After years of pilots, proof-of-concept deployments and early AI rollouts, health system technology leaders have sharpened their focus on a harder challenge: deploying the right tools at scale, with measurable outcomes and against real operational problems. The big question now is what big problem will health systems tackle next with technology?
Dwight Raum, executive vice president and chief digital information officer at Rochester Regional Health in Rochester, N.Y., sees system integration as the precondition everything else depends on. Rochester Regional spans nine hospitals, a large ambulatory network and post-acute facilities across upstate New York. Getting those components to operate as a single integrated system — one workflow across the full continuum of care — is what has to come before AI can fill the widening gap between patient demand and available supply.
“Truly getting into system integration, ensuring that we have one workflow for the appropriate functions and ensuring that we have the ability to integrate and operate as a single system, not a series of hospitals,” Mr. Raum said.
At Jefferson Health in Philadelphia, Luis Taveras, PhD, executive vice president and chief digital and information officer, is challenging a premise that has governed health IT for four decades. After his system crossed the 1 million ambient note mark nine months after launch, Dr. Taveras is now asking whether AI’s ability to generate and deploy functional code quickly enough to be useful means health systems no longer need to default to buying their technology.
“With the ability of AI today and how quickly we can write our own code and put applications in place, we have to really rethink that and say, do we now switch from a buy-first to a build-first?” Dr. Taveras said. “We have to reimagine computing in health care.”
The clinical frontier may belong to Paul Testa, MD, chief health informatics officer at NYU Langone Health in New York City. Dr. Testa has moved past the extraction and summarization use cases that defined AI’s first chapter in clinical settings and is now building toward what he calls the flow.
“As an ED doc, the magic is in the flow,” Dr. Testa said. “We’re beginning to inject models not just at the extraction point. We’re looking for the wins to be had in the flow of an ED, the flow of a hospital, the flow of a patient in the arc of their care.”
NYU Langone has deployed models in the emergency department designed to watch documentation, lab results and imaging in real time, surfacing a nudge when a pattern suggests a high-risk diagnosis may be worth revisiting.
“The opportunity to offer a nudge away from anchoring bias is incredibly powerful,” Dr. Testa said.
Other health systems are more focused on optimizing their ambient technology, which was a huge investment. Susan Goodson, senior vice president and chief digital information officer at Ann & Robert H. Lurie Children’s Hospital of Chicago, has a similar perspective. Lurie Children’s has deployed ambient documentation alongside generative AI tools for in-basket messaging, aimed at reducing the cognitive overhead that pulls clinicians away from patients.
“We are solving some boring problems so that people can focus on the more interesting aspects of their day to day,” Ms. Goodson said.
She describes AI as “a force multiplier” valuable not for its novelty but for its capacity to absorb the repetitive administrative layer that wears down clinical and operational staff.
At El Camino Health in Mountain View, Calif., CIO Deb Muro is pursuing the same goal. Her team is planning to deploy agentic AI in the call center to handle appointment scheduling, prescription refill inquiries and routine patient questions, and then redeploy the staff currently doing that work into care navigation roles.
“We’re really wanting to have humans meet with humans and really make a difference in how they’re impacted by their healthcare journey,” Ms. Muro said.
Crystal Broj, enterprise chief digital transformation officer at Medical University of South Carolina in Charleston, is tackling the friction clinicians face in their daily workflows affecting patient care. MUSC serves patients across urban and rural South Carolina, and Ms. Broj sees disconnected systems, excess handoffs and tasks that don’t require human judgment as the root cause of both staff burnout and poor patient experience.
“Healthcare is complex. It’s not getting any easier. We’ve got too many clicks, too many handoffs, too many disconnected systems,” Ms. Broj said. “Technology only succeeds when we pair it with operational redesign and then really strong governance.”
MUSC has deployed a voice AI platform — a bot named Emily — across more than 100 patient access lines, handling about 25% of incoming calls around the clock in English and Spanish without human intervention. The system has freed up the equivalent of roughly 30 full-time employees of staff capacity, redirected toward more complex patient interactions.
At Children’s Hospital Los Angeles, Omkar Kulkarni, vice president and chief innovation and transformation officer, is focused on a different constraint: capacity. The hospital sees more than 90,000 emergency visits and 750,000 total patient visits per year, and demand consistently outpaces available slots. Mr. Kulkarni is deploying AI to match patients on waitlists with open appointments in ambulatory clinics, the infusion center and the operating room faster than manual processes allow.
“The use of AI to maximize capacity so that we can take care of more kids and get them the care they need sooner and faster is a huge important project for us,” Mr. Kulkarni said.”It speaks to the huge demand there is for services in our region but also how AI can be a great enabler to make sure that we can maximize the resources we have, which are limited, in terms of taking care of these kids.”
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