Cleveland Clinic and health technology company Dyania Health have won a 2026 Gartner Eye on Innovation Award for their work using artificial intelligence to speed up how quickly eligible patients are identified for clinical trials, with study teams reporting enrollment rates roughly 40% faster and patient volumes up about 47% after the underlying Synapsis AI platform rolled out enterprise-wide in November 2025.
What the Tool Actually Does
Synapsis AI scans electronic health records across Cleveland Clinic’s system, matching patients against the detailed, often highly specific eligibility criteria required for active clinical trials — a task that previously required research coordinators to manually review charts one at a time, a process that could take hours per trial and often missed eligible patients buried in unstructured physician notes rather than structured data fields. By automating the initial screening step, the system lets human coordinators focus their time on outreach and enrollment rather than search.
Why the Award Matters Beyond the Headline Numbers
Gartner’s Eye on Innovation recognition carries weight in the health IT industry specifically because it requires demonstrated, measurable outcomes rather than rewarding promising pilot programs or early-stage proof-of-concepts. Cleveland Clinic’s scale — one of the largest academic medical centers in the United States, running a large and diverse portfolio of clinical trials across specialties — gives the results more credibility as a signal of how the technology performs at genuine enterprise scale, not just in a controlled pilot unit.
The Broader Trend This Fits Into
Cleveland Clinic’s results arrive alongside similar claims from other major health systems: Ochsner Health reported a 41% increase in clinical trial screening capacity and roughly 75% less manual screening workload after deploying a comparable AI system, while Oracle Health and AstraZeneca separately announced a partnership in October to explore AI-driven recruitment across multiple disease areas. Taken together, these announcements suggest 2026 has become the year AI-assisted trial matching moved from experimental pilot to a genuinely scaled, if still unevenly validated, clinical research tool.
The Caveats Worth Noting
The specific efficiency figures cited by Cleveland Clinic and Dyania Health come from the companies’ own announcements rather than independent, peer-reviewed research, meaning outside researchers have not yet validated the methodology behind the 40% and 47% figures or ruled out factors like concurrent staffing changes or trial-mix shifts that could partly explain the improvement. Independent validation typically lags vendor announcements by a year or more in health IT, given the time needed to design and publish rigorous comparative studies.
The Patient Privacy Question
Systems that scan comprehensive patient records to identify trial candidates also raise data privacy and consent questions that health systems have had to navigate carefully, ensuring that AI-driven pre-screening doesn’t run afoul of patient consent frameworks designed around human-initiated record review, even though the ultimate contact and enrollment decision remains with human coordinators and the patients themselves.
What’s Next
Dyania Health and Cleveland Clinic are expected to expand the Synapsis AI deployment to additional trial types and disease areas following the award recognition, while the broader industry will be watching for independent academic studies validating whether AI-assisted trial matching genuinely improves enrollment speed and diversity, or whether current results reflect selection effects specific to early-adopter institutions.
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