UNC Hospitals experiment with AI, work to integrate new technology in healthcare

As the use of artificial intelligence becomes more widespread, the UNC Health system has increasingly developed and utilized AI technology that researchers, professors and medical professionals alike say could change the future of healthcare.

According to UNC Health Chief Information Officer Brent Lamm, UNC Health is an early adopter and pilot site for a variety of AI technologies.

Lamm said many of the tools UNC Hospitals uses primarily focus on increasing efficiency by recording and analyzing patient interaction, better scheduling patient visits, drafting end-of-shift documentation for nurses and handling other administrative tasks. 

“We're being aggressive in our exploration of these capabilities,” Lamm said. “We're trying things and piloting and we want to do that, but we're doing it in a very safe and thoughtful way.”

Jessica Zègre-Hemsey, a nurse scientist and UNC School of Nursing professor with current research in emergency cardiac care, has been working with AI to develop strategies to supplement clinical decision-making in emergency cardiac care.

Zègre-Hemsey said working with cardiac arrest cases requires quick decision making about diagnoses and interventions. She said AI technologies help medical staff by compiling multiple data points to create predictions of outcomes for patients when they reach the hospital and even after they are discharged.

“In the large landscape of healthcare, I do think the emergency setting is one of the specific areas that AI machine learning could most benefit, because it is a unique space where we're making really fast decisions with not always a lot of information or time,” Zègre-Hemsey said. 

However, Research Director for Digital Health at the Duke-Margolis Institute for Health Policy Christina Silcox said privacy concerns, among other risks and hesitations, remain unclear because AI technology is still so new.

“It's [AI] tested with data, and a lot of our healthcare data is unrepresentative and potentially also includes systemic bias and other types of bias within the data itself,” Silcox said. 

Jeff Stringer, division director of global women’s health at the UNC School of Medicine, created a low-cost, AI-assisted ultrasound device with his team that is able to diagnose gestational age, detect twins, estimate fetal weight and identify breech presentation, all from devices like phones, laptops or iPads. 

Stringer said concerns about bias do not affect his work, because the data used to train the AI tools comes from a small, specific data set. Because these models are focused on specific diagnoses, the AI models are highly accurate. However, he said it is well-known that much more scientific research has been done on men than on women, and developers have to be careful to make sure models don’t give answers with a male bias. 

Lamm said to address some of these concerns, UNC Health has been careful not to use fully autonomous AI and have made sure that when they use AI as a tool, there is still a human in control. 

Lamm added that UNC Health has a professionally diverse governance group and operational leaders that review every AI capability the hospital is considering to ensure that it is safe and ethical. 

As the use of AI tools in healthcare has increased, so have calls for legislative oversight. 

Compared to other states, North Carolina has not done much in terms of regulating the use of AI tools in healthcare.

Stringer said he supports legislation that provides clear guidance on the safe use of AI in healthcare, as long as it is done with the right intent. He said AI should be regulated in a deliberate and responsible, but also cautious way. 

“Given the situation of an aging population and an overburdened and overworked workforce, I think that it's really important that we figure out how to do AI right,” Silcox said. “And doing AI right is not obvious, and it's not easy, but I do think it is going to be important and have enormous benefits.” 

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