Generative AI’s healthcare professional role creep: a cross-sectional evaluation of publicly accessible, customised health-related GPTs
IntroductionGenerative artificial intelligence (AI) is advancing rapidly; an important consideration is the public’s increasing ability to customise foundational AI models to create publicly accessible applications tailored for specific tasks. This study aims to evaluate the accessibility and functi...
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Frontiers Media S.A.
2025-05-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1584348/full |
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| author | Bianca Chu Natansh D. Modi Bradley D. Menz Stephen Bacchi Ganessan Kichenadasse Ganessan Kichenadasse Catherine Paterson Catherine Paterson Catherine Paterson Joshua G. Kovoor Joshua G. Kovoor Joshua G. Kovoor Imogen Ramsey Jessica M. Logan Michael D. Wiese Ross A. McKinnon Andrew Rowland Michael J. Sorich Ashley M. Hopkins |
| author_facet | Bianca Chu Natansh D. Modi Bradley D. Menz Stephen Bacchi Ganessan Kichenadasse Ganessan Kichenadasse Catherine Paterson Catherine Paterson Catherine Paterson Joshua G. Kovoor Joshua G. Kovoor Joshua G. Kovoor Imogen Ramsey Jessica M. Logan Michael D. Wiese Ross A. McKinnon Andrew Rowland Michael J. Sorich Ashley M. Hopkins |
| author_sort | Bianca Chu |
| collection | DOAJ |
| description | IntroductionGenerative artificial intelligence (AI) is advancing rapidly; an important consideration is the public’s increasing ability to customise foundational AI models to create publicly accessible applications tailored for specific tasks. This study aims to evaluate the accessibility and functionality descriptions of customised GPTs on the OpenAI GPT store that provide health-related information or assistance to patients and healthcare professionals.MethodsWe conducted a cross-sectional observational study of the OpenAI GPT store from September 2 to 6, 2024, to identify publicly accessible customised GPTs with health-related functions. We searched across general medicine, psychology, oncology, cardiology, and immunology applications. Identified GPTs were assessed for their name, description, intended audience, and usage. Regulatory status was checked across the U.S. Food and Drug Administration (FDA), European Union Medical Device Regulation (EU MDR), and Australian Therapeutic Goods Administration (TGA) databases.ResultsA total of 1,055 customised, health-related GPTs targeting patients and healthcare professionals were identified, which had collectively been used in over 360,000 conversations. Of these, 587 were psychology-related, 247 were in general medicine, 105 in oncology, 52 in cardiology, 30 in immunology, and 34 in other health specialties. Notably, 624 of the identified GPTs included healthcare professional titles (e.g., doctor, nurse, psychiatrist, oncologist) in their names and/or descriptions, suggesting they were taking on such roles. None of the customised GPTs identified were FDA, EU MDR, or TGA-approved.DiscussionThis study highlights the rapid emergence of publicly accessible, customised, health-related GPTs. The findings raise important questions about whether current AI medical device regulations are keeping pace with rapid technological advancements. The results also highlight the potential “role creep” in AI chatbots, where publicly accessible applications begin to perform — or claim to perform — functions traditionally reserved for licensed professionals, underscoring potential safety concerns. |
| format | Article |
| id | doaj-art-704179dcd1a74fbf85ea701233f7b6ee |
| institution | DOAJ |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj-art-704179dcd1a74fbf85ea701233f7b6ee2025-08-20T02:56:07ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-05-011310.3389/fpubh.2025.15843481584348Generative AI’s healthcare professional role creep: a cross-sectional evaluation of publicly accessible, customised health-related GPTsBianca Chu0Natansh D. Modi1Bradley D. Menz2Stephen Bacchi3Ganessan Kichenadasse4Ganessan Kichenadasse5Catherine Paterson6Catherine Paterson7Catherine Paterson8Joshua G. Kovoor9Joshua G. Kovoor10Joshua G. Kovoor11Imogen Ramsey12Jessica M. Logan13Michael D. Wiese14Ross A. McKinnon15Andrew Rowland16Michael J. Sorich17Ashley M. Hopkins18Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, AustraliaFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, AustraliaFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, AustraliaDepartment of Neurology and the Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United StatesFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, AustraliaFlinders Centre for Innovation in Cancer, Department of Medical Oncology, Flinders Medical Centre, Flinders University, Adelaide, SA, AustraliaCaring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, SA, AustraliaFaculty