Effectiveness of Artificial Intelligence-Based Nursing Interventions for Chronic Illness Care: Umbrella Review.
Jee Young Joo, Megan Liu, Youngwoo Cho and 1 others
PMID 42459089WHAT IT FOUND
AI-assisted nursing interventions for chronic illness may improve risk prediction and reduce hospital use and costs.
Effects on depression, satisfaction, safety and quality were mixed. Treat AI as a support tool, not proven care.
Key findings
01This umbrella review synthesized 8 systematic reviews covering 142 unique primary studies, including 41 randomized controlled trials.
02AI-based nursing interventions showed potential benefits for predicting adverse outcomes and reducing hospital readmissions and costs, but the evidence was too heterogeneous to pool or support one AI approach.
03Psychosocial outcomes, including depression, satisfaction, patient safety and quality of care, were mixed or inconclusive.
STILL TO COME
How it was doneWhat they foundWhat it means for RNs
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What it does not show
The review could not pool results because AI types, populations and outcome measures varied too much. The hospital utilization evidence came from a small number of reviews and primary studies. Intervention dose, frequency and duration were usually not reported. The search was limited to recent English-language systematic reviews, so older or non-English evidence may be missing. Some primary studies overlapped across reviews, risking double counting. Authors noted possible publication bias and positive-result reporting. Predictive accuracy varied, and algorithmic bias, poor explainability, data quality, electronic record integration, trust, privacy and regulation are implementation barriers.
The easy way to misread this
Do not read this as proof that AI-based nursing interventions work for chronic illness care overall. The review combined very different AI tools, settings and outcomes, and psychosocial results were mixed.