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Exploring the Applicability of Artificial Intelligence for the Improvement of Nursing Practice in Korea.
- Source :
- Journal of Korean Academy of Nursing Administration; Dec2023, Vol. 29 Issue 5, p564-576, 13p
- Publication Year :
- 2023
-
Abstract
- Purpose: Based on a literature review of artificial intelligence (AI) applications within nursing tasks, this study delves into the feasibility of employing AI to improve nursing practice in Korea. Methods: We used "nursing" and "artificial intelligence" as keywords to search academic databases, resulting in 96 relevant studies from an initial pool of 940. After a detailed review, 35 studies were selected for analysis based on nursing process stages. Results: AI improves nursing assessment by enhancing pain diagnosis, fall detection, and movement monitoring in older adults. It aids nursing diagnosis through clinical decision support, risk prediction, and emergency patient triage. Further, it expedites the creation of precise plans utilizing predictive models in nursing planning. AI also forecasts medication errors and reduces the nursing documentation burden for nursing implementation. Additionally, it manages (re)hospitalization risks by assessing patient risk and prognoses in nursing evaluation. Conclusion: AI in Korean nursing can enhance assessment and diagnosis accuracy, promote a prevention-focused paradigm through risk prediction, and ease the burden of nursing practice amidst human resource shortages. [ABSTRACT FROM AUTHOR]
- Subjects :
- PAIN diagnosis
CLINICAL decision support systems
MEDICAL triage
NURSING models
NURSING
ARTIFICIAL intelligence
PATIENTS
MEDICATION errors
NURSING practice
RISK assessment
PATIENT monitoring
DOCUMENTATION
QUALITY assurance
ACCIDENTAL falls
BODY movement
EMERGENCY medical services
FORECASTING
PREDICTION models
Subjects
Details
- Language :
- Korean
- ISSN :
- 12259330
- Volume :
- 29
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Journal of Korean Academy of Nursing Administration
- Publication Type :
- Academic Journal
- Accession number :
- 174444942
- Full Text :
- https://doi.org/10.11111/jkana.2023.29.5.564