of Health, University of Canberra, Canberra, ACT, AustraliaCentral Adelaide Local Health Network, Adelaide, SA, AustraliaFaculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, AustraliaBallarat Base Hospital, Ballarat, VIC, AustraliaHealth and Information, Canberra, ACT, AustraliaCaring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, SA, Australia0Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia0Clinical and Health Sciences, University of South Australia, Adelaide, SA, AustraliaFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, AustraliaFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, AustraliaFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, AustraliaFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, AustraliaIntroductionGenerative artificial intelligence (AI) is advancing rapidly; an important consideration is the public’s increasing ability to customise foundational AI models to create publicly accessible applications tailored for specific tasks. This study aims to evaluate the accessibility and functionality descriptions of customised GPTs on the OpenAI GPT store that provide health-related information or assistance to patients and healthcare professionals.MethodsWe conducted a cross-sectional observational study of the OpenAI GPT store from September 2 to 6, 2024, to identify publicly accessible customised GPTs with health-related functions. We searched across general medicine, psychology, oncology, cardiology, and immunology applications. Identified GPTs were assessed for their name, description, intended audience, and usage. Regulatory status was checked across the U.S. Food and Drug Administration (FDA), European Union Medical Device Regulation (EU MDR), and Australian Therapeutic Goods Administration (TGA) databases.ResultsA total of 1,055 customised, health-related GPTs targeting patients and healthcare professionals were identified, which had collectively been used in over 360,000 conversations. Of these, 587 were psychology-related, 247 were in general medicine, 105 in oncology, 52 in cardiology, 30 in immunology, and 34 in other health specialties. Notably, 624 of the identified GPTs included healthcare professional titles (e.g., doctor, nurse, psychiatrist, oncologist) in their names and/or descriptions, suggesting they were taking on such roles. None of the customised GPTs identified were FDA, EU MDR, or TGA-approved.DiscussionThis study highlights the rapid emergence of publicly accessible, customised, health-related GPTs. The findings raise important questions about whether current AI medical device regulations are keeping pace with rapid technological advancements. The results also highlight the potential “role creep” in AI chatbots, where publicly accessible applications begin to perform — or claim to perform — functions traditionally reserved for licensed professionals, underscoring potential safety concerns.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1584348/fullcustomised GPTsGenerative AI in healthcareAI health applicationsmedical chatbotsAI regulationOpenAI GPT store |
| spellingShingle | Bianca Chu Natansh D. Modi Bradley D. Menz Stephen Bacchi Ganessan Kichenadasse Ganessan Kichenadasse Catherine Paterson Catherine Paterson Catherine Paterson Joshua G. Kovoor Joshua G. Kovoor Joshua G. Kovoor Imogen Ramsey Jessica M. Logan Michael D. Wiese Ross A. McKinnon Andrew Rowland Michael J. Sorich Ashley M. Hopkins Generative AI’s healthcare professional role creep: a cross-sectional evaluation of publicly accessible, customised health-related GPTs Frontiers in Public Health customised GPTs Generative AI in healthcare AI health applications medical chatbots AI regulation OpenAI GPT store |
| title | Generative AI’s healthcare professional role creep: a cross-sectional evaluation of publicly accessible, customised health-related GPTs |
| title_full | Generative AI’s healthcare professional role creep: a cross-sectional evaluation of publicly accessible, customised health-related GPTs |
| title_fullStr | Generative AI’s healthcare professional role creep: a cross-sectional evaluation of publicly accessible, customised health-related GPTs |
| title_full_unstemmed | Generative AI’s healthcare professional role creep: a cross-sectional evaluation of publicly accessible, customised health-related GPTs |
| title_short | Generative AI’s healthcare professional role creep: a cross-sectional evaluation of publicly accessible, customised health-related GPTs |
| title_sort | generative ai s healthcare professional role creep a cross sectional evaluation of publicly accessible customised health related gpts |
| topic | customised GPTs Generative AI in healthcare AI health applications medical chatbots AI regulation OpenAI GPT store |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1584348/full |
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