Research on the Application of Generative AI in Nursing Documentation

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Biotechnology Frontier (Yearly) is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of biotechnology technology. The main focus of the journal is the academic papers, comments and research review of latest improvement in the fields of Biotechnology technology, microorganism, medicine, agriculture & forestry, edible fungus, light food, environmental protection and related, aiming at... [More] Biotechnology Frontier (Yearly) is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of biotechnology technology. The main focus of the journal is the academic papers, comments and research review of latest improvement in the fields of Biotechnology technology, microorganism, medicine, agriculture & forestry, edible fungus, light food, environmental protection and related, aiming at providing a good communication platform to transfer, share and discuss the theoretical and technical development of electrical theory development for professionals, scholars, researchers and administrative staffs in this field, reflecting the academic front level, promote academic change and foster the development of biotechnology technology.

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Paper Infomation

Research on the Application of Generative AI in Nursing Documentation

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Author: Xiaofen Wang, Qiong Ni, Shenhui Wu

Abstract: In nursing practice, electronic nursing records (ENRs) are an important component of patient care documents, but they also significantly increase administrative burdens. With the development of artificial intelligence technology, it has become possible to use large text models to assist in generating nursing documents. This article explores the application of generative AI in nursing documentation. Research has shown that the application of generative AI in nursing documents demonstrates significant potential, but also faces challenges in terms of quality and implementation. In terms of efficiency, AI assisted document tools can significantly reduce the administrative burden on nurses by reallocating time to direct patient care. Studies have shown that they can reduce document time by 21-30%. However, there are variables in the quality of AI generated records, and the content is often described as 'textbook style', lacking patient specific details and appropriate medical terminology. Successful implementation relies on a specialized framework that includes strong stakeholder engagement and adaptation to nursing specific workflows and regulatory standards. The conclusion points out that current AI systems are most suitable for assisting in drafting nursing documents, and clinical validation remains crucial for patient safety and document integrity.

Keywords: Artificial Intelligence; Electronic Nursing Records; Nursing Documentation; Framework

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