Name
Capella University
NURS-FPX 4040 Managing Health Information and Technology
Prof. Name
Date
This paper will review the application of Artificial Intelligence (AI) in healthcare, specifically nursing. AI is revolutionizing healthcare through embedded complicated data analysis, diagnosis, patient clinical deterioration prognosis, and recommended course of action (Varnosfaderani & Forouzanfar, 2024). The following annotated bibliography looks into peer-reviewed articles regarding the effects of AI on patient safety and quality of care, as well as its position within a healthcare team. In the last section of this paper, the work will summarize the study’s conclusion and recommendations that can be transcribed to integrate AI into nursing to enhance patient care and service delivery.
I chose AI for this assessment because of its positive impact on the healthcare industry, among them being the safety of patients, accuracy in diagnosis, and efficiency in operations. I chose the topic of AI in nursing because of the ability of AI to analyze big data and send information in real time to inform clinical decisions. I searched PubMed, CINAHL, and ProQuest Nursing and Allied Health databases for my research. The following search phrases used are: “AI in nursing,” “Artificial intelligence in patient care,” “Artificial intelligence in the safety of patients,” and “Artificial intelligence in healthcare quality enhancement.” It helped me find peer-reviewed articles discussing the role of AI in professional nursing and the collaboration of professions.
Abukhadijah, H. J., & Nashwan, A. J. (2024). Transforming hospital quality improvement through harnessing the power of artificial intelligence. Global Journal on Quality and Safety in Healthcare, 7(3), 132–139. https://doi.org/10.36401/jqsh-24-4
The authors have embraced the subject of how Artificial Intelligence can shape and advance the quality improvement agenda of hospitals. The authors comprehensively discuss the current AI applications and methods for improving operations, facilitating clinical decisions, and utilizing resources. The benefit of AI in enhancing patient safety and quality care by providing risk analysis for early detection, quality assurance, and minimizing preventable adverse events is described in the publication. The study highlights the importance of AI in nursing practice and experiences how the technology improves the organization’s healthcare processes and supports a multidisciplinary team in achieving quality improvement goals.
For example, AI-driven predictive analytics tools help nurses identify high-risk patients for hospital-acquired infections (HAIs) and implement timely interventions. Additionally, AI-powered scheduling systems optimize staffing, supporting multidisciplinary collaboration to enhance care quality and achieve organizational improvement goals. This resource was chosen as it provides the reader with practical tips on using AI technology to derive benefits and create safer conditions for patients by following actual achievements at the theoretical level.
Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A., Almohareb, S. N., Aldairem, A., Alrashed, M., Saleh, K. B., Badreldin, H. A., Yami, A., Harbi, S. A., & Albekairy, A. M. (2023). Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Medical Education, 23(1). https://doi.org/10.1186/s12909-023-04698-z
This article aims to expand on how artificial intelligence is beginning to revolutionize clinical practice in aspects of healthcare education and client care delivery. It gives a detailed insight into how AI augments clinical decision-making and improves diagnostic accuracy, operational efficiency and safety, and the dispositions of the patients. The public awareness raised by the publication focuses on the potential of AI in preventing avoidable errors in clinical practice, improving care delivery processes, and making care better and safer.
It also highlights the relevance of AI in nursing practice by fostering interdisciplinary collaboration and preparing healthcare teams for future challenges, such as managing complex patient conditions and addressing workforce shortages. By integrating AI tools, nurses and other healthcare professionals can enhance communication, streamline care coordination, and improve team efficiency, ensuring better patient outcomes. This article was chosen because of its richness in explaining AI and its various roles and usages. It includes potential implications for practical implementation into the educational environment of nursing practice and use by healthcare professionals.
Choudhury, A., & Asan, O. (2020). Role of artificial intelligence in patient safety outcomes: Systematic literature review. JMIR Medical Informatics, 8(7). https://doi.org/10.2196/18599
This systematic literature review explores the role of AI in improving patient safety performance indicators in different contexts. The publication thoroughly examines the means, ways, and extent to which AI applications, including predictive analytics, clinical decision support, and monitoring, minimize errors, enhance diagnosis accuracy, and enhance protocols for patient treatment. This work concludes that AI has the potential to improve patient safety by reducing human error, timely identification of clinical decline, and improving the quality of the decisions made in real-time.
This technology’s relevance in nursing practice involves assisting the nurses in providing accurate, timely, and patient-orientated care and enabling the nurse to create seamless synergy with the rest of the healthcare team. The usefulness of this particular employment of the resource was judged because it presents important perspectives on the practical application of AI solutions to decision-making in several key roles of health care provision. The value of such an employment of the resource manifested clearly to a practitioner seeking to apply a range of AI systems to promote patient safety and quality care.
Rony, M. K. K., Parvin, Mst. R., & Ferdousi, S. (2023). Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future. Nursing Open, 11(1). https://doi.org/10.1002/nop2.2070
The subject of this article is thus centered on the use of AI in the nursing practice while highlighting its application in enhancing preparedness in clinical practice and in managing clients. It outlines a brief guide on how the various AI tools can be applied to diagnose and determine accurate results, admission and timely intervention, and client care mapping. The study’s findings show that using AI has prospective performance gains in patient safety and quality diagnosis by minimizing care mistakes and using AI-supported inappropriate alternatives. Besides, it raises the significance of the profession, the role of AI in creating interdisciplinary, and the ability to address new challenges in healthcare. Of the available publications, the present one was chosen for its relevance, outlining AI’s luminous impact on nursing as a valuable source for healthcare practitioners willing to prepare for the future with technological integration.
