The Exec: How Artificial Intelligence Benefits Nurses

'AI needs to be a partner with us,' says NCSBN CEO David Benton.

Editor’s note: This article appears in the October-December 2023 edition of HealthLeaders magazine.

The AI wave comes at a crucial time in nursing because it can effectively train nursing students, improve patient care management, and adjust nurse workloads, which ultimately helps to reduce stress and burnout.

And that’s just the tip of the iceberg for the emerging technology.

HealthLeaders spoke with David Benton, RGN, PhD, FRCN, FAAN, CEO of the National Council of State Boards of Nursing (NCSBN), on what AI can do for nursing.

This transcript has been lightly edited for clarity and brevity.

HealthLeaders: What are the most useful AI innovations for nurses that you’re aware of?

David Benton: You've got to think about this in terms of different sectors. Artificial intelligence has been used within the education sector, in the clinical sector, and in the managerial space, as well, and the level of sophistication of those systems varies by sector.

Within education, what we're starting to see is artificial intelligence being used to help craft communication support and simulation systems that enable individual students to have a common experience, but it's tailored to their response. For example, patients with "various conditions" are developed that then interact with the students. The students are given a prompt and the AI is then scoring their responses, so it tailors their learning experience to their specific needs.

First of all, it's a safe space, so they can develop their skills in an environment where they're not going to do any harm, but they're going to get targeted feedback on their performance. Second, at a time when there are faculty shortages, this gives them a unique experience to their learning needs, rather than learning within a group experience on a particular topic.

In the management space, artificial intelligence can be used for scheduling, in a way to manipulate large amounts of data in very short periods of time.

We’re also starting to see it in the clinical arena as well, such as in Illinois, where it’s available to schedule cancer services as part of a clinical program. Asia is probably further down the track in developing these systems. In China, they have systems that are being used for venipuncture, so if you need to have an IV inserted, there is a system now that scans the person's arm, identifies the veins, and gets it right 90+% of the time.

David Benton, CEO, National Council of State Board of Nursing / Photo courtesy of NCSBN

HL: What are nursing pain points that AI eventually will be able to resolve?

Benton: Every two years, we do a survey of the workforce, and one of the areas that we've identified here is an increase in burnout. One of the things we need to think about is if nurses are asked to do things that technology could do more efficiently or more effectively. There's no need for nurses to be doing that kind of work when a machine can do it much more quickly, more efficiently, and in a less-stressful manner.

Taking some of that stress for these routine tasks and focusing on the things that only the nurse can do—that's what people came into nursing to do. They came into it to work with patients and to keep them safe.

HL: The technology is still new, of course, but how prevalent is AI in nursing?

Benton: It depends on the institution that you're working in, and where you are working, as well. Some countries are far more advanced, and some health systems are far more advanced than others in AI usage. Sometimes, people don't even know that they're using some of these systems because they're now embedded into the technology.

For example, some of the cardiac dysrhythmia monitoring systems that are prevalent within intensive care units, cardiac care units, emergency departments, and even in ambulances have built-in technology to support the clinician in their determination of what's going on with that individual. Some of these systems are almost under the radar in terms of the support that they're now offering.

HL: How receptive are nurse leaders to AI?

Benton: In the discussions that I'm having with nurse leaders, there's everything from enthusiasts to laggards. It depends on their own personal experience with these systems and their levels of comfort.

If they understand the technology, then they're often more receptive. There are concerns, obviously, about artificial intelligence. Artificial intelligence learns from data sets and if there are errors in those data sets, then they learn those errors or biases. That's why nursing needs to be very prominent in helping to develop these systems and to implement these systems and to detect where there are errors in the system.

In the early work on ChatGPT, when you would ask questions, it would confabulate with made-up answers and give the wrong response, and unless you knew the topic extremely well, you could be quite convinced by the response because it was very strongly asserted. The latest generation, ChatGPT-4, has started to address some of those issues and ChatGPT-5 will be getting even better still.

This is an extremely rapidly evolving space, and one of the challenges that nurse leaders have, in particular, is keeping pace with all of these developments and taking the time to familiarize themselves with what some of these technologies can do, and indeed what they can’t do, as well.

HL: Some in healthcare approach AI as "augmented intelligence," rather than "artificial intelligence," to advocate the idea of the technology assisting, rather than replacing, nurses and other healthcare staff. How important is that distinction?

Benton: At this stage, it is an important distinction because "augmented" enables the individual to retain accountability for their actions, because the ultimate decision sits with that clinician, whether they be a nurse or a doctor. Artificial intelligence infers that it’s doing it all on its own, and therefore as a device for discussing AI with the public, with politicians, etc., it’s a useful distinction at this point.

But when the machine can outperform the human consistently, then the question is, "As a human, would you overrule the machine when you know it's going to get it right 99.99% of the time, and a human gets it right only 90% of the time?" I know that I, as a patient, would want to deal with something that's going to get it right 99.99% of the time.

These are real dilemmas that society needs to be familiarized with, and not just clinicians, because that’s giving people the information they need to decide. And I have a duty as a practitioner to make sure that you are making an informed decision.

HL: What would you like to see AI do for nursing?

Benton: In the clinical space, where artificial intelligence can do as good a job or better job than a nurse, then we need to be partners with our technology, just like any other tool. If you think about years gone by when we were using mercury thermometers to take people's temperature, we didn't think anything about it; it enabled us to get an accurate value in terms of whether someone might have an infection.

Nowadays, we've got different technology that does that in real time, and we think nothing about it. AI needs to be a partner with us in terms of delivering safe, effective, and efficient healthcare into the future.