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European Journal of Applied Sciences – Vol. 11, No. 4
Publication Date: August 25, 2023
DOI:10.14738/aivp.114.15154
Ahmed, N. (2023). Artificial Intelligence Applications in Nursing. European Journal of Applied Sciences, Vol - 11(4). 62-65.
Services for Science and Education – United Kingdom
Artificial Intelligence Applications in Nursing
Noha Ahmed, DBA, MSc, PGDCA
Nursing Informatics Specialist,
Nursing Informatics Department, HMC, Qatar
INTRODUCTION
Artificial intelligence (AI) is considered as a technique to train computers to mimic human
cognitive activities including reasoning, learning, decision making and real time
communication. It is the new future and often regarded as super intelligence. While the world
is rapidly transforming towards virtual spaces and global village theme and transforming our
living mode, work cultures and interests, AI can be regarded as the driving force behind these
major transformations. As per recent study conducted, global AI healthcare innovations would
spike up with an estimated spending of about $ 36.5 billion by 2025. (1) This research article
will provide a brief overview of Artificial Intelligence and how it transforms the medical world.
It focuses on major transformations in nursing field with the help of AI and the way its
automating manual tiresome and recurring tasks performed by nurses to auto scheduled jobs.
While AI based techniques are applied in nursing for enhanced patient care, decision making,
and service delivery, it has brought advancements in health care outcomes.
The number of researches around AI in health and nursing is growing at a fast pace since last
decade. Living in a world where amount of data is increasing exponentially has opened new
avenues for AI researchers and developers to find new insights from given data extracted from
rich healthcare systems and is offering various transformations towards the development of a
reduced, cost efficient and reliable health care applications (2)
There are several studies focusing on improving nursing documentation and data standards.
supporting nurses’ decision-making and care delivery. Other studies employed AI to predict
patient triage and enhance clinical diagnoses, with two focusing on monitoring patients and
their environment. Some studies reported a mixture of potential benefits. However, as the AI
approaches were not used by nurses or midwives in professional practice, their efficacy and
impact on clinical decision-making and care delivery in real-world settings remain largely
unknown (3,4)
APPLICATIONS OF AI IN NURSING
One of the very first step towards analyzing the impact of Artificial Intelligence techniques in
nursing is the wider domain insights identification where its adding value in nursing field as
studied in Booth et al. 2021. (5) For this we also need to assess the roles of nurses as an end
user of AI models and as health care experts. This will enable better research and
improvements identification in leading and defining the development of modern AI in nursing
as stated by O’Connor et al. 2022, where clinical and professional care experiences of nurses
will play a significant part in a well-designed automation yet human friendly patient care tools.
However, as per recent research done by Kikuchi 2020 the participation of nurses is still below
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Ahmed, N. (2023). Artificial Intelligence Applications in Nursing. European Journal of Applied Sciences, Vol - 11(4). 62-65.
URL: http://dx.doi.org/10.14738/aivp.114.15154
the benchmark and needs more clarity with respect to the domain. Another major reason
behind this is early-stage exclusion of nurses, where they are not added in development and
design discussion. Another issue is terminology variations at a higher level due to lack of
common understandable vocabulary amongst both domain experts which also results in a
communication barrier for nurses to participate in a modernized research and architecture
design. Reviewing recent researches published on AI in nursing, the knowledge gap, benchmark
definitions, ideas, and theories for AI in nursing can be fruitful. (6,7)
Patient Safety and Healthcare Outcomes
The most report studies in areas of healthcare that utilizes AI application were critical care,
general nursing care, wound care, falls, infection, older adult care, hospital readmissions,
midwifery care, emergency care and hospital discharge. Dermody and Fritz 2019 suggested an
automated behavioral detection technique that recognizes elopement attitudes in Alzheimer's
patients by applying a Markov model. It has been observed that accurate predictions of
detectors would ultimately reduce the elopement rate and its risk. This will also save the
patient from severe consequences being faced by them. Similarly, another major AI application
in nursing care is a personal data collector via real-time house monitoring sensors, electronic
health records, human activity recognition trackers, and daily health care reports for nursing
home care assistance evaluation as studied in Duan et al. 2022. Such applications are highly
suggested in daycares, hospital settings, educational settings, for disabled among others.
There are also scenarios where physical activity intervention record is required such as
pressure ulcers, hand washing skills, length of stay, etc. (8,9)
Nursing Administration and Management
Application of AI in Nursing administration and management domains are addressed in recent
researches focusing on nursing data and documentation by examining how AI can improve
nursing ontologies, terminologies, data quality or written nursing notes. It also includes
studying variables to predict nurse staffing in acute settings, burnout in nurses, variables
affecting nurses' job performance and developing a model to predict sleep disturbances of
nurses. (10,11,12)
Nursing Education
In the domain of Nursing Education, AI are utilized to predict student academic failure,
graduation, and completion rates of undergraduate nursing students, or to learn how to use
medical devices using AI-assisted software. In healthcare organizations, virtual reality training
can improve knowledge in nursing education and be used in pediatric and adult populations as
a treatment tool or clinical intervention (13,14,15)
CHALLENGES OF AI IN NURSING
In order to ensure that the outcomes of predictive models were clinically relevant and that
models were built using retrospective datasets, which may or may not be useful for future
needs, nurses should be knowledgeable about the concepts of AI in addition to their
involvement in testing, implementing, and evaluating the AI system. Lack of AI expertise in
nurses are among the challenges which could hinder AI development and application in
healthcare. Special consideration should be provided pertaining to the lack of governance and
regulation around the use of AI to help address some of the ethical and legal issues (16,17)
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European Journal of Applied Sciences (EJAS) Vol. 11, Issue 4, August-2023
Several AI applications will be helpful for nursing, but this may cause some serious, legitimate
concerns among nurses, who fear losing their jobs as a result of technology taking the place of
people. Similarly, this also introduces another debate of neglecting health care ethics and
principles, data breach and outsourcing risks and some other concerns towards ethical
practices of health records. These apprehensions can be alleviated by sharing appropriate
guidelines about artificial intelligence to end users, (18)
CONCLUSION
The use of artificial intelligence in nursing practice was depicted in this article, along with its
benefits for enhancing the necessary practice. There are few studies on how nursing
professionals can influence artificial intelligence framework and how to incorporate them into
their daily practice.
