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How Vanderbilt University Medical Center Uses AI to Bring Joy Back to Medicine

Adoption, C-Suite, Workflow
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Healthcare is at a crossroads. Inflation pressures and labor shortages are squeezing hospital budgets everywhere, and for academic medical centers like Vanderbilt University Medical Center, sustaining their mission requires the financial strength to keep investing in infrastructure, people, and research.

Neal Patel, MD, MPH, Chief Information Officer at Vanderbilt University Medical Center, has spent nearly 30 years at the medical center watching that pressure build. As a pediatric critical care physician by training, Patel has lived through every wave of health IT hype, from the earliest clinical decision-support tools of the 2000s to the electronic health record (EHR) mandates of the meaningful use era. Now, he sees generative AI and machine learning as the next inflection point, and a chance to undo some of the damage the last wave left behind.

“A lot of clinicians are disenfranchised and feel that the burden of the computer has taken away the joy of medicine,” Patel said. “We have an opportunity to get that back into the clinical workflow and make folks excited about practicing medicine again.”

An operating system, not another vendor

The push to act came from the top. Vanderbilt’s CEO asked the health technology team to find a way to identify patients with time-sensitive, critical findings faster. That question led the team to Aidoc.

When Patel and his team first crossed paths with Aidoc, imaging AI was still in its infancy. What set the conversation apart, he said, was that Aidoc wasn’t a single-algorithm point solution.

“We didn’t want to have to deal with each individual company one by one by one,” Patel said. Aidoc’s aiOS™ offered something different: an operating system where algorithms from multiple vendors can run on a single workflow. 

From wary to “when can we get more?”

After implementing Aidoc’s AI, Vanderbilt saw results almost immediately. “We instantly saw the reduction in time to diagnoses,” Patel said. “It had a tangible impact on speed and clinician satisfaction.”

Radiologists who were initially cautious about AI entering their workflow came to see it as a trusted workflow prioritization partner. That shift changed how Vanderbilt approaches adoption altogether. Traditional change management, Patel noted, used to mean one-on-one conversations to convince clinicians that a certain tool was worth their time. Not anymore. “It’s amazing how fast it spreads. As soon as something just works, everybody wants to be a part of it.”

Today, clinicians are asking for more AI solutions. “Our clinicians are truly ready and constantly at my door saying, when can we get more?”

Bringing the magic back

For Patel, the real story is about what happens when technology finally starts working the way people expect it to.

“The magic of it is back,” he said. “Instead of just being something that you have to enter data into — relegated to the duties of a clerk — you’re now back in where this is truly an aid to you.” He points to the everyday tools people rely on outside the hospital, like GPS, as the standard clinicians now expect at work. “Health technology just hasn’t kept pace with the same way as consumer technology has. The latest tools that have come out kind of bring that magic back to the bedside.”

That shift shows up in the anecdotes clinicians share with him directly. “I’ve heard feedback like, ‘This is life-changing,’ ‘I feel that the tools are helping me deliver faster care and better care.’”

Personal, not transactional

Patel is candid that this work has never been abstract for him. Having spent his career in pediatric critical care — where timing can mean everything and overnight support is thin — he approaches every deployment with the same question: would this be good enough for his own family? “All of my family uses our medical center for their care, and we know that all of our peers use this medical center for their care,” he said. “We want to deliver the same care for the patients in front of us as if it was our family member in that bed.”

That philosophy extends to how he thinks about vendor relationships. “A relationship with any vendor that a CIO has must be a partnership. It can’t be client-customer, because that sort of transactional relationship always potentially has the concept of a winner and a loser.”

What’s next

Looking ahead, Patel’s vision goes beyond flagging suspected critical findings. He sees the next frontier as what he calls Vanderbilt system intelligence: making sure the right insight, whether from imaging, the EHR or physiologic data, reaches the right person inside their existing workflow, every time, without requiring anyone to remember an extra step.

His broader hope for the field is one of humility. “If we do our job well, the technology should recede into the background and almost become invisible, so that the focal point goes right back to the patient and the care delivery team doing their best work.”

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