The selected articles present properly researched how artificial intelligence (AI) improves patient safety, care quality, and interprofessional relations in the healthcare field. Abukhadijah and Nashwan (2024) discuss the strategic role of AI in enhancing the hospital’s quality and connecting it with the application for using prediction analysis in HAI. Also, for deploying AI scheduling systems that assemble practitioners’ schedules and help develop collaboration among multidisciplinary staff to enhance workflow and patient results. Alowais et al. (2023) emphasize decision support and error reduction, increasing diagnostic accuracy as AI’s opportunities for improving clinical practice, specifically for nursing and interprofessional teamwork, for managing complexity and workforce issues.
Choudhury and Asan (2020) conducted a systematic review of the use of AI to improve patient safety, and ways such as clinical decision support and predictive analytics that reduce human errors, and nurses can make real-time decisions to give accurate and patient-centric care while maintaining interdisciplinary collaboration. Uncertainty management in the context of preparing en masse nursing professionals to deal with future challenges, Rony et al. (2023) describe the tools for diagnosis, intervention, communication, and care mapping to reduce errors and augment patient outcomes. Moreover, it solidifies interdisciplinary teamwork to face emerging challenges within emerging healthcare. All these articles provide the reader with an understanding of implementing AI, its immediate effect on safety and quality, and how AI can help healthcare teams in their mission to provide top-notch care to people in need.
Several organizational considerations are key determinants to the choice of AI technologies in healthcare organizations, including the organization’s strategy of achieving greater patient safety, reduction of diagnostic error, and optimization of the delivery of care. An important issue is budgeting since implementing AI solutions often takes a lot of money to invest in software and hardware solutions. Another essential internal context is staff readiness because the introduction of AI implies the education of healthcare staff on the proper utilization of these tools (Ahmed et al., 2023).
Management approval is critical for the execution of an AI strategy and for a clear statement of objectives for the use of AI, including the general goals of enhancing the quality of health and efficiency. However, the current technological support and the availability of skilled personnel in organizations to manage and implement these systems are vital. They found that elements such as the organizational culture regarding AI and innovation adoption by the staff were determinative of the success of technology integration (Ahmed et al., 2023). All these factors should be addressed to ensure that AI technologies improve the healthcare organization’s performance, promote interdisciplinary teamwork, and ultimately improve patient outcomes.
AI is applied in various healthcare facilities to address Quality and Safe care delivery patterns, and there is enough rationale for AI. Smart technologies like predictive modeling and Clinical Decision Support for identifying patients with acute risk factors help avoid complications or events, including nosocomial infections or medication mishaps (Gala et al., 2024). More so, through significant analysis of patients’ information, AI helps make correct diagnoses and appropriate early interventions that would help better treat all patients. Not only this, but AI also reduces operational burdens in the form of time-consuming administrative work, scheduling, and staffing to guarantee better nurse-to-patient distribution ratios (Varnosfaderani & Forouzanfar, 2024). AI also reduces errors, improves patient care and formal decision-making procedures, and integrates patient care across specialties, leading to higher quality health care delivery and reduction of practicing environments.
In conclusion, integrating AI into nursing practice significantly improves patient safety, diagnostic accuracy, and care efficiency. Through predictive analytics and clinical decision support, AI enhances decision-making, reduces errors, and fosters interdisciplinary collaboration, ultimately leading to better patient outcomes. While successful implementation requires addressing organizational factors such as budget, staff readiness, and technological infrastructure, the long-term benefits of AI in improving healthcare delivery and enhancing the quality of care justify its adoption. With proper support and training, AI can revolutionize nursing and healthcare systems.
Abukhadijah, H. J., & Nashwan, A. J. (2024). Transforming hospital quality improvement through harnessing the power of artificial intelligence. Global Journal on Quality and Safety in Healthcare, 7(3), 132–139. https://doi.org/10.36401/jqsh-24-4
Ahmed, M. I., Spooner, B., Isherwood, J., Lane, M. A., Orrock, E., & Dennison, A. (2023). A systematic review of the barriers to the implementation of artificial intelligence in healthcare. Cureus, 15(10). https://doi.org/10.7759/cureus.46454
Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A., Almohareb, S. N., Aldairem, A., Alrashed, M., Saleh, K. B., Badreldin, H. A., Yami, A., Harbi, S. A., & Albekairy, A. M. (2023). Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Medical Education, 23(1). https://doi.org/10.1186/s12909-023-04698-z
Choudhury, A., & Asan, O. (2020). Role of artificial intelligence in patient safety outcomes: systematic literature review. JMIR Medical Informatics, 8(7). https://doi.org/10.2196/18599
Gala, D., Behl, H., Shah, M., & Makaryus, A. N. (2024). The role of artificial intelligence in improving patient outcomes and future of healthcare delivery in cardiology: A narrative review of the literature. Healthcare, 12(4), 481. https://doi.org/10.3390/healthcare12040481
Rony, M. K. K., Parvin, Mst. R., & Ferdousi, S. (2023). Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future. Nursing Open, 11(1). https://doi.org/10.1002/nop2.2070
Varnosfaderani, S. M., & Forouzanfar, M. (2024). The role of AI in hospitals and clinics: transforming healthcare in the 21st century. Bioengineering, 11(4), 337. https://doi.org/10.3390/bioengineering11040337
