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. 2022 Nov;30(8):3654-3674.
doi: 10.1111/jonm.13425. Epub 2021 Aug 13.

The role of artificial intelligence in enhancing clinical nursing care: A scoping review

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The role of artificial intelligence in enhancing clinical nursing care: A scoping review

Zi Qi Pamela Ng et al. J Nurs Manag. 2022 Nov.

Abstract

Aim: To present an overview of how artificial intelligence has been used to improve clinical nursing care.

Background: Artificial intelligence has been reshaping the healthcare industry but little is known about its applicability in enhancing nursing care.

Evaluation: A scoping review was conducted. Seven electronic databases (CINAHL, Cochrane Library, EMBASE, IEEE Xplore, PubMed, Scopus, and Web of Science) were searched from 1 January 2010 till 20 December 2020. Grey literature and reference lists of included articles were also searched.

Key issues: Thirty-seven studies encapsulating the use of artificial intelligence in improving clinical nursing care were included in this review. Six use cases were identified - documentation, formulating nursing diagnoses, formulating nursing care plans, patient monitoring, patient care prediction such as falls prediction (most common) and wound management. Various techniques of machine learning and classification were used for predictive analyses and to improve nurses' preparedness and management of patients' conditions CONCLUSION: This review highlighted the potential of artificial intelligence in improving the quality of nursing care. However, more randomized controlled trials in real-life healthcare settings should be conducted to enhance the rigor of evidence.

Implications for nursing management: Education in the application of artificial intelligence should be promoted to empower nurses to lead technological transformations and not passively trail behind others.

Keywords: artificial intelligence; healthcare; machine learning; nursing; patient care.

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References

REFERENCES

    1. Abhisht, N. S. (2020). A study on artificial intelligence. International Research Journal of Engineering and Technology, 7(8), 2195-2200.
    1. Abranches, D., O'Sullivan, D., & Bird, J. (2019). Nurse-led design and development of an expert system for pressure ulcer management. Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, 1-6.
    1. Adelson, P., & Eckert, M. (2020). Skin cancer in regional, rural and remote Australia: Opportunities for service improvement through technological advances and interdisciplinary care. Australian Journal of Advanced Nursing, 37(2), 372-374.
    1. Aguña, A. G., Batalla, M. F., Duque, A. C., Jaén, S. H., Macario, E. M. S., Rodríguez, M. L. J., García, J. M. S., Sánchez, S. C. R., Vidal, N. V., & Camara, D. F. C. (2018). Elements for an ontology of care in the field of artificial intelligence. Studies in Health Technology and Informatics, 250, 198-198.
    1. An, N., Jin, L., Ming, H., Cheng, W., & Yang, J. (2019). Neural-network-based outcome classification for nursing care. International Conference on Computational & Experimental Engineering and Sciences (pp. 1091-1099).

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