For Dr. Erich Huang, Duke Health’s chief data officer for quality, one issue often overlooked when discussing AI in healthcare is the importance of the user experience.
“It’s not just an abstract Westworld brain sitting out there,” Huang says. “It has to be well integrated with clinical workflow, and nurses are essential to that.”
With the Sepsis Watch early warning program, Huang says, nurses were able to apply their professional experience to kick off the cascade of actions that would follow an AI-produced alert.
“One of the big issues with electronic health records is fatigue from alerts,” he says. “If you have a human intermediary who can serve as a first line, that’s an important component, because we can then triage things appropriately.”
Huang adds that he’d like to see more nurse-initiated thinking about automated processes that would make nurses’ jobs easier.
“I’d like to hear nursing staff identify inefficiencies they deal with, and think about the things AI and ML would be helpful in improving, allowing them to spend more time with their patients,” he says. “All clinical staff really need to be well integrated into the development or selection of these AI-based apps.”
DISCOVER: Learn how to bridge the gap between nurses and IT teams.
Including Nurses in the AI Conversation
Nurses must ensure that advanced technologies such as AI don’t cause harm or compromise the nature of human interactions and relationships that are central to their job, says Liz Stokes, director of the American Nurses Association’s Center for Ethics and Human Rights.
“Nurses must also be sensitive to unintended consequences related to the development and use of AI technologies,” Stokes says. “As with any other advanced technology in practice, nurses should ensure that the AI being used is not biased, and they must express their concerns if there is potential or actual bias that is occurring.”
Though AI can produce efficiencies in processes, such as prediction and diagnosis, Stokes says it has the potential to lower efficiency and increase stress and burnout if the cognitive demand on clinical teams is higher.
Adequate training and education for nurses is imperative, Stokes adds, and IT leaders need to involve nurses during the development and consideration of AI-related technologies. Those leaders should also collaborate with nurse informaticists, ethicists, engineers and other stakeholders when AI implementation is considered.