a live clinical trial setting and the performance metrics and diversity findings suggest an opportunity to expand AI-enabled tools more broadly for clinical trial matching, population health registries and real-time quality reporting.

The takeaway

This study demonstrates how AI-powered medical chart review can improve the speed, accuracy and equity of clinical trial enrollment, particularly for rare diseases. By rapidly identifying eligible patients, including those from underrepresented backgrounds, this technology has the potential to accelerate the development of new treatments and expand access to clinical research.