Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale

Background Artificial intelligence (AI) technology can enable more efficient decision-making in healthcare settings. There is a growing interest in improving the speed and accuracy of AI systems in providing responses for given tasks in healthcare settings. Objective This study aimed to assess the r...

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Main Authors: Jae Hyuk Kim, Sun Kyung Kim, Jongmyung Choi, Youngho Lee
Format: Article
Language:English
Published: SAGE Publishing 2024-01-01
Series:Digital Health
Online Access:https://doi.org/10.1177/20552076241227132
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author Jae Hyuk Kim
Sun Kyung Kim
Jongmyung Choi
Youngho Lee
author_facet Jae Hyuk Kim
Sun Kyung Kim
Jongmyung Choi
Youngho Lee
author_sort Jae Hyuk Kim
collection DOAJ
description Background Artificial intelligence (AI) technology can enable more efficient decision-making in healthcare settings. There is a growing interest in improving the speed and accuracy of AI systems in providing responses for given tasks in healthcare settings. Objective This study aimed to assess the reliability of ChatGPT in determining emergency department (ED) triage accuracy using the Korean Triage and Acuity Scale (KTAS). Methods Two hundred and two virtual patient cases were built. The gold standard triage classification for each case was established by an experienced ED physician. Three other human raters (ED paramedics) were involved and rated the virtual cases individually. The virtual cases were also rated by two different versions of the chat generative pre-trained transformer (ChatGPT, 3.5 and 4.0). Inter-rater reliability was examined using Fleiss’ kappa and intra-class correlation coefficient (ICC). Results The kappa values for the agreement between the four human raters and ChatGPTs were .523 (version 4.0) and .320 (version 3.5). Of the five levels, the performance was poor when rating patients at levels 1 and 5, as well as case scenarios with additional text descriptions. There were differences in the accuracy of the different versions of GPTs. The ICC between version 3.5 and the gold standard was .520, and that between version 4.0 and the gold standard was .802. Conclusions A substantial level of inter-rater reliability was revealed when GPTs were used as KTAS raters. The current study showed the potential of using GPT in emergency healthcare settings. Considering the shortage of experienced manpower, this AI method may help improve triaging accuracy.
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spelling doaj.art-cdf977b282664244b1393622b46d32d12024-01-19T20:06:08ZengSAGE PublishingDigital Health2055-20762024-01-011010.1177/20552076241227132Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity ScaleJae Hyuk Kim0Sun Kyung Kim1Jongmyung Choi2Youngho Lee3 Department of Emergency Medicine, Mokpo Hankook Hospital, Jeonnam, South Korea Department of Biomedicine, Health & Life Convergence Sciences, Biomedical and Healthcare Research Institute, Jeonnam, South Korea Department of Computer Engineering, , Jeonnam, South Korea Department of Computer Engineering, , Jeonnam, South KoreaBackground Artificial intelligence (AI) technology can enable more efficient decision-making in healthcare settings. There is a growing interest in improving the speed and accuracy of AI systems in providing responses for given tasks in healthcare settings. Objective This study aimed to assess the reliability of ChatGPT in determining emergency department (ED) triage accuracy using the Korean Triage and Acuity Scale (KTAS). Methods Two hundred and two virtual patient cases were built. The gold standard triage classification for each case was established by an experienced ED physician. Three other human raters (ED paramedics) were involved and rated the virtual cases individually. The virtual cases were also rated by two different versions of the chat generative pre-trained transformer (ChatGPT, 3.5 and 4.0). Inter-rater reliability was examined using Fleiss’ kappa and intra-class correlation coefficient (ICC). Results The kappa values for the agreement between the four human raters and ChatGPTs were .523 (version 4.0) and .320 (version 3.5). Of the five levels, the performance was poor when rating patients at levels 1 and 5, as well as case scenarios with additional text descriptions. There were differences in the accuracy of the different versions of GPTs. The ICC between version 3.5 and the gold standard was .520, and that between version 4.0 and the gold standard was .802. Conclusions A substantial level of inter-rater reliability was revealed when GPTs were used as KTAS raters. The current study showed the potential of using GPT in emergency healthcare settings. Considering the shortage of experienced manpower, this AI method may help improve triaging accuracy.https://doi.org/10.1177/20552076241227132
spellingShingle Jae Hyuk Kim
Sun Kyung Kim
Jongmyung Choi
Youngho Lee
Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale
Digital Health
title Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale
title_full Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale
title_fullStr Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale
title_full_unstemmed Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale
title_short Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale
title_sort reliability of chatgpt for performing triage task in the emergency department using the korean triage and acuity scale
url https://doi.org/10.1177/20552076241227132
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