Performance of ChatGPT on basic healthcare leadership and management questions

Author:

Leutz-Schmidt Patricia,Grözinger Martin,Kauczor Hans-Ulrich,Jang Hyungseok,Sedaghat SamORCID

Abstract

Abstract Purpose ChatGPT is an LLM-based chatbot introduced in 2022. This study investigates the performance of ChatGPT-3.5 and ChatGPT-4 on basic healthcare leadership and management questions. Methods ChatGPT-3.5 and -4 (OpenAI, San Francisco, CA, USA) generated answers to 24 pre-selected questions on three different areas of management and leadership in medical practice: group 1) accessing management/leadership training, group 2) management/leadership basics, group 3) department management/leadership. Three readers independently evaluated the answers provided by the two versions of ChatGPT. Three 4-digit scores were developed to assess the quality of the responses: 1) overall quality score (OQS), 2) understandibility score (US), and 3) implementability score (IS). The mean quality score (MQS) was calculated from these three scores. Results The interrater agreement was good for ChatGPT-4 (72%) and moderate for ChatGPT-3.5 (56%). The MQS of all questions reached a mean score of 3,42 (SD: 0,64) using ChatGPT-3.5 and 3,75 (SD: 0,47) using ChatGPT-4. ChatGPT-4 showed significantly higher MQS scores in group 2 and 3 questions than ChatGPT-3.5 (p = 0.039 and p < 0.001, respectively). Also, significant differences between ChatGPT-3.5 and ChatGPT-4 regarding OQS, US, and IS in group 3 questions were seen with significances reaching p < 0.001. Significant differences between the two chatbot versions were also present regarding OQS in question groups 1 and 2 (p = 0.035 each). 87.5% of the answers provided by ChatGPT-4 (21 of 24 answers) were considered superior to the answers provided by ChatGPT-3.5 for the same questions. Neither ChatGPT-3.5 nor ChatGPT-4 offered any inaccurate answers. Conclusion ChatGPT-3.5 and ChatGPT-4 performed well on basic healthcare leadership and management questions, while ChatGPT-4 was superior.

Funder

Universitätsklinikum Heidelberg

Publisher

Springer Science and Business Media LLC

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