"I've always said that I can teach a nurse a skill, but I can't teach what sick sounds like on the phone. That's lived experience, that's learned experience, and that's what the clinician brings. And I think those are the things that we need to focus on and make sure that people have the time and the bandwidth to really engage,"
"We're upstream of it - we're not reacting in an emergency. We're proactively intervening when we see that the clinical condition may be changing, and that's being driven by AI algorithms,"
AI will not replace clinicians' lived judgment but can relieve administrative burden by automating routine tasks, enabling clinicians to spend more time on direct patient care. Rising care demand and a shrinking clinical workforce increase the need for scalable AI-driven task automation. A critical bottleneck is the shortage of faculty to train nurses despite ample program applications. Investment in AI includes both in-house development and vendor products. In-house models monitor Epic patient data to flag early deterioration and enable proactive intervention. Additional internal tools analyze data to identify patients at risk for sepsis, supporting earlier response and improved outcomes.
Read at MedCity News
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