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How Does AI Impact Nursing?

Analysis  |  By G Hatfield  
   February 26, 2024

AI can be a huge disruptor, but it has a lot of potential.

AI is currently being implemented in many aspects of nursing, including documentation, admission and discharge processes, measuring and monitoring vitals, and data collection and analysis.

However, the success of AI varies, and depends largely on proper implementation.

According to Betty Jo Rocchio, Senior Vice President and Chief Nurse Executive at Mercy, a lot of thoughtful planning goes into ensuring that AI won’t become a disruptor to nurses.

“It’s not just automated intelligence, but how we augment that intelligence that the nurse brings to the bedside,” Rocchio said.

Solving problems

Ultimately, the goal of any CNO wanting to implement AI in their workforce is to solve problems and make the delivery of care more efficient and effective.

“We can never replace the care that we deliver and the critical thinking of a nurse,” Rocchio continued, “but we can help nurses be much more equipped to be able to deliver… care in a much more streamlined fashion.”

Rocchio said Mercy is partnering with Epic and Microsoft, along with other resources, to implement new processes and smaller innovations that will lead to larger future projects.

One problem that the team at Mercy is trying to solve is handoffs between departments. Typically, according to Rocchio, when a patient arrives in the emergency department and is admitted, there is typically a handoff from the emergency department nurse to the inpatient nurse.

To make this process more efficient, Mercy is exploring the use of AI to first develop a note from the emergency department record, then develop the key points in an AI automated fashion. The last step would be to deliver that note to the inpatient nurse via the nurses’ mobile phones.

“We’re trying to use AI to scour that record and deliver the most important points up to the inpatient nurse without nursing having to intervene,” Rocchio said.

AI is also assisting CNOs, not just bedside nurses.

Mercy has launched a workforce platform that allows the team to get the right clinician to the right spot without manual intervention. Rocchio said they are using AI in the background to calculate the number of necessary shifts and set the rate on incentive shifts for nurses who want extra work.

“Just like [how] Uber and Lyft use a supply-and-demand model and use data in the background,” Rocchio said, “we’re starting to use that in healthcare to be able to develop our workforce and get them in the right spots at the right time.”

AI technology can also help with hiring and recruiting processes.

“We use platforms now for hiring and recruiting that [help] candidates get to the right spot for interviews quicker,” Rocchio continued, “as well as deliver information to the candidates and collect [candidate] information… [that helps us] prioritize the areas we want to focus on.”

Challenges and concerns

As with any new technology or trend, there are challenges that come along with implementation, that CNOs should carefully consider before moving forward.

“An office is a very dangerous place to start making decisions about clinical areas from,” Rocchio stated.

The nurses themselves do have concerns about AI, but not about the use of it. The concern lies with understanding how AI will fit into their nursing practice. Nurses want to make sure that AI is going to actually be incorporated into their workflows.

“There’s no concern as long as [implementing AI] isn’t done to [nurses], but it’s done with them,” Rocchio said.

Patients, on the other hand, are very excited about AI technology. According to Rocchio, patients want information to come to them quickly and completely, and if AI can accomplish that, then they view it as a positive.

“It’s just frightening to [patients] if [information] comes in pieces,” Rocchio said, “but if it’s a part of their standard care and they can see it, they’re embracing their piece in helping us reach their healthcare goals.”


To help test new AI and mitigate some of these concerns, Mercy has launched innovation units where frontline staff can also give their input. The innovation units are there to help not only nurses, but also staff in other departments, to see where the technology could help them in their workflows.

“It’s not just AI off to the side, it’s AI embedded into the workflows and how that comes together with the frontline giving us their feedback on how it works,” Rocchio said. “We’re doing some rapid cycle improvement processes with this and making sure that we’re taking the frontline into account.”

Alongside innovation units, Mercy has put up electronic boards in every patient room that provide a connection point for information between the patient, the family, the nurse, and the physician. The boards also help speed up communication and set goals with the patient, said Rocchio.

“We’re finding [that] the power of those boards and connecting [them] into the electronic health record is helping nurses think about how they plan their day better,” Rocchio said, “and I think that’s going to be a real game changer.”

Additionally, Mercy has been using AI in the background to monitor the blood sugar of patients living with diabetes, Rocchio said. The AI tool pushes information to the patient and allows physicians and nurses to see that information as well. Clinical staff can then clearly communicate with patients in a timely manner and help them manage their blood sugar. The data can also be g used to monitor health trends for the patient. 

“If it’s buried in a medical record, somebody has to dig it out to have communications,” Rocchio said, “but when AI serves it up to the physician, the nurse, and the patient, we’re able to stay on top of it in real time.”

Measuring outcomes and success

According to Rocchio, Mercy has already seen great outcomes from the testing they’ve done in their innovation units, and in other areas of the health system. In general, the team has been able to take information and compare it with other metrics.

“We export that data into dashboards and allow our frontline nurse leaders to make good decisions around filling shifts [and] how often they need help,” Rocchio said, “in a very automated fashion, so they don’t have to manually do it.”

The same thing is true for patients, the data is aggregated, and both patients and providers are able to track, trend, and monitor patient health conditions.

Mercy has been measuring how many EHR clicks are being saved i through a mobile platform that nurses can use to chart at the bedside.

“To date, we’ve saved over 200,000 clicks in the electronic medical record,” Rocchio said, “which is important because that keeps nurses by the bedside, not spending time in documentation.”

Advice for CNOs

The implementation of AI technology can be overwhelming, so it’s important that CNOs approach it carefully and strategically.

“Get a partner that’s been working in the AI lane, like Microsoft or Google, or somebody that’s used it outside of healthcare first,” Rocchio said. “[Somebody] that understands the limitations as well as the power of it, because we’re just dipping our toe in and we want to make sure we use it in the right way.”

Rocchio recommends looking at the problems in workflows and addressing them in ways that do not involve manual intervention, but use technology or analytics to present the problem in a different way.

“It takes us leaders thinking about things differently and how to solve them,” Rocchio said, “because today the world’s moving in a while different direction.”

Click here to listen to the full interview.

G Hatfield is the nursing editor for HealthLeaders.


CNOs need to ensure they are implementing AI technology carefully into their workflows for it to succeed. 

Nurses will accept AI if they know it is being done with them, not to them. 

AI can help get real time data to the physcian, the nurse, and the patient for more efficient care. 

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