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Assessing the utility of artificial intelligence throughout the triage outpatients: a prospective randomized controlled clinical study
Currently, there are still many patients who require outpatient triage assistance. ChatGPT, a natural language processing tool powered by artificial intelligence technology, is increasingly utilized in medicine. To facilitate and expedite patients' navigation to the appropriate department, we c...
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Published in: | Frontiers in public health 2024-05, Vol.12, p.1391906 |
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creator | Liu, Xiaoni Lai, Rui Wu, Chaoling Yan, Changjian Gan, Zhe Yang, Yaru Zeng, Xiangtai Liu, Jin Liao, Liangliang Lin, Yuansheng Jing, Hongmei Zhang, Weilong |
description | Currently, there are still many patients who require outpatient triage assistance. ChatGPT, a natural language processing tool powered by artificial intelligence technology, is increasingly utilized in medicine. To facilitate and expedite patients' navigation to the appropriate department, we conducted an outpatient triage evaluation of ChatGPT. For this evaluation, we posed 30 highly representative and common outpatient questions to ChatGPT and scored its responses using a panel of five experienced doctors. The consistency of manual triage and ChatGPT triage was assessed by five experienced doctors, and statistical analysis was performed using the Chi-square test. The expert ratings of ChatGPT's answers to these 30 frequently asked questions revealed 17 responses earning very high scores (10 and 9.5 points), 7 earning high scores (9 points), and 6 receiving low scores (8 and 7 points). Additionally, we conducted a prospective cohort study in which 45 patients completed forms detailing gender, age, and symptoms. Triage was then performed by outpatient triage staff and ChatGPT. Among the 45 patients, we found a high level of agreement between manual triage and ChatGPT triage (consistency: 93.3-100%, |
doi_str_mv | 10.3389/fpubh.2024.1391906 |
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<0.0001). We were pleasantly surprised to observe that ChatGPT's responses were highly professional, comprehensive, and humanized. This innovation can help patients win more treatment time, improve patient diagnosis and cure rates, and alleviate the pressure of medical staff shortage.</description><identifier>ISSN: 2296-2565</identifier><identifier>EISSN: 2296-2565</identifier><identifier>DOI: 10.3389/fpubh.2024.1391906</identifier><identifier>PMID: 38873307</identifier><language>eng</language><publisher>Switzerland: Frontiers Media S.A</publisher><subject>Adult ; Aged ; Artificial Intelligence ; ChatGPT ; Female ; Humans ; Male ; Middle Aged ; Natural Language Processing ; Outpatients - statistics & numerical data ; Prospective Studies ; Public Health ; Triage ; triage outpatients</subject><ispartof>Frontiers in public health, 2024-05, Vol.12, p.1391906</ispartof><rights>Copyright © 2024 Liu, Lai, Wu, Yan, Gan, Yang, Zeng, Liu, Liao, Lin, Jing and Zhang.</rights><rights>Copyright © 2024 Liu, Lai, Wu, Yan, Gan, Yang, Zeng, Liu, Liao, Lin, Jing and Zhang. 2024 Liu, Lai, Wu, Yan, Gan, Yang, Zeng, Liu, Liao, Lin, Jing and Zhang</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c350t-3ebda96d2f6ab80e4e78694135ae598bb0c255649dceb1d625a17c67e7314403</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11171710/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11171710/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38873307$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liu, Xiaoni</creatorcontrib><creatorcontrib>Lai, Rui</creatorcontrib><creatorcontrib>Wu, Chaoling</creatorcontrib><creatorcontrib>Yan, Changjian</creatorcontrib><creatorcontrib>Gan, Zhe</creatorcontrib><creatorcontrib>Yang, Yaru</creatorcontrib><creatorcontrib>Zeng, Xiangtai</creatorcontrib><creatorcontrib>Liu, Jin</creatorcontrib><creatorcontrib>Liao, Liangliang</creatorcontrib><creatorcontrib>Lin, Yuansheng</creatorcontrib><creatorcontrib>Jing, Hongmei</creatorcontrib><creatorcontrib>Zhang, Weilong</creatorcontrib><title>Assessing