Artificial intelligence in nursing: Current trends, possibilities and pitfalls

Sirwan Khalid Ahmed

► To cite this version:

Sirwan Khalid Ahmed. Artificial intelligence in nursing: Current trends, possibilities and pitfalls. Journal of Medicine, Surgery, and Public Health, 2024, 3, pp.100072. 10.1016/j.glmedi.2024.100072. hal-04733737

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# Artificial intelligence in nursing: Current trends, possibilities and pitfalls

## ARTICLE INFO

### Keywords

Artificial intelligence

Nursing

Nursing practice

Nursing education

Nursing research

Academic writing

Ethical issues

## ABSTRACT

This paper explores the integration of artificial intelligence (AI) in nursing and its implications for healthcare research and academic writing. The use of AI in healthcare has become increasingly prevalent across various industries and holds great promise for optimizing clinical workflows, enhancing diagnostic accuracy, and improving patient engagement. Moreover, AI has the potential to expedite research cycles and foster collaboration in academic writing, thereby making significant contributions to the field. Nevertheless, there are challenges associated with this paradigm shift, such as concerns about the loss of the human touch in patient care, ethical dilemmas concerning algorithmic bias and data privacy, and the risk of excessive reliance on AI systems. Addressing these challenges requires a balanced approach that places patient-centered care at the forefront and upholds ethical standards. To achieve this, nurses and researchers must actively participate in the design, implementation, and regulation of AI technologies, ensuring that they align with clinical expertise and patient-centered values. Furthermore, the establishment of transparent guidelines and regulations is essential to govern the responsible use of AI. Additionally, training programs should equip professionals with the necessary skills to effectively collaborate with AI systems. By fostering collaboration, transparency, and accountability, the complexities of integrating AI can be effectively managed, thereby unlocking its transformative potential to revolutionize patient care and advance knowledge discovery in the field of nursing and healthcare research.

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Dear Editor,

In recent years, the integration of artificial intelligence (AI) into various sectors has revolutionized industries, and healthcare is no exception [1]. Among the many facets of healthcare, nursing plays a crucial role in patient care, and the incorporation of AI has the potential to enhance and streamline nursing practices [2-4]. However, while AI offers promising possibilities, there are also notable pitfalls that must be carefully considered and navigated. This paper delves into the potential benefits and challenges of incorporating AI in nursing, highlighting the opportunities for improved patient outcomes alongside the ethical and human-centric concerns that require thoughtful attention.

The integration of AI in nursing holds immense promise for revolutionizing patient care [5]. AI-powered technologies can assist nurses in numerous ways, optimizing clinical workflows and decision-making processes [6-8]. One significant avenue is the use of AI for predictive analytics, which can help identify patients at risk of deteriorating health conditions [9]. By analyzing vast amounts of patient data, AI algorithms can recognize patterns and alert nurses to potential issues before they become critical, enabling proactive interventions and improved patient outcomes [10,11]. Another potential area of advancement lies in diagnosis and treatment planning [12]. AI can support nurses in making accurate diagnoses by analyzing complex medical data, such as medical images and test results. This can significantly reduce human errors and enhance diagnostic accuracy. Additionally, AI-driven treatment recommendations can provide nurses with evidence-based insights, ensuring that patients receive the most appropriate care tailored to their individual needs [13,14]. AI-powered virtual assistants and chatbots also hold the potential to improve patient engagement and education. These tools can provide patients with accurate medical information, answer

queries, and offer guidance on post-discharge care. By empowering patients with knowledge, nurses can focus on more critical aspects of care while fostering patient autonomy and well-being.

In nursing policy and administration, AI technologies can streamline administrative work, optimize resource allocation, and improve organizational efficiency. AI-powered systems analyze healthcare data to identify areas for improvement and provide policymakers with evidence-based information [15]. They can also automate routine tasks like appointment scheduling and financial management, allowing nurses to focus on direct patient care. However, implementing AI in nursing policy and administration requires addressing challenges related to data governance, interoperability, and workforce readiness [15]. Collaboration between policymakers, healthcare leaders, and technology developers is crucial to fully harness AI's capabilities while minimizing risks and ensuring ethical and equitable integration into nursing practice and administration.

The impact of AI on nursing education is of great importance [4,15]. It exerts its influence on curriculum design and instructional methodologies. The integration of virtual simulations and AI-driven educational tools provides nursing students with immersive learning experiences [15]. Moreover, AI is capable of assessing students' clinical skills and identifying areas of knowledge gaps, thereby enabling customized educational interventions. Additionally, AI technologies grant access to the most current information and evidence-based practices, thereby fostering continuous learning and professional development. Nonetheless, there are challenges that need to be addressed, such as the necessity for faculty training, investment in infrastructure, and the ethical use of AI within educational environments. Nursing educators must adeptly navigate these changes in order to fully leverage the benefits of AI in
enhancing the quality and effectiveness of nursing education [15].

