Reliance on artificial intelligence (AI) and the use of AI-based solutions to tackle everyday problems is growing by the day. But what does it mean for the nursing profession? Micromedex nursing experts Angela Anderson, MSN, RN-BC, and Courtney Holmes, RN, IFNCP, explore how artificial intelligence in nursing is creating new opportunities.
From enhancing clinical decision support and streamlining automation of administrative tasks to the integration of AI for ambient listening, these advancements can help the nursing workforce reclaim time for direct patient care in a variety of healthcare system environments. Let’s look at some examples of AI in nursing practice.
Nurses are the backbone of patient care, juggling countless responsibilities to ensure their patients receive the best possible treatment and support. They also face significant challenges in their clinical practice, from transitioning between units—often outside their specialty—to managing critically ill patients on multiple complex medications.
Angela Anderson, MSN, RN-BC, Senior Director of Clinical Innovation at Micromedex, highlights how these transitions demand that nurses quickly absorb and apply large amounts of complex clinical evidence and patient data. Applying AI technologies including AI algorithms and natural language processing to clinical decision support tools can help ease this cognitive burden by accelerating the information search and retrieval process and providing instant access to nursing-specific evidence.
“With their search efforts accelerated by the application of AI, nurses can access critical information such as IV compatibility checks and clear drug interaction data faster,” Angela explains. “This enables nurses to focus on what matters most – delivering exceptional nursing care and protecting patient safety.”
Courtney Holmes, RN, IFNCP, Clinical Director at Micromedex, emphasizes the responsibility of nurses often being the primary point of contact for patients. This requires balancing their own need for rapid self-education with the need to provide patient education and involves simplifying and communicating intricate medical information. “Generative AI and machine learning can assist by serving up evidence-based medication counseling information,” Courtney shares. “It helps reduce the cognitive load around patient education, allowing more space for critical thinking and clinical judgment.”
AI’s role in using predictive analytics and algorithms to identify patterns and provide insights can serve as a valuable “sidekick” for nurses, helping cut time spent on documentation and coordination. For example, the broader adoption of ambient listening AI for nurses, mirroring its success with other clinicians and healthcare professionals.
“Nurses receive, track, and respond to a wide variety of information from different sources, stakeholders and providers in the context of unique patient scenarios throughout the day,” Angela explains. “AI can help with the capture and analysis of patient monitoring and other datasets, freeing up time and brain space for informed decision-making and action.” In terms of care coordination, AI could track conversations and activities in real-time, spotting gaps or items that require follow up action. It could also potentially limit health disparities by assisting with the creation of education that is specifically tailored to an individual patient’s needs.
Angela expands; “One of our clients recently piloted ambient listening AI for nurses and found it increased patient satisfaction scores, because nurses were more engaged with patients and less focused on administrative tasks.” Improving those scores is a real win for the health system and nurse leader, ultimately contributing to better patient outcomes and transforming healthcare delivery.
“I’ve noticed a decline in nursing time available to spend with patients, particularly in specialized fields like pediatric oncology,” Courtney shares. “I’m excited to see how AI-driven digital health initiatives can help nurses reclaim this time, fostering deeper connections with patients, which is the core reason many become nursing professionals.”
An example could be AI tools and features integrated into electronic health records (EHRs) to assist with nurse handover notes and care plan summaries to further streamline their workflows.
“Human connection is an important part of nursing, and AI development can’t replace that,” explains Angela. Nor can AI systems replace the decades of expertise nurses bring to person-centered care and understanding individual needs and interventions. Rather, the use of artificial intelligence can serve as a valuable assistant to nurses, handling repetitive tasks, surfacing critical information faster, and helping alleviate cognitive load. It can empower them to excel in a variety of nursing roles and healthcare settings, giving them more time and space to focus on patient care and well-being.
Education around the use of AI in healthcare is essential for nursing students and those entering the nursing profession. “Nursing education and nursing programs should put a focus on understanding where the clinical data surfaced by AI tools actually originates, assessing the trustworthiness of AI tools, and developing sound clinical judgment,” Courtney remarks. This strong foundation will enable nurses to use these technologies responsibly and effectively in their nursing careers.
As the use of AI in healthcare expands, healthcare systems must set clear guidelines for AI implementation, ensure ethical use, and protect sensitive patient data. Upholding ethical standards in clinical practice is key to maintaining public trust and meeting regulatory requirements.
See how AI-powered search is accelerating access to clinical decision support in healthcare organizations and providers worldwide.