The Nursing community should focus more AI applications in patient safety, promoting team
communication and offering accurate care. they should support developing researches and
regulation for the successful and widespread implementation of AI in healthcare setting.
References
1. Nassim Taleb et al. (2023) Artificial Intelligence (AI) in Healthcare, BRAND MINDS https://brandminds.com
2. Abuzaid, M. M., Elshami, W., & Fadden, S. M. (2022). Integration of artificial intelligence into nursing
practice. Health and technology, 12(6), 1109–1115.
3. Hwang, Gwo-Jen, Kai-Yu Tang, and Yun-Fang Tu. 2022. What an artificial intelligence (AI) supports nursing
education: profiling the roles, applications, and trends of ai in nursing education research (1993–2020).
Interactive Learning Environments, 1–20.
4. Seibert, K., Domhoff, D., Bruch, D., Schulte-Althoff, M., Fürstenau, D., Biessmann, F., & Wolf-Ostermann, K.
(2021). Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review. Journal of medical
Internet research, 23(11), e26522.
5. Booth, R. G., Strudwick, G., McBride, S., O’Connor, S., & Solano López, A. L. (2021). How the nursing
profession should adapt for a digital future. The BMJ, 373, n1190.
https://doi.org/10.1136/bmj.n1190O’Connor,
6. O'Connor, S., Yan, Y., Thilo, F. J. S., Felzmann, H., Dowding, D., & Lee, J. J. (2022). Artificial intelligence in
nursing and midwifery: A systematic review. Journal of clinical nursing, 10.1111/jocn.16478. Advance online
publication. https://doi.org/10.1111/jocn.16478.
7. Kikuchi, R. 2020. Application of artificial intelligence technology in nursing studies: a systematic review. On- Line Journal of Nursing Informatics 24 (1).
8. Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T., & Bamford, M. (2020). Predicted Influences of
Artificial Intelligence on the Domains of Nursing: Scoping Review. JMIR nursing, 3(1), e23939.
9. Dermody, G., & Fritz, R. (2019). A conceptual framework for clinicians working with artificial intelligence
and health-assistive Smart Homes. Nursing inquiry, 26(1), e12267.
10. Duan, X., Su, D., Yu, H., Xin, W., Wang, Y., & Zhao, Z. (2022). Adoption of Artificial Intelligence (AI)-Based
Computerized Tomography (CT) Evaluation of Comprehensive Nursing in the Operation Room in
Page 4 of 4
65
Ahmed, N. (2023). Artificial Intelligence Applications in Nursing. European Journal of Applied Sciences, Vol - 11(4). 62-65.
URL: http://dx.doi.org/10.14738/aivp.114.15154
Laparoscopy-Guided Radical Surgery of Colon Cancer. Computational intelligence and neuroscience, 2022,
2180788.
11. Guo, C., & Li, H. (2022). Application of 5G network combined with AI robots in personalized nursing in China:
A literature review. Frontiers in public health, 10, 948303.
12. Jeong G. H. (2020). Artificial intelligence, machine learning, and deep learning in women's health
nursing. Korean journal of women health nursing, 26(1), 5–9.
13. Robert N. (2019). How artificial intelligence is changing nursing. Nursing management, 50(9), 30–39.
14. Seibert, K., Domhoff, D., Bruch, D., Schulte-Althoff, M., Fürstenau, D., Biessmann, F., & Wolf-Ostermann, K.
(2021). Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review. Journal of medical
Internet research, 23(11), e26522.
15. ZHANG, Pengbo, and Fen XU. 2021. Effect of ai deep learning techniques on possible complications and
clinical nursing quality of patients with coronary heart disease. Food Science and Technology 42.
16. Ng, Z. Q. P., Ling, L. Y. J., Chew, H. S. J., & Lau, Y. (2022). The role of artificial intelligence in enhancing clinical
nursing care: A scoping review. Journal of nursing management, 30(8), 3654-3674.
17. von Gerich, H., Moen, H., Block, L. J., Chu, C. H., DeForest, H., Hobensack, M., ... & Peltonen, L. M. (2022).
Artiicial Intelligence-based technologies in nursing: A scoping literature review of the
evidence. International journal of nursing studies, 127, 104153.
18. Ronquillo, C. E., Peltonen, L. M., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., ... & Topaz, M. (2021).
Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of
the Nursing and Artificial Intelligence Leadership Collaborative. Journal of advanced nursing, 77(9), 3707-
3717.