What if better care begins in a different reality?
A student nurse knows the checklist. Ask about pain. Medication. Allergies. History.
But the first time it matters, it won’t feel like a checklist. It will feel like a conversation that doesn’t go to plan, with a patient who is anxious, frustrated, or certain they already know what is wrong.
That clash with reality comes quickly, and it’s often decisive.
Estimates suggest up to a third of nurses leave within their first two years in practice, often when training meets reality.
In a different kind of reality, that moment can be rehearsed.
With augmented reality tools, a nurse can miss a question, start again, and ask it better. They can practice administering fluids or collecting blood samples. They can do this with patients that respond like real people.
If that rehearsal makes the first days on the ward feel less abrupt, it points to something bigger.
The next generation of tools built for nurses could support them not only in training, but throughout their careers.
Bridging the gap before practice
Tim Morris, a former emergency department charge nurse who now leads Elsevier’s nursing portfolio understands the gap between training and practice.
“What technology can help us do,” he says, “is to bridge that gap safely.”
That matters because nursing is getting more demanding.
Nurses under pressure
61% see more patients than a year ago
43% say keeping up with medical advances is challenging
34% say tiredness or exhaustion has affected their ability to treat patients effectively
Even under that pressure, 71% of nurses say they still have enough time with patients to give good care.
That consistency is a sign of how much nurses are carrying. They deserve support that matches that effort.
Even under that pressure, 71% of nurses say they still have enough time with patients to give good care.
That consistency is a sign of how much nurses are carrying. They deserve support that matches that effort.
A safer place to practice
That support can start before a nurse ever reaches the ward.
The same way a student can try a conversation again, they can now examine a heart, place a line, or work through a procedure — and do it again until it feels natural.
Complete HeartX, Elsevier’s pilot XR product, was built to explore that potential. It lets learners study cardiac anatomy and practice core clinical steps such as venipuncture and auscultation in an environment that is interactive, repeatable, and visually precise.
Irene Walsh, who works on immersive learning at Elsevier, says the response has shown “such a hunger in the market for tools that are really well crafted and thoughtful.”
Pairing traditional 2D anatomy imagery with a detailed 3D heart model adds “another dimension that helps cognitive recall,” Walsh says. In a university study, she saw a “light bulb moment” — when spatial understanding became usable.
These tools let students repeat, correct, and build confidence before they meet the same pressures in real care.
Nursing needs tools built for nursing
In practice, there’s no chance to start again, so the support nurses rely on in that moment matters even more.
Nurses are already using AI, but often in ways that weren’t designed with their work in mind. Elsevier’s Clinician of the Future: Nurses Edition suggests they are not yet getting the level of support they deserve, with 41% saying their views are never or rarely adequately represented in organisational decision-making.
Use of AI Among Nurses and Doctors
Percentage of those who use AI for work
41% of nurses
57% of doctors
Among those who use AI, the percentage of those who use a clinical-specific tool
30% of nurses
37% of doctors
Say nurses’ views are never or rarely adequately represented in decision-making
Craig Lindsey, a nurse and informatics leader who now teaches AI in healthcare, has seen why.
“It’s different depending on the clinical specialty,” he says. Tools designed for physicians do not automatically fit nursing workflows.
Where he sees promise is in areas that absorb time and attention: education, documentation, handover, and follow-up after discharge so fewer patients fall through the cracks.
Trust starts with what sits underneath
For Morris, the problem with generic AI is practical.
“It might give me a good answer, but is it accurate?” he asks. And if a nurse still has to stop and validate that answer, “that just moves the pressure to a different place.”
That is why the underlying content matters. Lindsey puts it plainly: “The content is what drives the success there.” If a system is built on “really clean data,” he says, it creates “a heightened sense of reliability.”
Nurses describe that trust in practical terms.
What would improve nurses’ trust in AI
65% say tools must be easy to use
62% want comprehensive answers drawn from multiple sources
61% want transparency with citations
Answers alone are not enough. Nurses need answers they can trust.
This is only the beginning
Rather than referring to artificial intelligence, Lindsey prefers the phrase “augmented intelligence.” The nurse remains the caregiver. The tool helps them notice more, document more easily, and focus attention where it matters most.
That is also how nurses themselves see the future.
How nurses see AI
80% say AI will not replace clinicians but become a critical assistant
78% say skill with AI tools will be an essential part of training
42% currently say they trust AI tools
Used well, Lindsey hopes, these tools can “relieve cognitive burden,” reduce moral injury, and even “return joy to practice.”
The different reality, then, is not separate from care.
It is one way of getting closer to it — by giving nurses more room to learn, more confidence before practice, and better support once practice begins.