Artificial Intelligence and Nursing Care: Revolutionizing Patient Diagnosis and Treatment Strategies: Most Recent Literature Review Based Study

Abstract

Background: Introduction of Artificial Intelligence (AI) into nursing care opens many opportunities to assist in patient diagnosis, treatment strategies and in general in health care provision. With continued evolution of AI technologies, they hold solutions to enhance the nursing workflow, decrease diagnostic errors, and increase patient safety. However, in healthcare settings these technologies have yet to be widely adopted, thanks to Data privacy challenges, related ethical concerns, and lack of training.
Aim: In this systematic review, we investigate how AI can be integrated into nursing care to improve patient diagnosis and treatment and identify existing barriers to its adoption. This study reviews AI technologies used to enhance nursing efficiency and patients’ outcomes, and develops proposals to overcome the concerns of ethics, data privacy and training requirements.
Method: A search of literature published between 2020-2024 was performed focusing on databases such as PubMed, Google Scholar, ScienceDirect, IEEE Xplore, and CINAHL. A total of 711 studies were identified, 10 of which fulfilled the selection criteria. Through an analysis of these studies, we were able to identify themes concerning an AI enhanced diagnostic, workflow optimization, clinical decision support, patient safety and ethical issues.
Results: Key themes were identified from the research and included AI influence on diagnostic accuracy, workflow automation, clinical decision making, and patient safety. Using AI systems were found enable more precise diagnosis, decrease nursing workload, and help set personalized treatment plans. We observe, however, that there are many challenges, such as data privacy and algorithmic biases, and the need for training of the healthcare professional, which need to be overcome to ensure success in the adoption of EMRs. The results underline the need for standard frameworks and structured training programs for sound integration of AI in nursing.
Conclusion: AI can be integrated into nursing and has the potential to transform patient care by improving diagnostics, optimizing of workflows and increasing patient outcomes. But these benefits cannot be fully realized until ethical issues, data confidentiality and ongoing training become challenges. Setting up a framework for the ethical and effective use of AI in nursing would require a collaborative effort of healthcare providers, technology developers, and policymakers.