the utility of artificial intelligence throughout the triage outpatients: a prospective randomized controlled clinical study</title><title>Frontiers in public health</title><addtitle>Front Public Health</addtitle><description>Currently, there are still many patients who require outpatient triage assistance. ChatGPT, a natural language processing tool powered by artificial intelligence technology, is increasingly utilized in medicine. To facilitate and expedite patients' navigation to the appropriate department, we conducted an outpatient triage evaluation of ChatGPT. For this evaluation, we posed 30 highly representative and common outpatient questions to ChatGPT and scored its responses using a panel of five experienced doctors. The consistency of manual triage and ChatGPT triage was assessed by five experienced doctors, and statistical analysis was performed using the Chi-square test. The expert ratings of ChatGPT's answers to these 30 frequently asked questions revealed 17 responses earning very high scores (10 and 9.5 points), 7 earning high scores (9 points), and 6 receiving low scores (8 and 7 points). Additionally, we conducted a prospective cohort study in which 45 patients completed forms detailing gender, age, and symptoms. Triage was then performed by outpatient triage staff and ChatGPT. Among the 45 patients, we found a high level of agreement between manual triage and ChatGPT triage (consistency: 93.3-100%,
<0.0001). We were pleasantly surprised to observe that ChatGPT's responses were highly professional, comprehensive, and humanized. This innovation can help patients win more treatment time, improve patient diagnosis and cure rates, and alleviate the pressure of medical staff shortage.</description><subject>Adult</subject><subject>Aged</subject><subject>Artificial Intelligence</subject><subject>ChatGPT</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Natural Language Processing</subject><subject>Outpatients - statistics & numerical data</subject><subject>Prospective Studies</subject><subject>Public Health</subject><subject>Triage</subject><subject>triage outpatients</subject><issn>2296-2565</issn><issn>2296-2565</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVUstu3CAUtapWTZTmB7qoWHYzEx4GTDdVFPURKVI22SMM1x4ixkwBR5p-QL67eGYaJWLBvXDPua_TNJ8JXjPWqathN_ebNcW0XROmiMLiXXNOqRIrygV__8o-ay5zfsQYE8xaTMnH5ox1nWQMy_Pm-TpnyNlPIyobQHPxwZc9igMyqfjBW28C8lOBEPwIk4UaluI8buJcDoiSvBkBVXdnioep5G_IoF2KeQe2-CdAyUwubv1fcMjGqaQYwmIGP3lbyXOZ3f5T82EwIcPl6b5oHn7-eLj5vbq7_3V7c323sozjsmLQO6OEo4MwfYehBdkJ1RLGDXDV9T22lHPRKmehJ05Qboi0QoJkpG0xu2huj7Qumke9S35r0l5H4_XhIaZRL23bANpxNlBFbeeGthXOdqpj1losueyJ5X3l-n7kqovYQk1YWzPhDenbn8lv9BifNCFE1rNU8_XEkOKfGXLRW59tnbSZIM5ZMyw6yQVWSyg9hto62JxgeMlDsF70oA960Ise9EkPFfTldYUvkP_bZ_8AhCC27g</recordid><startdate>20240530</startdate><enddate>20240530</enddate><creator>Liu, Xiaoni</creator><creator>Lai, Rui</creator><creator>Wu, Chaoling</creator><creator>Yan, Changjian</creator><creator>Gan, Zhe</creator><creator>Yang, Yaru</creator><creator>Zeng, Xiangtai</creator><creator>Liu, Jin</creator><creator>Liao, Liangliang</creator><creator>Lin, Yuansheng</creator><creator>Jing, Hongmei</creator><creator>Zhang, Weilong</creator><general>Frontiers Media S.A</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20240530</creationdate><title>Assessing the utility of artificial intelligence throughout the triage outpatients: a prospective randomized controlled clinical study</title><author>Liu, Xiaoni ; Lai, Rui ; Wu, Chaoling ; Yan, Changjian ; Gan, Zhe ; Yang, Yaru ; Zeng, Xiangtai ; Liu, Jin ; Liao, Liangliang ; Lin, Yuansheng ; Jing, Hongmei ; Zhang, Weilong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c350t-3ebda96d2f6ab80e4e78694135ae598bb0c255649dceb1d625a17c67e7314403</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Artificial Intelligence</topic><topic>ChatGPT</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Natural Language Processing</topic><topic>Outpatients - statistics & numerical data</topic><topic>Prospective Studies</topic><topic>Public Health</topic><topic>Triage</topic><topic>triage outpatients</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Xiaoni</creatorcontrib><creatorcontrib>Lai, Rui</creatorcontrib><creatorcontrib>Wu, Chaoling</creatorcontrib><creatorcontrib>Yan, Changjian</creatorcontrib><creatorcontrib>Gan, Zhe</creatorcontrib><creatorcontrib>Yang, Yaru</creatorcontrib><creatorcontrib>Zeng, Xiangtai</creatorcontrib><creatorcontrib>Liu, Jin</creatorcontrib><creatorcontrib>Liao, Liangliang</creatorcontrib><creatorcontrib>Lin, Yuansheng</creatorcontrib><creatorcontrib>Jing, Hongmei</creatorcontrib><creatorcontrib>Zhang, Weilong</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Frontiers in public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Xiaoni</au><au>Lai, Rui</au><au>Wu, Chaoling</au><au>Yan, Changjian</au><au>Gan, Zhe</au><au>Yang, Yaru</au><au>Zeng, Xiangtai</au><au>Liu, Jin</au><au>Liao, Liangliang</au><au>Lin, Yuansheng</au><au>Jing, Hongmei</au><au>Zhang, Weilong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing the utility of artificial intelligence throughout the triage outpatients: a prospective randomized controlled clinical study</atitle><jtitle>Frontiers in public health</jtitle><addtitle>Front Public Health</addtitle><date>2024-05-30</date><risdate>2024</risdate><volume>12</volume><spage>1391906</spage><pages>1391906-</pages><issn>2296-2565</issn><eissn>2296-2565</eissn><abstract>Currently, there are still many patients who require outpatient triage assistance. ChatGPT, a natural language processing tool powered by artificial intelligence technology, is increasingly utilized in medicine. To facilitate and expedite patients' navigation to the appropriate department, we conducted an outpatient triage evaluation of ChatGPT. For this evaluation, we posed 30 highly representative and common outpatient questions to ChatGPT and scored its responses using a panel of five experienced doctors. The consistency of manual triage and ChatGPT triage was assessed by five experienced doctors, and statistical analysis was performed using the Chi-square test. The expert ratings of ChatGPT's answers to these 30 frequently asked questions revealed 17 responses earning very high scores (10 and 9.5 points), 7 earning high scores (9 points), and 6 receiving low scores (8 and 7 points). Additionally, we conducted a prospective cohort study in which 45 patients completed forms detailing gender, age, and symptoms. Triage was then performed by outpatient triage staff and ChatGPT. Among the 45 patients, we found a high level of agreement between manual triage and ChatGPT triage (consistency: 93.3-100%,
<0.0001). We were pleasantly surprised to observe that ChatGPT's responses were highly professional, comprehensive, and humanized. This innovation can help patients win more treatment time, improve patient diagnosis and cure rates, and alleviate the pressure of medical staff shortage.</abstract><cop>Switzerland</cop><pub>Frontiers Media S.A</pub><pmid>38873307</pmid><doi>10.3389/fpubh.2024.1391906</doi><oa>free_for_read</oa></addata></record> |
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subjects | Adult Aged Artificial Intelligence ChatGPT Female Humans Male Middle Aged Natural Language Processing Outpatients - statistics & numerical data Prospective Studies Public Health Triage triage outpatients |
title | Assessing the utility of artificial intelligence throughout the triage outpatients: a prospective randomized controlled clinical study |
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