Evaluating the Quality of Postpartum Hemorrhage Nursing Care Plans Generated by Artificial Intelligence Models

Author:

Karacan Emine1

Affiliation:

1. Author Affiliations:Dortyol Vocational School of Health Services, Iskenderun Technical University, Hatay, Turkey.

Abstract

Background: With the rapidly advancing technological landscape of health care, evaluating the potential use of artificial intelligence (AI) models to prepare nursing care plans is of great importance. Purpose: The purpose of this study was to evaluate the quality of nursing care plans created by AI for the management of postpartum hemorrhage (PPH). Methods: This cross-sectional exploratory study involved creating a scenario for an imaginary patient with PPH. Information was put into 3 AI platforms (GPT-4, LaMDA, Med-PaLM) on consecutive days without prior conversation. Care plans were evaluated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) scale. Results: Med-PaLM exhibited superior quality in developing the care plan compared with LaMDA (Z = 4.354; P = .000) and GPT-4 (Z = 3.126; P = .029). Conclusions: Our findings suggest that despite the strong performance of Med-PaLM, AI, in its current state, is unsuitable for use with real patients.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Reference34 articles.

1. Effects of a simulation-based nursing process educational program: a mixed-methods study;Chang;Nurse Educ Pract,2021

2. Application scenarios for artificial intelligence in nursing care: rapid review;Seibert;J Med Internet Res,2021

3. Applications of artificial intelligence in nursing care: a systematic review;Martinez Ortigosa;J Nurs Manag,2023

4. Research trends in artificial intelligence associated nursing activities based on a review of academic studies published from 2001 to 2020;Hwang;Comput Inform Nurs,2022

5. Artificial intelligence in nursing and midwifery: a systematic review;O’Connor;J Clin Nurs,2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3