The N.U.R.S.E.S. framework was introduced by Stephanie H. Hoelscher and Ashley Pugh in an article published in the Nursing Outlook journal (Volume 73, Issue 4, July–August 2025). It explains six important parts for nurses to use AI well in clinical work:
Each part helps nurses learn to use AI the right way. The goal is to make sure AI helps patients, not makes care harder. People who run medical offices and IT teams should know this framework to give nurses the right tools, training, and rules.
Nurses need to understand the basic ideas behind AI before using the tools. AI in healthcare often uses complex computer processes to look at patient information, help with diagnosis, and aid care choices. Knowing how AI collects, handles, and understands data helps nurses feel more comfortable using AI systems.
Hospital leaders should provide training programs that make AI clearer to nurses. This is important for AI tools in electronic health records (EHR) and decision support systems. Nurses must understand what AI can and cannot do to avoid mistakes or relying too much on it.
AI should help nurses be more efficient and accurate, but not replace their judgment. AI systems can give useful information that helps nurses make better choices, predict changes in patients, and make care plans suited to each patient.
Services like Simbo AI offer front-office automation that helps nurses and office staff with routine communication tasks. Automated phone answering makes call wait times shorter and ensures patients get quick replies, so nurses can spend more time with patients.
Medical office leaders who want to add AI should pick tools that match their goals, like improving patient satisfaction or making workflow better. They should test AI tools in a small setting first, get feedback from nurses, and adjust before using widely.
AI can improve nursing work and results, but it has risks. One major risk is bias in data and errors in algorithms. AI depends on the data it learns from, and if that data has social, racial, or economic bias, AI may continue those unfair biases.
The American Nurses Association (ANA) warns nurses to watch out for these problems. Nurses should carefully check AI recommendations to make sure patient care is good and not harmed by wrong AI advice. AI makers must be open and regulated to lower risks.
IT managers should set up systems to find AI mistakes or bias fast. Nurses working with information technology should help review AI tools regularly. Nurses also need training to question AI advice and to know its limits. This prevents relying too much on AI.
AI changes fast. Nurses need ongoing education and skill-building to keep up. Hoelscher and Pugh suggest teaching AI literacy in nursing school and on the job to fix knowledge gaps.
Healthcare groups should create continued AI training courses and workshops for nurses. Classes should include updates on new AI tools, ethical issues, and hands-on practice with AI systems used in clinics.
Administrators should plan budgets for regular education and work with nursing schools and tech companies to build learning plans. IT staff can help by offering easy-to-use AI tools and technical support to nursing teams.
Ethics is key when using AI in nursing. The ANA says AI should support caring, trust, and human contact—not replace these values.
Nurses stay responsible for clinical decisions even when AI helps. They must make sure AI does not break patient privacy, fairness, or transparency. AI tools should not treat minority patients unfairly or cause health gaps.
Healthcare leaders must make policies that include fairness and privacy rules for AI use. They should train nurses to spot ethical problems with AI and involve nurses in making AI rules and decisions.
Nurses have a role beyond just using AI tools. They should help guide AI development and rules. Their experience with patients and workflow gives helpful views on how AI works in real life.
Healthcare groups should invite nurses to join teams that study, regulate, and deploy AI. This helps AI tools fit real clinical needs and handles ethical issues before broad use.
In U.S. healthcare systems, which are quickly using digital tools, nurses leading AI governance can help connect new technology with good patient care.
One important area where AI can help nursing and healthcare management is front-office automation. Companies like Simbo AI show how AI systems for phone answering and call handling can improve how medical offices work.
Front desks get many calls for appointments, prescriptions, and questions. High call volume can stress staff and slow patient contact. Using AI phone automation lets these regular calls be handled quickly and correctly. This cuts wait times and frees staff to handle harder tasks.
For medical administrators, using Simbo AI can save costs and make resource use better. Automated phone systems work all day and night, so no calls are missed. This helps keep patient access and satisfaction higher.
IT teams must link these AI systems well with electronic health records and practice software. Keeping data safe, making sure AI works well, and training users are important to get full benefits.
This AI workflow automation indirectly supports nursing by making clinic operations smoother. Nurses face fewer distractions from admin work and can focus more on patients. Also, faster and accurate communication helps share clinical information, which improves patient health results.
Adding AI to nursing in the U.S. must follow rules and ethics that require careful work by administrators. Rules on data privacy—especially HIPAA—must be followed when using AI tools that handle patient information. AI systems have to be clear about how data is used.
Nurses in the U.S. not only care for patients but also teach them about AI, especially on data privacy with health apps and devices. Administrators must support nurses with clear policies and resources to answer patient questions with confidence.
Also, nurses need protection against less human contact caused by too much automation. AI should add to nurse-patient interactions, not replace them. Caring and being physically present remain important.
Administrators and IT managers should balance AI use between making work efficient and keeping care focused on people. Ethical rules supported by groups like the ANA can guide this balance.
Many nurses in the U.S. do not know enough about AI now. Adding the N.U.R.S.E.S. framework into nurse training programs can help fix this and get nurses ready to work safely and well with AI.
Hospitals and healthcare groups should work with schools to put AI learning into nursing degrees and ongoing education. This learning covers AI basics, ethics, limits, and how to use AI in clinics. It builds nurse confidence with AI tools.
Hands-on training with AI systems like Simbo AI’s automated phone answering helps nurses and office staff get used to new technology. Hospitals can also ask nurses for feedback to check how well AI works and keep making it better.
For medical office leaders, healthcare owners, and IT teams in the U.S., using AI in nursing should be done carefully and responsibly. The N.U.R.S.E.S. framework gives a clear way to help nurses learn, use, and manage AI well.
Using AI the right way, with ongoing training and attention to improving workflow through automation like Simbo AI, can improve patient care without losing key nursing values.
By supporting this framework, healthcare leaders in the U.S. can help their facilities use AI’s benefits—better decisions, smoother workflows, and improved patient communication—while keeping patient trust and safety as the top goals.
AI literacy is crucial for nurses to ensure the safe and effective use of AI technologies in patient care, enabling them to enhance decision-making and adapt to evolving healthcare environments.
The N.U.R.S.E.S. framework—Navigate AI basics, Utilize AI strategically, Recognize AI pitfalls, Skills support, Ethics in action, and Shape the future—offers a structured approach for nurses to incorporate AI knowledge and ethics into clinical practice.
By integrating AI principles into both academic curricula and bedside learning, nurses can close the knowledge gap, ensuring proficiency in AI application and ongoing competency development.
Continuous education helps nurses stay updated with AI advances, sharpening their skills to responsibly and competently use AI tools in dynamic healthcare settings.
AI enhances nursing decision-making, supports workflow efficiency, and provides tools for improved patient diagnosis and care management.
Challenges include managing biased data, ensuring ethical application, and overcoming gaps in AI knowledge among nursing staff.
Ethical considerations ensure that AI is used responsibly, protecting patient rights and safety, while maintaining trust and integrity in healthcare delivery.
Nurses influence AI development by advocating for ethical policies, participating in governance, and applying AI tools that prioritize patient and organizational benefits.
Recognizing pitfalls such as bias and misuse enables nurses to mitigate risks, promoting safer AI implementation and safeguarding quality care.
AI literacy empowers nurses to confidently navigate emerging technologies, enhancing their role in care delivery and policy advocacy within healthcare systems.
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