Applications of Artificial Intelligence in Nursing Care: A Systematic Review

Abstract

Aim. To synthesise the available evidence on the applicability of artificial intelligence in nursing care. Background. Artificial intelligence involves the replication of human cognitive abilities in machines, allowing to perform tasks that conventionally necessitate human cognition. However, its application in health sciences is a recent one, and its use is currently limited to supporting the diagnosis and prognosis of hospitalised patients, among others. Evaluation. A systematic review was conducted in the PubMed-Medline, Scopus, CINAHL, Web of Science, and Nursing & Allied Health databases until September 2022, following the PRISMA guidelines. Key Issues. A total of 21 articles were selected for the review. The different applications of artificial intelligence in nursing identified comprised (i) advances in early disease detection and clinical decision making; (ii) artificial intelligence-based support systems in nursing for patient monitoring and workflow optimisation; and (iii) artificial intelligence insights for nursing training and education. Conclusion. Artificial intelligence-based systems demonstrated increased autonomy of patients and professionals in care processes such as wound management through guided instructions, improved workflows, and efficiency in terms of time, materials, and human resources. Implications for Nursing Management. Artificial intelligence applied to nursing practice can be a very useful resource for professionals, managers, and supervisors. It has the potential to change current working flow systems and may serve as a down-to-earth resource to support nursing professionals in their decision-making process that ensures high quality and patient safety care.

AI-Assisted Decision-Making in Long-Term Care: Qualitative Study on Prerequisites for Responsible Innovation (Preprint)

“…Finally, as our efforts to contextualize and operationalize high-level responsible AI principles to the context of AI-assisted decision-making by nurses and other care professionals in LTC have shown promising outcomes, we recommend conducting further research in this area. A vast amount of research has been conducted on the (potential) supportive roles of AI-based technologies in the nursing process [6][7][8][9], and into high-level requirements for responsible AI innovation [25][26][27]. This study builds upon previous studies in both research fields by adding the perspective of a variety of experienced nurses and other LTC professionals on opportunities and prerequisites for responsible AI-assisted decision-making.…”

“…In the long-term care (LTC) for older adults, technologies based on artificial intelligence (AI) are increasingly being developed and deployed to support the nursing process, from the assessment and diagnosis of care needs to the planning, implementation and evaluation of care strategies addressing these needs [1][2][3][4][5][6][7][8][9]. For instance, AI-based decision-support systems (AI-DSSs) could support specific aspects of the nursing process such as monitoring clients' behavior and vital signs with the aim to identify frailty, to assess dementia-related problems and suitable interventions, and to triage health deteriorations before eventually transferring clients to an emergency department or institutional care setting [1,[10][11][12][13].…”

Evaluating the Quality of Postpartum Hemorrhage Nursing Care Plans Generated by Artificial Intelligence Models

“…5 In our constantly evolving modern age of technology, nurses need to adopt contemporary technologies and innovations to effectively sustain their nursing processes, improve their professional development, and provide highquality care to patients. 6,7 In this context, artificial intelligence (AI), which has made significant recent advancements, may support nursing practices by offering real-time decision support, minimizing time needed for administrative tasks, and streamlining the efficient management of patient data and care. 8,9 Furthermore, AI-based support systems can assist in making clinical decisions, thereby contributing to the betterment of evidencebased nursing care.…”

“…20,21 Among medical AI models (eg, MedQA, MedicalGPT, Med-PaLM), Med-PaLM stands out as the AI model demonstrating the best clinical knowledge performance. 21 The potential applications of AI in various nursing domains such as education 22,23 and nursing care 6,7,24 are currently under intensive research. The health care sector is a transformational industry that requires the evaluation of the best methods for integrating Al.…”

“…The health care sector is a transformational industry that requires the evaluation of the best methods for integrating Al. 6,7 It is anticipated that nursing professionals can benefit from AI models such as GPT-4 and Med-PaLM to interpret patient data, enhance decision-making, and facilitate communication. [24][25][26] However, generally, there are 2 different opinions on the utilization of AI in nursing care services.…”