Yale New Haven Health Modernizes Legacy Radiology Infrastructure With Rad AI
The premier academic health system makes a foundational infrastructure decision to transform radiology reporting, embracing the next era of diagnostic medicine
Across YNHHS' multi-site network, which manages more than 700,000 annual radiology exams, radiologists were often challenged by administrative burdens and significant workflow friction, including fragmentation, repetitive speech corrections and manual data entry, which can slow workflows, increase administrative burden and create additional complexity for radiologists. To accelerate the pace and quality of medical imaging, the institution chose to adopt a radiologist-first AI reporting solution.
In its search for a reporting partner, YNHHS sought a more open and flexible platform capable of integrating across its existing clinical and diagnostic systems. Rad AI was selected for its ability to integrate with existing systems and improve radiologists' day-to-day experience. Rad AI helps reduce documentation burden, automate repetitive tasks and improve workflow efficiency, allowing radiologists to remain focused on patient care rather than administrative work.
"As an academic medical center, our priority is always to advance the quality of patient care. In evaluating the future of our radiology infrastructure, we realized that standard software vendors couldn't keep pace with our evolving needs; we required a true co-development partner, capable of building alongside us," said
While reporting software has been a staple in radiology, this collaboration represents a shift away from treating the report as an isolated administrative task to leveraging it as an essential tool for the entire healthcare ecosystem. By pairing Rad AI's ability to seamlessly automate the documentation process with Yale's clinical research expertise, the partnership will not only elevate report quality but also drive joint clinical research and allow for the co-development of specialized AI tools to meet YNHHS' unique needs.
"Radiologists have spent years adapting their workflows around systems that were never truly designed for the realities of modern radiology," said Doktor Gurson, co-founder and CEO of Rad AI. "As a company founded by radiologists, we understand how critical speed, accuracy and clarity are in high-volume environments, and this partnership reflects a growing recognition that reporting software must work naturally within the clinical workflow, not create more friction for the teams delivering care."
The announcement coincides with the 2026 annual meeting of the Society for Imaging Informatics in Medicine (SIIM) in
About Yale New Haven Health
Yale New Haven Health (YNHHS), the most comprehensive healthcare system in
About Rad AI
Rad AI is the leader in generative AI solutions for radiology, helping radiologists reduce documentation burden, improve workflow efficiency, and enhance patient care. Built by radiologists, Rad AI's solutions are trusted by thousands of radiologists and leading health systems across the United States. The company has been recognized by CB Insights (Digital Health 50, AI 100), CNBC's Disruptor 50, Deloitte Fast 500 and Fast Company's Most Innovative Companies.
Learn more about Rad AI at www.radai.com or on LinkedIn at www.linkedin.com/company/radai/.
Press Contact
Heather Cmiel
Vice President, Marketing and Communications
[email protected]
Alex Jenkins
120/80 MKTG for Rad AI
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SOURCE Rad AI
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