{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T22:33:05Z","timestamp":1793226785930,"version":"4.5.0"},"reference-count":25,"publisher":"Elsevier BV","issue":"5","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["bjanaesthesia.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["British Journal of Anaesthesia"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.bja.2026.08.008","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T20:46:44Z","timestamp":1788900404000},"page":"1349-1354","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Language, power, and access: large language models and equity in medicine"],"prefix":"10.1016","volume":"137","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5630-3065","authenticated-orcid":false,"given":"Hazem","family":"Lashin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.bja.2026.08.008_bib1","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1038\/s43856-023-00370-1","article-title":"The future landscape of large language models in medicine","volume":"3","author":"Clusmann","year":"2023","journal-title":"Commun Med (Lond)"},{"key":"10.1016\/j.bja.2026.08.008_bib2","series-title":"Ethics and governance of artificial intelligence for health: guidance on large multi-modal models","year":"2024"},{"key":"10.1016\/j.bja.2026.08.008_bib3","doi-asserted-by":"crossref","first-page":"e260","DOI":"10.1016\/S2589-7500(20)30317-4","article-title":"Health data poverty: an assailable barrier to equitable digital health care","volume":"3","author":"Ibrahim","year":"2021","journal-title":"Lancet Digit Health"},{"key":"10.1016\/j.bja.2026.08.008_bib4","article-title":"Challenges and opportunities of artificial intelligence in African health space","volume":"11","author":"Alaran","year":"2025","journal-title":"Digit Health"},{"key":"10.1016\/j.bja.2026.08.008_bib5","doi-asserted-by":"crossref","DOI":"10.1016\/j.bjao.2024.100296","article-title":"A comparative study of English and Japanese ChatGPT responses to anaesthesia-related medical questions","volume":"10","author":"Ando","year":"2024","journal-title":"BJA Open"},{"key":"10.1016\/j.bja.2026.08.008_bib6","article-title":"Evaluating large language models in dental anesthesiology: a comparative analysis of ChatGPT-4, Claude 3 Opus, and Gemini 1.0 on the Japanese Dental Society of Anesthesiology board certification exam","volume":"16","author":"Fujimoto","year":"2024","journal-title":"Cureus"},{"key":"10.1016\/j.bja.2026.08.008_bib7","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1038\/s41746-023-00939-z","article-title":"Large language models propagate race-based medicine","volume":"6","author":"Omiye","year":"2023","journal-title":"NPJ Digit Med"},{"key":"10.1016\/j.bja.2026.08.008_bib8","article-title":"Gender disparities in artificial intelligence\u2013generated images of hospital leadership in the United States","volume":"3","author":"Gisselbaek","year":"2025","journal-title":"Mayo Clin Proc Digit Health"},{"key":"10.1016\/j.bja.2026.08.008_bib9","doi-asserted-by":"crossref","DOI":"10.1136\/bmjgh-2023-014131","article-title":"Colonialism in the new digital health agenda","volume":"9","author":"Sekalala","year":"2024","journal-title":"BMJ Glob Health"},{"issue":"2","key":"10.1016\/j.bja.2026.08.008_bib10","doi-asserted-by":"crossref","DOI":"10.1056\/AIoa2300068","article-title":"Almanac - Retrieval-Augmented Language Models for Clinical Medicine","volume":"1","author":"Zakka","year":"2024","journal-title":"NEJM AI"},{"key":"10.1016\/j.bja.2026.08.008_bib11","first-page":"298","article-title":"Automation bias in AI-decision support: results from an empirical study","volume":"317","author":"K\u00fccking","year":"2024","journal-title":"Stud Health Technol Inform"},{"key":"10.1016\/j.bja.2026.08.008_bib12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1177\/00222429251314491","article-title":"Lower artificial intelligence literacy predicts greater AI receptivity","volume":"89","author":"Tully","year":"2025","journal-title":"J Mark"},{"key":"10.1016\/j.bja.2026.08.008_bib13","doi-asserted-by":"crossref","first-page":"1873","DOI":"10.1056\/NEJMp2517624","article-title":"Can AI say \u2018I Don\u2019t know\u2019?","volume":"394","author":"Sikora","year":"2026","journal-title":"N Engl J Med"},{"key":"10.1016\/j.bja.2026.08.008_bib14","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1007\/s11739-023-03484-5","article-title":"How accurate are the references generated by ChatGPT in internal medicine?","volume":"19","author":"Sebo","year":"2024","journal-title":"Intern Emerg Med"},{"key":"10.1016\/j.bja.2026.08.008_bib15","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1038\/s43856-025-00781-2","article-title":"Physician clinical decision modification and bias assessment in a randomized controlled trial of AI assistance","volume":"5","author":"Goh","year":"2025","journal-title":"Commun Med (Lond)"},{"key":"10.1016\/j.bja.2026.08.008_bib16","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pdig.0000899","article-title":"Evaluating large language models for drafting emergency department encounter summaries","volume":"4","author":"Williams","year":"2025","journal-title":"PLoS Digit Health"},{"key":"10.1016\/j.bja.2026.08.008_bib17","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1038\/s41746-025-01670-7","article-title":"A framework to assess clinical safety and hallucination rates of LLMs for medical text summarisation","volume":"8","author":"Asgari","year":"2025","journal-title":"NPJ Digit Med"},{"key":"10.1016\/j.bja.2026.08.008_bib18","doi-asserted-by":"crossref","first-page":"1134","DOI":"10.1038\/s41591-024-02855-5","article-title":"Adapted large language models can outperform medical experts in clinical text summarization","volume":"30","author":"Van Veen","year":"2024","journal-title":"Nat Med"},{"key":"10.1016\/j.bja.2026.08.008_bib19","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1016\/j.bja.2025.01.001","article-title":"A comparison of large language model-generated and published perioperative neurocognitive disorder recommendations: a cross-sectional web-based analysis","volume":"136","author":"Saxena","year":"2026","journal-title":"Br J Anaesth"},{"key":"10.1016\/j.bja.2026.08.008_bib20","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2024.0357","article-title":"Generative artificial intelligence to transform inpatient discharge summaries to patient-friendly language and format","volume":"7","author":"Zaretsky","year":"2024","journal-title":"JAMA Netw Open"},{"key":"10.1016\/j.bja.2026.08.008_bib21","article-title":"Evaluating generative AI in mental health: systematic review of capabilities and limitations","volume":"12","author":"Wang","year":"2025","journal-title":"JMIR Ment Health"},{"key":"10.1016\/j.bja.2026.08.008_bib22","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1038\/s41586-025-08869-4","article-title":"Towards accurate differential diagnosis with large language models","volume":"642","author":"McDuff","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.bja.2026.08.008_bib23","series-title":"Regulatory considerations on artificial intelligence for health","year":"2023"},{"key":"10.1016\/j.bja.2026.08.008_bib24","series-title":"AI in practice","year":"2026"},{"key":"10.1016\/j.bja.2026.08.008_bib25","series-title":"EU AI act: first regulation on artificial intelligence","year":"2024"}],"container-title":["British Journal of Anaesthesia"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S000709122600601X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S000709122600601X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T22:09:14Z","timestamp":1793225354000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S000709122600601X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":25,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["S000709122600601X"],"URL":"https:\/\/doi.org\/10.1016\/j.bja.2026.08.008","relation":{},"ISSN":["0007-0912"],"issn-type":[{"value":"0007-0912","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Language, power, and access: large language models and equity in medicine","name":"articletitle","label":"Article Title"},{"value":"British Journal of Anaesthesia","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bja.2026.08.008","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"simple-article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}