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Generative AI’s healthcare professional role creep

A cross-sectional evaluation of publicly accessible, customised health-related GPTs

Bibliographic Data

ID22074457
AuthorsBianca Chu (Flinders University), Natansh D Modi (0000-0003-3262-5374, Flinders University), Bradley D Menz (0000-0002-0855-5081, Flinders University), Stephen Bacchi (0000-0001-5130-8628, Massachusetts General Hospital), Ganessan Kichenadasse (0000-0001-9923-5149, Flinders University), Catherine Paterson (0000-0002-1249-6782, Flinders University), Joshua G Kovoor (0000-0002-3880-3840, Ballarat Health Services), Imogen Ramsey (0000-0002-8757-1572, Flinders University), Jessica M Logan (0000-0003-4046-6908, University of South Australia), Michael D Wiese (0000-0002-3255-9242, University of South Australia), Ross A McKinnon (0000-0002-3725-793X, Flinders University), Andrew Rowland (0000-0001-9564-0032, Flinders University), Michael J Sorich (0000-0003-1999-866X, Flinders University), Ashley M Hopkins (0000-0001-7652-4378, Flinders University, corresponding author)
Year2025
Volume13
Pages1584348-1584348
Publication date2025-05-09
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1584348
PMID40416675
OpenAlexW4410247904
LanguageEN
References cited23

Introduction: Generative 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. Methods: We 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. Results: A 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. Discussion: This 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

Business · European union · Health care · Health professionals · Medical education · Observational study · Political science · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI · Medicine · Psychology · Internal Medicine

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