Authors
Sammy A Kimanzi, Lucy W Kivuti-Bitok, Dorcas W Maina, Eunice A Omondi
Published in
Computers, informatics, nursing : CIN. Sep 22, 2026. Epub Sep 22, 2026.
Abstract
The application of artificial intelligence (AI) in nursing care has surfaced as a revolutionary method for improving the quality and efficiency of patient care. Examining AI-driven care plans could yield valuable insights for improving nursing care. A pretest-posttest quasi-experimental study with 43 participants compared manual and AI-generated care plans in performance expectancy, effort expectancy, user satisfaction, and efficiency, before and after the intervention. AI-driven care plans were produced through www.careplans.com in line with NANDA taxonomy. Participants were selected consecutively and completed a self-administered questionnaire. Data analysis was conducted using R (v4.1.2), utilizing the Wilcoxon signed-rank test for paired data. Results were illustrated in box plots, with differences deemed significant at P-values <.05. Care plans generated by AI consistently demonstrated superior performance compared to those developed manually across all evaluated criteria. The median scores for AI-generated plans were 91.67%, 93.75%, 91.67%, and 92.86% in perceived efficiency. In contrast, the manually written plans achieved scores of 58.33%, 56.25%, 50%, and 45%, respectively. Wilcoxon signed-rank test indicated that these differences were statistically significant (P< .001). Utilising efficient AI-generated care plans enhances nursing care, allowing for the reallocation of time saved to focus on direct patient care.
PMID:
42773861
Bibliographic data and abstract were imported from PubMed on 23 Sep 2026.
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