Clinical Application Effects of AI-Enabled Continuous Quality Improvement Model in Critical Care Nursing: A Meta-Analysis
Abstract
might help improve nursing results in ICU. But no complete meta analysis has been carried out on all the effects that AI CQI designs could
have in particular care nursing. Methods: PubMed, Embase, CINAHL, Web of Science, CNKI, Wanfang were all searched from inception
to December 2024. The meta-analysis was carried out by Revman, we used I2
for heterogeneity and Egger's to check on publication bias.
Results: In which 18 had a total of 4276. The AI enabled CQI was signifcantly associated with the reduction of nrsng adverse evnt ryt( RR =
0. 54, 95 %CI: 0. 44 -0. 67, P<0. 001), nursing qualty scrne improvemt(SMD=1. 23, 95% CI: 0. 98 - 1. 48, P < 0. 001) and icu los(t) (WMD =
-1. 86 days, 95% CI:-2. 41 to -1. 31, P< 0. 001). There is no publication bias found. Conclusion: The AI-CQI improved the quality of care in
the intensive care, Patient Safety and the process of Care. We've got to get randomized multiple center studies like we found it.
Keywords
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DOI: http://dx.doi.org/10.70711/pmr.v3i7.9424
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