Can artificial intelligence help ED nurses more accurately triage patients?

Q3 Nursing

Nursing Pub Date : 2024-06-01 Epub Date: 2024-05-17 DOI:10.1097/NSG.0000000000000019

Melinda Regan

引用次数: 0

Abstract

Abstract: The Emergency Severity Index (ESI) is the most popular tool used to triage patients in the US and abroad. Evidence has shown that ESI has its limitations in correctly assigning acuity. To address this, AI can be incorporated into the triage process, decreasing the likelihood of assigning an incorrect ESI level.

查看原文本刊更多论文

人工智能能否帮助急诊室护士更准确地分流病人？

摘要：在美国和国外，急诊严重程度指数（ESI）是用于分流病人的最常用工具。有证据表明，ESI 在正确分配严重程度方面有其局限性。为解决这一问题，可将人工智能纳入分诊流程，从而降低分配错误 ESI 等级的可能性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Nursing Medicine-Medicine (all)

CiteScore

0.80

自引率

0.00%

发文量

338

期刊介绍： Nursing2020 (ISSN 0360-4039; online ISSN 1538-8689) published its first issue in November 1971, under founders Gene W. Jackson and Daniel Cheney. In the intervening years, its circulation has grown to over 150,000, making it one of the largest nursing journals in the world. Published monthly, Nursing2020 is widely regarded as offering current, practical contents to its readers, and has won many editorial awards testifying to the quality of its copy and graphics. The editorial and clinical staff, a 19-member Editorial Board of distinguished clinicians and practitioners, and over 100 invited reviewers help ensure the quality of this publication.