Every year at the IHI Forum, you can feel the pulse of what’s changing in healthcare. This year, that pulse was unmistakably AI. According to our very own Cheryl Pammer, who attended the event and connected with healthcare leaders across the country, AI wasn’t just a buzzword, it was the topic people were eager to talk about, question, and better understand.
But what stood out most wasn’t the novelty of AI. It was the urgency behind it.
Healthcare systems aren’t asking, “Should we adopt AI?” anymore. They’re asking, “How do we do it safely? Responsibly? And in a way that actually improves care?”
AI in healthcare today: real use cases, not theoretical promise
Walking through the poster sessions at IHI, it was clear that AI is moving beyond experimentation. Hospitals and research groups are already putting it to work.
1. Predicting and preventing clinical deterioration (Stanford Medicine)
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A pilot run by Stanford University School of Medicine detailed how a machine learning model helped clinicians identify patients at risk of rapid deterioration. But what was striking wasn’t just the model—it was the workflow redesign around it. Nurses used AI-generated alerts to structure team huddles, communicate earlier, and intervene sooner. The results?
The lesson echoed throughout the conference: AI works when paired with sound processes, collaboration, and validated insights. |
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2. Automating billing and reducing waste (Singapore General Hospital)
| Another team at Singapore General Hospital showcased how Robotic Process Automation (RPA) eliminated manual billing tasks, cutting processing time by 90%, reducing error rates, and freeing staff time—a reminder that AI isn’t only about clinical outcomes. It’s about operational excellence, too. |  |
3. Trust, verify, innovate (Vizient)
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Perhaps the most relevant poster to the broader AI conversation was Vizient, Inc's work using an internal ChatGPT instance to classify and evaluate emerging clinical technologies. Their message was clear: AI can accelerate research and decision-making if it is validated, monitored, and embedded within a trustworthy analytical framework. They emphasized the need for:
If that sounds familiar, it’s because these principles have guided Minitab’s philosophy for over 50 years. |
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The road ahead: AI with accountability
If there was a single theme across the conference, it was this: AI is powerful, but healthcare must adopt it with discipline, structure, and a commitment to patient safety.
As more hospitals explore predictive modeling, automated workflows, and AI-assisted decision support, the need for reliable analytics will only grow. The excitement around AI is real—but so is the responsibility that comes with it.
And that’s exactly why healthcare organizations are turning to partners like Minitab.
Click here to learn more about Minitab's AI capabilities.
Main takeaway? Hospitals need a partner, not just a vendorHospitals don’t just need algorithms; they need interpretability, repeatability, and quality-driven workflows. As the information at IHI showed, multidisciplinary teamwork is essential for AI success. Minitab already supports these teams across:
Our AI capabilities—housed within the Minitab Solution Center—are built to enhance this work, not replace it.
Start streamlining your healthcare operations with a true partner.
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