Aug 2026· Clinical nurse specialist CNS· Vol 40 5, pp.
193-199
· 0 citations· 21 references
Medicine
TL;DR
GenAI is a useful tool supporting the workflow of clinical nurse specialists in all practice settings and can build stronger nursing and healthcare systems resources and optimize patient outcomes.
Abstract
PURPOSE/
Objectives
Generative artificial intelligence (GenAI), as a new technology and innovation in practice, is here. The purpose of this paper is to introduce general principles for using GenAI to enhance the workflow of the clinical nurse specialist.
DESCRIPTION
This technology is rapidly advancing and influencing practice, education, communication, and workflow for nurses and clinical nurse specialists. Understanding how to optimize GenAI, including developing strong prompts to improve outputs, is shared.
OUTCOME
A hypothetical example of a clinical error is used to demonstrate ways in which GenAI can be used to search the literature, create a Situation, Background, Assessment, and Recommendation (SBAR) document and a competency tool is presented.
Conclusions
GenAI is a useful tool supporting the workflow of clinical nurse specialists in all practice settings. Understanding the nuances of using AI inclusive of the importance of human, expert oversight by the clinical nurse specialist, can build stronger nursing and healthcare systems resources and optimize patient outcomes.
The evidence indicates that AI can improve risk stratification, early recognition of clinical deterioration, medication-safety processes, documentation quality, and access to simulation-based education, and support a human-in-the-loop model in which AI augments rather than replaces nursing judgment.
Heloísa de Oliveira Nascimento· Nexus Science Review· 0 citations
Artificial intelligence (AI) is rapidly transforming healthcare delivery and nursing education by supporting clinical decision-making, documentation, risk prediction, personalized learning, simulation, assessment, and administrative processes. The increasing availability of generative AI and large language models has f...
Natasha Mohit Mahajan· International Journal of Nur...· 0 citations
AIM
Artificial intelligence (AI) is reshaping healthcare delivery. This work aims to explore how nursing expertise can be fully integrated into the development of AI-based health technologies and to assess the implications for clinical practice, education, leadership, industry, policy and research.
METHODS
This quali...
Laura-Maria Peltonen, Maxim Topaz, Martin Michalowski et al.· Journal of Advanced Nursing· 0 citations
Background: Artificial intelligence-based clinical decision support systems (AI-CDSS) are increasingly used in healthcare to support data-informed clinical decisions. In nursing practice, these systems may assist with risk assessment, medication safety, early recognition of patient deterioration, documentation, and car...
I. M, Bamigboye T. O., Oniyide A. A.· International journal of re...· 0 citations
AI delivers its greatest value when deployed as a collaborative instrument that augments rather than replaces clinical judgment, which depends on sustained investment in digital literacy, explainable systems, clinician involvement in design, and equitable institutional infrastructure.
A. Bociąg, Łukasz Ptach, Rafał Marciniak et al.· International Journal of Inn...· 0 citations
Artificial intelligence (AI) is moving from experimental research into routine healthcare workflows, including diagnostic support, clinical documentation, rehabilitation, laboratory medicine, medical imaging, patient education, and service management. Allied health professionals are increasingly involved in these AI-en...
Sakthivel Ramya, Ragul Baskaran, Loganayaki Somasundaram· International Journal of Cur...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
