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Clinical artificial intelligence competence in obstetrics and gynecology: patient safety, physician accountability, and responsible use.

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Τίτλος: Clinical artificial intelligence competence in obstetrics and gynecology: patient safety, physician accountability, and responsible use.
Συγγραφείς: Grünebaum A; Northwell Health, Division of Ethics, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, NY. Electronic address: agrunebaum@northwell.edu., Dudenhausen J; Northwell Health, Division of Ethics, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, NY., Chervenak FA; Northwell Health, Division of Ethics, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, NY.
Πηγή: American journal of obstetrics and gynecology [Am J Obstet Gynecol] 2026 Oct; Vol. 235 (4), pp. 817-824. Date of Electronic Publication: 2026 Jun 19.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: United States NLM ID: 0370476 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-6868 (Electronic) Linking ISSN: 00029378 NLM ISO Abbreviation: Am J Obstet Gynecol Subsets: MEDLINE
Imprint Name(s): Publication: <2005->: New York : Elsevier
Original Publication: St. Louis.
Ιατρικοί όροι (MeSH): Obstetrics*/education , Obstetrics*/standards , Gynecology*/standards , Gynecology*/education , Artificial Intelligence* , Patient Safety* , Clinical Competence* , Social Responsibility*, Humans ; Female ; Generative Artificial Intelligence ; Gynecologists ; Obstetricians ; Pregnancy
Περίληψη: Artificial intelligence, especially generative large language models, has rapidly entered obstetric and gynecologic care through patient use, clinician documentation, counseling support, medical education, and evidence retrieval. This integration has occurred faster than formal training, specialty-specific standards, or governance structures have developed. The relevant clinical question is, therefore, no longer whether obstetricians and gynecologists will encounter artificial intelligence, but whether they can use it competently, verify its outputs, protect patient privacy, and remain accountable for clinical decisions. This Clinical Opinion proposes clinical artificial intelligence competence as an emerging component of safe professional practice in obstetrics and gynecology. We define this competence as the ability to use artificial intelligence tools for appropriate clinical tasks while critically appraising output, recognizing hallucinations and outdated guidance, verifying sources, preserving confidentiality, communicating uncertainty, and maintaining independent clinical judgment. Potential benefits include improved readability of patient materials, more efficient evidence retrieval, documentation support, informed consent assistance, and reduced cognitive burden during complex care. Risks include fabricated citations, incorrect recommendations, algorithmic bias, privacy breaches, deskilling of trainees, and inappropriate delegation of clinical reasoning. Historical experience with ultrasound, electronic fetal monitoring, cell-free DNA screening, and other obstetric technologies suggests that the profession should neither reject new tools reflexively nor adopt them uncritically. Instead, artificial intelligence use should be structured, supervised, version-specific, and proportionate to clinical risk. Clinical artificial intelligence competence should be incorporated gradually into residency, fellowship, continuing medical education, departmental teaching, morbidity and mortality review, and patient safety programs. Outcome-based evaluation remains essential as these tools enter practice.
(Copyright © 2026 The Author(s). Published by Elsevier Inc. All rights reserved.)
Contributed Indexing: Keywords: artificial intelligence; clinical artificial intelligence competence; clinical decision support; clinical governance; clinical judgment; continuing medical education; gynecology; health literacy; implementation science; informed consent; medical professionalism; obstetrics; patient communication; patient counseling; patient safety; physician accountability; physician-patient relationship; quality improvement; residency education
Entry Date(s): Date Created: 20260619 Date Completed: 20260917 Latest Revision: 20260917
Update Code: 20260918
DOI: 10.1016/j.ajog.2026.06.011
PMID: 42320614
Βάση Δεδομένων: MEDLINE
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  Data: Artificial intelligence, especially generative large language models, has rapidly entered obstetric and gynecologic care through patient use, clinician documentation, counseling support, medical education, and evidence retrieval. This integration has occurred faster than formal training, specialty-specific standards, or governance structures have developed. The relevant clinical question is, therefore, no longer whether obstetricians and gynecologists will encounter artificial intelligence, but whether they can use it competently, verify its outputs, protect patient privacy, and remain accountable for clinical decisions. This Clinical Opinion proposes clinical artificial intelligence competence as an emerging component of safe professional practice in obstetrics and gynecology. We define this competence as the ability to use artificial intelligence tools for appropriate clinical tasks while critically appraising output, recognizing hallucinations and outdated guidance, verifying sources, preserving confidentiality, communicating uncertainty, and maintaining independent clinical judgment. Potential benefits include improved readability of patient materials, more efficient evidence retrieval, documentation support, informed consent assistance, and reduced cognitive burden during complex care. Risks include fabricated citations, incorrect recommendations, algorithmic bias, privacy breaches, deskilling of trainees, and inappropriate delegation of clinical reasoning. Historical experience with ultrasound, electronic fetal monitoring, cell-free DNA screening, and other obstetric technologies suggests that the profession should neither reject new tools reflexively nor adopt them uncritically. Instead, artificial intelligence use should be structured, supervised, version-specific, and proportionate to clinical risk. Clinical artificial intelligence competence should be incorporated gradually into residency, fellowship, continuing medical education, departmental teaching, morbidity and mortality review, and patient safety programs. Outcome-based evaluation remains essential as these tools enter practice.&lt;br /&gt; (Copyright &#169; 2026 The Author(s). Published by Elsevier Inc. All rights reserved.)
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