How AI Can Transform Nursing Practice

AI is all the rage. Ever since ChatGPT started helping the general public generate written answers to just about any question, its current and potential applications have exploded. Nursing schools already use the chatbot to create mock simulations that resemble real-life nurse/patient interactions.

Electronic medical records (EMRs) are already ubiquitous in healthcare, with 96% of general acute care hospitals and 88% of office-based clinics using the tool, many of which have some form of AI capability.

Tiffany Kelley, Ph.D., is the Frederick A. DeLuca Foundation Visiting Professor for Innovations and New Knowledge in Nursing and director of the Healthcare Innovation Certificate Program at the University of Connecticut School of Nursing. She is also the founder and CEO of two healthcare technology companies. With nearly 20 years of nursing informatics and health IT experience, she believes digitizing patient health data opens the door for innovations in healthcare.

“It can create advanced health insights using AI tools that were not possible in the paper-based world,” Kelley points out.

For example, AI tools can help determine your risk for specific health conditions or larger-scale population risks following a major event like a disease outbreak. AI tools will only get more sophisticated and are predicted to transform nursing practice, Kelley says.

However, confusion abounds over how and when to use AI and its use in patient care. Indeed, not all AI is welcomed by the nursing community. There can be a huge learning curve, especially for nurse educators, and some nurses may resist trying new technologies.

Learn more about AI’s role in healthcare, nursing fears around it, and the future of AI in nursing.

AI is defined as technology that can allow a computer system or computer-controlled robot to learn, reason, perceive, infer, communicate, and make decisions like humans or better than humans.

“AI technologies depend on data, information, knowledge, the building blocks of informatics, to ensure the algorithms are providing reliable and accurate insights,” Kelley says.

There are also AI tool subsets that support AI technologies, including:

These AI subsets can improve patient care by analyzing large amounts of data to improve decision-making among healthcare providers.

As one recent example, Google’s cloud business recently partnered with the Mayo Clinic in Minnesota to create new AI patient care solutions. The collaboration allows Mayo Clinic to use an app known as Gen App Builder to more quickly identify patient information typically found in different formats and locations. This app can save time for clinicians and researchers, make predictions about a patient’s health, and help prevent or slow the course of health conditions.

Chatboxes and social robots also are growing in popularity in healthcare. Not only are they being used to accompany nurses in practice, but they also are helping the general public, especially the older population. Chatboxes and social robots simulate human conversations and provide companionship for older individuals in long-term care facilities.

Specifically in nursing, AI can play a huge role in helping nursing students and nurses make better clinical decisions about their patients.

“Answering questions to support the patient’s specific questions about a condition, dressing change, or medication, to name a few, could be a supportive AI tool, especially in the inpatient setting,” Kelley says.

AI and technology are beginning to change the role of nursing significantly. In 2022, nurse executives across the U.S. participated in a panel on artificial intelligence and the future of nursing.

Two recent use cases have made waves as potential boons to nursing practice:

KATE and the Rothman Index are clinical decision support systems or tools nurses and other providers use to get real-time clinical information on patients. KATE’s AI capabilities can help emergency room nurses triage patients efficiently, getting the higher-risk patients to the right care quickly.

Two other examples of AI tools currently being used, Kelley points out, are supporting the detection of patients at risk for falls and readmission.

“I fully expect the use of AI to significantly grow as we come to further understand its capabilities and identify where AI tools can be effective in supporting the delivery of quality nursing and healthcare,” Kelley says.

Technological advantages in nursing are designed to support the needs of nurses. But there is still fear surrounding the use of AI in healthcare, specifically in nursing.

“With any prospective new technology, there is often a tendency to resist because it means changing the status quo,” Kelley says.

Nursing educators have expressed concerns about the potential impact of AI on their workload and their roles as teachers.

Another potential disadvantage of AI is that technologies are being developed quickly. This risks us needing to fully understand the potential benefits and unintended consequences of these tools, Kelley points out.

“Additionally, we will need internal policies and likely regulations to effectively use such tools for the delivery of quality care,” Kelley says.

Fears like breaches in HIPPAA and computer security are real risks. Having consumer health AI tools that are as reliable and accurate as those that get adopted within healthcare settings are equally important with the rise of AIHTs, Kelley says.

Robust training and guidance should help ease the fear of AI.

AI technology can give new insights to help form better care decisions. Kelley believes some of the movement toward AI requires nursing as a profession to be willing to look toward what could be possible instead of a focus on how it will change.

Kelley believes we need nurses, especially informatics nurses and nursing leaders, to not only conceptualize AI’s use in nursing and healthcare delivery but also identify appropriate and effective use cases that support nursing and patient workflows.

The potential for any AI tool and integration into nursing is limitless but will require critical evaluation. It will also take time to become fully comfortable with AIHTs becoming fully blended into nursing programs.

But, it is essential to point out that AIHTs can improve clinical decision-making and influence the traditional nurse-patient relationship by enhancing the teaching and learning process.

“We must ensure and emphasize that these AI tools are intended to support or assist and not replace the critical thinking of our nurses,” Kelley says.