The Impact and Issues of Artificial Intelligence in Nursing Science and Healthcare Settings
Open accessAbstract
Research and development of artificial intelligence (AI)-based technologies systems in healthcare has increased over the past decade, highlighting the strong potential of AI to improve the quality of nursing care. To meet the new demands for nursing care, it is necessary that AI be integrated into nursing science and healthcare setting, especially in nursing care. The current challenge is to transform this expanded set of technology into clinical benefits for patients, through more advanced, accurate, practical, effective, efficient, and economical and personalized care. Along with the potential positive outcomes, AI technology also has unintended consequences that have the potential to negatively impact and adversely affect the nursing profession and the primary purpose of nursing practice in healthcare system. This aimed to explore and discuss the impact of applying AI in nursing science and healthcare system to provide approximate nursing care. Some of the impacts that can be evaluated and seen today in the context of using AI technology systems in the scope of nursing and healthcare are expanding access to quality medical care, improving medical records, and improving the quality of services. The use of AI technology systems also has some issues, such as bias and algorithms, which are drawbacks that need to be considered when evaluating the accuracy of the displayed results.
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The absence of nursing-specific AI frameworks hinders insight into long-term impacts of nursing-specific AI frameworks on nurse clinical workflow and patient outcomes.
“This absence limits evaluation and improvement of AI tools and hinders insight into long-term impacts of nursing-specific AI frameworks on nurse clinical workflow and patient outcomes.4,5,7”
From Empathic and agentic artificial intelligence in nursing: perspectives on a human-centered framework for cancer care navigation in the United States of America (2026) · cites this paper as [7]
The Introduction says few AI studies reach real-world use and even fewer evaluate clinical outcomes; the Discussion of Topic identifies gaps in AI outcomes research. These passages support a gap in evaluating AI’s effects, but they do not identify an absence of nursing-specific AI frameworks or say that such an absence hinders evaluation or insight into long-term workflow and patient outcomes. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe absence of nursing-specific AI frameworks limits evaluation and improvement of AI tools.
“This absence limits evaluation and improvement of AI tools and hinders insight into long-term impacts of nursing-specific AI frameworks on nurse clinical workflow and patient outcomes.4,5,7”
From Empathic and agentic artificial intelligence in nursing: perspectives on a human-centered framework for cancer care navigation in the United States of America (2026) · cites this paper as [7]
The Introduction (page not available) says few AI studies evaluate clinical outcomes, and the Discussion of Topic identifies gaps in AI outcomes research. Neither section identifies an absence of nursing-specific AI frameworks or says that such an absence limits evaluation and improvement of AI tools. Searches for nursing-specific frameworks and their effects on evaluation and clinical workflow found no passage addressing that causal claim. (LLM, conf=0.72)
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Testing Machine Learning-Based Pain Assessment for Postoperative Geriatric Patients
Kurt, T., & Taşdemir, N. (2025) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000001248
Takashima, Y., Ito, H., Soriano, G. P., Yasuhara, Y., Osaka, K., Schoenhofer, S. O., & Tanioka, T. (2025) · Belitung Nursing Journal · doi:10.33546/bnj.3623 · Cited by 1 · see citing works
Deep Learning-Based Decision Support System for Nurse Staff in Hospitals
Chen, J., He, F., Tang, L., & Gu, L. (2025) · Big Data · doi:10.1089/big.2024.0122 · Cited by 1 · see citing works
Bager, P., & Bager, L. (2025) · Springer eBooks · doi:10.1007/978-3-031-87503-8_50
Artificial Intelligence as an Adjunct to Nurses in Pediatrics and Pediatric Dentistry
Chauhan, D. (2025) · Dental Journal of Advance Studies · doi:10.5005/djas-11014-0079
Pediatri Hemşireliğinde Yapay Zekâ Destekli Yaklaşımlar
Tutar, Ş., Özgörü, H., & Şensoy, Ö. (2025) · Akdeniz Hemşirelik Dergisi · doi:10.59398/ahd.1741115
The Emerging Roles of AI in Self-Directed Stress-Management: a Systematic Review (Preprint)Preprint
Reyes, M. K. G., Min, S. T. S., & Hartanto, A. (2026) · doi:10.2196/preprints.90709
Harun, A. (2026) · EDUCATUM Journal of Social Sciences · doi:10.37134/ejoss.vol12.sp2.7.2026
İnam, Ö., Kahvecioğlu, Y., & Okay, S. (2026) · Journal of Human Lactation · doi:10.1177/08903344261446830
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Tang, B., He, Y., Xiang, Y., & Chen, Y. (2026) · BMC Nursing · doi:10.1186/s12912-026-04860-0
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Surveying Artificial Intelligence (AI) Attitudes, Use, and Competencies Among Nursing Faculty
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Inteligencia artificial aplicada en el cuidado de enfermería
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Liu, Y., Huang, Y., Huang, A., Chen, X., Chen, Y., & Li, L. (2026) · Frontiers in Medicine · doi:10.3389/fmed.2026.1929882
Sarıtaş, E., & Öztürk, P. Ç. (2026) · Sakarya Üniversitesi Holistik Sağlık Dergisi · doi:10.54803/sauhsd.1924219
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AI Use, Perceptions, and Perceived Impact Among Nursing Students: Cross-Sectional Study
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Mawla, A. A. E., Younis, A. A. A., Ahmed, F. R., Atalla, A. D. G., Shehata, Y. M., & Morsy, A. A. I. (2026) · Teaching and learning in nursing · doi:10.1016/j.teln.2026.09.012
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- Authors
- Pailaha, A. D.
- Affiliations
- Inpatient Department Nurse, General Ward Nursing, Department of Nursing, Siloam Hospitals Agora, Jakarta, Indonesia
- Corresponding author
- Pailaha, Aprianto Daniel
- Venue
- SAGE Open Nursing
- Publisher
- SAGE Publications
- Published
- 2023-01
- Volume
- 9
- Pages
- 23779608231196847-23779608231196847
- ISSN
- 2377-9608 (ISSN-L)
- PMC
- PMC10492460
- OpenAlex
- W4386544836
- Cited by
- 85
- References
- 30
- Citations by year
- 2026: 21 · 2025: 33 · 2024: 31
- FWCI
- 3.39
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- SAGE Open Nursing (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- artificial intelligence in healthcare, nursing care, nursing care quality, individualized care, algorithmic bias, unintended consequences of AI, medical records, health care access, nursing profession
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