{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T10:58:13Z","timestamp":1792061893729,"version":"4.4.0"},"reference-count":20,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:00:00Z","timestamp":1792022400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:00:00Z","timestamp":1792022400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["shmpublications.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Hospital Medicine"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Large language models (LLMs) can now draft hospital discharge summaries. Reported hallucination rates vary by measurement context, from about 1%\u20132% in structured summarisation to over 60% under provocation testing. The common argument that LLMs outperform a tired resident treats a high\u2010stakes clinical and legal document as a text\u2010quality problem. We argue that a potentially underappreciated concern is the weakening of clinician oversight when reviewing fluent machine\u2010generated text, and that the joint clinician\u2010AI system is central to safety. We propose a Clinician\u2010AI Oversight Model with four safeguards: bounded autonomy, structured verification, error\u2010signal monitoring, and longitudinal evaluation of cognitive effects.<\/jats:p>","DOI":"10.1002\/jhm.70513","type":"journal-article","created":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T10:42:16Z","timestamp":1792060936000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Cognition, oversight, and the safety case for documentation AI"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4100-1571","authenticated-orcid":false,"given":"Fahad Wali","family":"Ahmed","sequence":"first","affiliation":[{"name":"Department of Medicine King Faisal Specialist Hospital and Research Centre Madinah Saudi 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