AI Could Help Nurses Catch Chronic Disease Complications Before They Become Emergencies

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Estimated reading time: 2 minutes

Artificial intelligence could help nurses identify patients at risk for worsening chronic illness before they require emergency care, according to a new umbrella review published in JMIR Nursing.

The review found AI-based nursing interventions improved risk prediction, reduced unplanned hospital use, and enabled more proactive chronic disease management.

The study, led by Jee Young Joo, RN, PhD, of the College of Nursing at Gachon University in Incheon, Republic of Korea, analyzed evidence from eight high-quality systematic reviews evaluating the use of AI in chronic illness management.

AI Helps Nurses Spot Problems Earlier

Lead author Joo and her colleagues found AI can help nurses identify patients at greater risk of complications by analyzing large amounts of clinical data for subtle patterns that might otherwise go unnoticed.

The review found the strongest evidence for improvements in:

  • Predicting health risks and disease progression
  • Reducing unplanned hospital admissions and emergency department visits
  • Supporting proactive chronic disease management
  • Potentially lowering healthcare costs

Machine learning was the most common form of AI evaluated across the studies. Researchers emphasized that AI functions as a clinical decision support tool, helping nurses make more informed decisions when caring for patients with chronic conditions such as heart disease and diabetes.

AI May Become a Routine Part of Chronic Disease Care

As the number of people living with chronic illnesses continues to grow, AI could become an increasingly valuable part of routine nursing practice.

By identifying patients whose conditions may be worsening before serious complications develop, AI may help nurses intervene earlier and potentially prevent avoidable hospitalizations.

The review suggests healthcare leaders and nurse educators can use these findings to guide the integration of AI into clinical practice and nursing education.

Questions Remain About Patient Well-Being

While the evidence supported AI’s ability to improve clinical outcomes, researchers identified an important gap.

The review found there is not yet enough evidence to determine whether AI-based nursing interventions improve patients’ psychological or emotional well-being.

The authors say additional research is needed to better understand how AI affects the overall patient experience beyond clinical outcomes.

What It Means for Nurses

Rather than replacing nurses, AI appears to have its greatest value as a clinical decision-support tool that helps clinicians identify patients who may benefit from earlier intervention.

As healthcare organizations continue adopting AI, the review suggests the technology could become an important tool for helping nurses deliver earlier, more proactive chronic disease care while researchers continue studying its impact on patient well-being.

Renée Hewitt
Renée Hewitt
Renée is Editorial Director of Nurse Approved and a healthcare storytelling pro who’s spent decades turning complex topics into compelling reads. She leads the platform’s editorial vision, championing nurses through trusted journalism, expert insights, and community-driven stories. When she’s not shaping content strategy, she’s the co-founder of IntoBirds, proving her advocacy extends well beyond humans.

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