AI-driven technologies have unparalleled capabilities in data analysis, predictive modeling, and decision assistance, empowering researchers to extract important insights from extensive healthcare data. AI can aid researchers in several aspects of academic writing, including as doing literature reviews, analyzing data, and even producing initial drafts [16–18]. This can accelerate research cycles and improve the overall quality of scholarly work. Moreover, algorithms powered by artificial intelligence can assist in detecting areas of research that need attention, proposing possible approaches for conducting studies, and promoting cooperation among researchers from other fields. Nevertheless, researchers must exercise caution and carefully navigate through significant drawbacks that accompany this potential. The importance of ethical considerations regarding data privacy, algorithmic bias, and the proper utilization of AI technologies cannot be overstated [1]. Moreover, there is a possible danger of excessively depending on AI systems, which could undermine the development of critical thinking abilities and creativity in academic pursuits [19]. Achieving a harmonious equilibrium between utilizing the advantages of AI and safeguarding the authenticity and human-centered principles of healthcare research is crucial in fully realizing the capabilities of AI in developing nursing and healthcare studies.

While the potential benefits of AI in nursing are remarkable, there are notable challenges that require careful consideration. One of the primary concerns is the potential erosion of the human touch in patient care. Nursing is deeply rooted in empathy, compassion, and the ability to form meaningful connections with patients [4]. The introduction of AI-run interactions could lead to a loss of the human element, potentially affecting patient satisfaction and overall well-being. Another significant ethical concern involves data privacy and security [20]. AI systems rely heavily on patient data, which raises questions about how this information is collected, stored, and shared. Ensuring that patient data remains confidential and is used responsibly is essential to building trust in AI-powered nursing interventions. Furthermore, there is a risk of algorithmic bias, where AI systems may inadvertently perpetuate existing healthcare disparities [21–24]. If not properly trained and validated on diverse datasets, AI algorithms could lead to unequal treatment recommendations or diagnoses, disproportionately affecting marginalized populations. It is imperative to address this issue to ensure equitable healthcare for all. To harness the benefits of AI in nursing while addressing potential pitfalls, a human-centric approach is paramount. Nurses must be involved in the design, development, and implementation of AI technologies to ensure that these tools align with their clinical expertise and patient-centered values. Training programs should be established to equip nurses with the skills necessary to work effectively alongside AI systems, promoting collaboration and shared decision-making [25–27]. Additionally, transparent guidelines and regulations must be established to govern the use of AI in nursing [28]. Ethical frameworks should be put in place to address issues such as data privacy, algorithmic bias, and patient consent [28]. Regular audits and assessments can help monitor the performance and impact of AI systems, ensuring that they uphold high standards of patient care. However, the adoption of new technologies also presents challenges. Nurses need to adapt and acquire digital literacy skills. It is important to ensure that the benefits of AI are distributed equitably among different nursing roles. As AI becomes more prevalent, nurses may transition into roles focused on managing and optimizing AI systems. Ongoing education and training are essential to equip the nursing workforce with the necessary skills and knowledge to fulfill these evolving responsibilities [26].

Ultimately, the incorporation of artificial intelligence (AI) into nursing and healthcare research offers both great potential and notable obstacles. The unquestionable advantages of AI lie in its ability to optimize healthcare workflows, enhance diagnostic accuracy, and improve patient engagement. Furthermore, in the realm of scholarly writing, AI has the potential to completely transform research procedures by expediting the process of discovery and fostering collaboration.

Nevertheless, these progressions are accompanied by significant drawbacks, such as apprehensions about the decline of personal interaction in patient care, ethical dilemmas with data privacy and algorithmic prejudice, and the peril of over dependence on AI systems. To successfully address these difficulties, it is necessary to adopt a considerate and human-focused strategy that gives priority to the well-being of patients and maintains ethical principles. Nurses and researchers should actively participate in the development, execution, and oversight of AI technologies, guaranteeing that these tools are in accordance with the fundamental principles of healthcare and academic honesty. Through the cultivation of collaboration, transparency, and accountability, we can effectively utilize the revolutionary capabilities of AI while ensuring the protection of the fundamental ideals of nursing and healthcare research. In order to fully harness the advantages of AI in enhancing patient care and knowledge discovery in nursing and healthcare, it is essential to prioritize responsible innovation and ethical stewardship.

## Ethical approval

The ethical approval was not required, as the study conducted did not involve any ethical concerns or issues.

## Funding

This article did not receive any financial support.

## Declaration of Competing Interest

The author declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Data Availability

No data were used in the research described in this article.

## Acknowledgement

Thanks to all the peer reviewers and editors for their opinions and suggestions and for their support of this research.

## Author contributions

The author was solely responsible for all of the work presented in this publication.

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Sirwan Khalid Ahmed<fnref n="1" />

Department of Adult Nursing, College Nursing, University of Raparin,
Rania, Sulaymaniyah, Kurdistan Region 46012, Iraq
E-mail address: sirwan.k.ahmed@gmail.com.

<footnote n="1">¹ https://orcid.org/0000-0002-8361-0546</footnote>