5 Ways AI Can Transform Nursing Education
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- Although relevant AI technologies have existed in some form for years, they often go underutilized in nursing education due in large part to a lack of educators or confidence.
- To help nursing education keep pace with AI expansion, experts suggest that curriculum change is needed.
- AI-assisted simulators are one key way to enhance student learning and nurse-patient communication.
Artificial intelligence (AI) is making its way through the worlds of higher education and healthcare, causing stakeholders to rapidly adjust to powerful but potentially disruptive tools like ChatGPT.
Nursing education sits at the nexus of these two worlds — and some experts say the field isn't doing enough to keep pace with rapidly expanding AI technology, both in the classroom and at patients' bedsides.
A 2017 survey of nurses found that a lack of resource uptake may be limiting the number of nurses with the appropriate knowledge, skills, and confidence to teach AI and digital health concepts.
"Transformation of nursing curricula will be necessary to ensure future nurses are equipped with informatics competencies, as well as competencies in digital and data literacy to work in clinical settings that increasingly use AI and ML (machine learning) technology," according to a 2023 JMIR Nursing report, which cited the survey in its findings.
The report called for strong nursing leadership to incentivize educators to adopt new pedagogies to prepare nurses and nursing students to use these emerging technologies.
For nursing school leaders grappling with the challenges of bringing faculty and learners up to speed on AI, there is good news: a rich ecosystem of AI tools, from those that analyze student emotion to hyper-advanced AI robot patient simulators.
Here are five AI-assisted solutions with the power to transform nursing education and equip tomorrow's nurses for cutting-edge clinical care.
5 Ways AI Can Transform Nursing School
According to experts, simulations allow students to practice real-world scenarios in a real-world environment. As AI advances, the line between reality and simulation is increasingly blurred — and that can be a good thing for nursing education.
For example, Winston-Salem State University (WSSU) recently implemented virtual reality clinical simulations that help to enhance clinical judgment and increase knowledge retention through immersive patient interactions and the replication of hospital procedures.
"The students, when they put on the headset, it's like they're really in the hospital, and they're able to provide care as if they are in the hospital," Leslee Battle, professor and dean of the School of Health Sciences at WSSU, previously told BestColleges.
Educators can observe students' critical thinking as they practice communication and bedside manner with patients through decisions that have consequences.
On Nov. 14, Emory University's nursing school introduced an AI "patient" named HAL S5301, which engages in conversational speech and simulates physiological symptoms. The bot, created by Gaumard Scientific Co., can mimic stroke symptoms and create emergency, trauma, intensive care unit, and medical-surgical care scenarios.
According to the JMIR Nursing report, a new specialty could help bridge the overall gap between AI understanding and nursing: the "nurse-engineer."
"Undergraduate nursing programs that combine nursing principles with engineering principles can advance the development of AIHTs (AI health technologies) and help nurses understand the principles behind the AIHTs that they will likely encounter in clinical settings," the report stated.
Involving nurses in all stages of AI tools will alleviate the risk of creating unintentionally burdensome or otherwise problematic technology for health professionals, according to the report. However, it says, this duty falls upon nursing leadership to equip students in primary nursing education.
AI may also bring some volatility to students' personal information.
Jennie C. De Gagne of Duke University's nursing school wrote in an editorial that, since AI requires access to confidential information, it's essential to safeguard student information from potential data breaches.
"Nursing curricula should discuss ethical concerns such as data breaches, the potential for bias in the data used to develop algorithms, and the importance of social justice and person-centered approaches in the design of AIHTs," JMIR Nursing report authors wrote.
HAL represents the future of simulation — increased price tag and all — for higher-fidelity simulations.
Another of De Gagne's concerns is the high cost of implementing software, hardware, and staff training, which could require reallocation from existing budgets or increased external support.
HAL is no exception. According to school officials, HAL's price tag checks in at more than $160,000.
However, AI in healthcare is eventually expected to save money overall, particularly in administrative work.
According to a 2023 study titled "The Potential Impact of Artificial Intelligence on Healthcare Spending," AI could cut physician costs by $20 billion-$60 billion (based on 2019 numbers).
The spending costs are saved by implementing AI into administrative tasks, taking the administrative load off clinical workers.
De Gagne believes AI automation in grading, monitoring, and student progress tracking could also create a space for educators to focus primarily on complex teaching tasks.
Facial recognition software is widely known and utilized in a number of professional fields, from law enforcement to farming. Study evidence showed it has the power to transform nursing education, too.
The JMIR Nursing report cited a 2019 study where researchers used facial recognition software to assess nursing students' emotions throughout a simulation where a patient had ascites and respiratory distress syndrome followed by vomiting.
The researchers analyzed student emotions during clinical learning through emotion recognition and facial expression classification.
Ultimately, the study's authors wrote, this sort of technology could help determine which areas students have mastered and where they struggled, then tailor subsequent learning activities accordingly.
The JMIR Nursing report cited a 2015 study where students wore a "Myo" armband to measure student handwashing techniques.
"Myo's sensors are designed in order to recognize the activity of the forearm, palm and fingers. Using signal processing and machine learning, the quality of the hand washing process can be estimated and used as evaluation in medical teaching," study authors wrote.
Authors referenced a 2018 study stating that "the transformation of curricula and professional practice focusing on interpersonal and intrapersonal intelligence with attitudes that value human skills will ensure nursing's place/role in a society dominated by machines and scientific progress."