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 tech...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.展开更多
Background: In situations of care transfer of older people from hospital to home care at discharge, exchanging relevant and necessary information about the patient’s health status and individual needs are of importan...Background: In situations of care transfer of older people from hospital to home care at discharge, exchanging relevant and necessary information about the patient’s health status and individual needs are of importance to ensure continuity and appropriate nursing follow-up care. Objective: The objectives of the study were to: 1) examine the content of nurses’ discharge notes of older patients’ discharged from hospital to home care, and 2) investigate the association between the content of discharge notes and characteristics of patient and transfer. Methods: The nursing discharge notes of 70 older patients admitted to a geriatric unit and a general medicine ward at a local hospital in central Norway were analysed. The discharge notes were structured in accordance with the Well-being, Integrity, Prevention, and Safety (VIPS) model. Mean, standard deviations, and independent sample t-tests were performed to show and examine differences in use of VIPS keywords in relation to patient and transfer characteristics. To examine if use of VIPS keywords could be predicted by patient and transfer characteristics, linear multiple regression analyses were used. Results: Significant differences for mean scores on used VIPS keywords in the discharge note were found for gender, age, and medical department facility. While gender and medical department facility were significant predictors of mental related keywords in the discharge note, medical department facility was a significant predictor of physical related keywords. Conclusions: The result of this study indicate that documentation of patient status in the nursing discharge note of older patients transferred from hospital to home care is incomplete and are influenced by patient and transfer characteristics. In order to ensure continuity and appropriate nursing follow-up care, we emphasize the need for a more comprehensive approach to older patients, and that this must be reflected in the nursing discharge note.展开更多
基金supported by the Tightly Integrated Health Consortium Research Project(Grant ynlglht202412)。
文摘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.
文摘Background: In situations of care transfer of older people from hospital to home care at discharge, exchanging relevant and necessary information about the patient’s health status and individual needs are of importance to ensure continuity and appropriate nursing follow-up care. Objective: The objectives of the study were to: 1) examine the content of nurses’ discharge notes of older patients’ discharged from hospital to home care, and 2) investigate the association between the content of discharge notes and characteristics of patient and transfer. Methods: The nursing discharge notes of 70 older patients admitted to a geriatric unit and a general medicine ward at a local hospital in central Norway were analysed. The discharge notes were structured in accordance with the Well-being, Integrity, Prevention, and Safety (VIPS) model. Mean, standard deviations, and independent sample t-tests were performed to show and examine differences in use of VIPS keywords in relation to patient and transfer characteristics. To examine if use of VIPS keywords could be predicted by patient and transfer characteristics, linear multiple regression analyses were used. Results: Significant differences for mean scores on used VIPS keywords in the discharge note were found for gender, age, and medical department facility. While gender and medical department facility were significant predictors of mental related keywords in the discharge note, medical department facility was a significant predictor of physical related keywords. Conclusions: The result of this study indicate that documentation of patient status in the nursing discharge note of older patients transferred from hospital to home care is incomplete and are influenced by patient and transfer characteristics. In order to ensure continuity and appropriate nursing follow-up care, we emphasize the need for a more comprehensive approach to older patients, and that this must be reflected in the nursing discharge note.
