Yale New Haven Health Deploys Rad AI Radiology Tools Across Multi-Site Network
Yale New Haven Health System will roll out California-based Rad AI's generative AI radiology tools across its network, which spans more than 16 outpatient imaging centers and five hospital campuses. The health system will also co-develop new radiology technologies with the company for clinical testing.
Rad AI's software automates portions of radiology reporting, reducing dictation time and helping radiologists generate impressions faster. The company's Omni Impressions tool generates AI-enabled report impressions after a radiologist dictates findings.
Dr. Melissa Davis, vice chair for imaging informatics and radiology at Yale New Haven, said the impression generator addresses a core pain point for radiologists. "If you ask a radiologist broadly, 'What's made my day better?' An impression generator is what it is," Davis said.
Beyond Implementation: Co-Development Focus
Yale New Haven's partnership with Rad AI extends beyond deploying existing products. The health system wants to work with the company to build technologies tailored to its specific operational challenges.
Data management ranks high on the health system's list of needs. Davis cited questions the organization struggles to answer: How many radiologists should staff a given shift? Which services need staffing adjustments at particular times? How can the health system predict demand to give radiologists scheduling flexibility?
"We have a lot of information, and we don't know how to surface the questions that we actually need answered," Davis said.
Dr. Elizabeth Bergey, radiologist and chief clinical officer at Rad AI, said the company has the technical foundation to tackle such problems. "We are known for making a personalized model for impressions, and that kind of base skill set is what we have, which is building custom models for radiology-specific tasks," Bergey said.
Why Yale New Haven Matters to Rad AI
Yale New Haven was Rad AI's first major academic health system partner. Bergey described the relationship as one where both organizations have built trust and worked closely to shape Rad AI's product direction.
The expanded partnership reflects how health systems now view AI vendors - not just as software suppliers, but as development partners who can help solve operational problems unique to their organizations.
Learn more about Generative AI and LLM applications in healthcare, or explore AI for Healthcare more broadly.
Your membership also unlocks:
