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Rapid Evaluation of Artificial Intelligence Technology Used for Ambient Dictation in Primary Care: Comparing the Quality of Documentation of Artificial Intelligence-Generated and Human-Produced Clinical Notes.

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Title: Rapid Evaluation of Artificial Intelligence Technology Used for Ambient Dictation in Primary Care: Comparing the Quality of Documentation of Artificial Intelligence-Generated and Human-Produced Clinical Notes.
Authors: Reddy A; Department of Medicine, Division of General Internal Medicine, University of Washington, and Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, Washington (A.R., K.M.N.)., Gunnink E; Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, Washington (E.G., C.L.W.)., Wheat CL; Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, Washington (E.G., C.L.W.)., Pawlikowski S; VA Office of Primary Care, Washington, DC; and Department of Medicine, Loyola University Chicago Stritch School of Medicine, Chicago, Illinois (S.P.)., Payne CM; VA Simulation Learning, Evaluation, Assessment, and Research Network, Orlando, Florida (C.M.P., S.W.)., Wiltz S; VA Simulation Learning, Evaluation, Assessment, and Research Network, Orlando, Florida (C.M.P., S.W.)., Hubert TL; Discovery, Education and Affiliate Networks, Veterans Health Administration, U.S. Department of Veterans Affairs, Washington, DC (T.L.H.)., Kirsh S; Discovery, Education and Affiliate Networks, Veterans Health Administration, U.S. Department of Veterans Affairs, Washington, DC; Case Western Reserve University, Cleveland, Ohio (S.K.)., Carey E; VA Digital Health Office, National AI Institute, Washington DC (E.C., D.H.)., Hill D; VA Digital Health Office, National AI Institute, Washington DC (E.C., D.H.)., Nelson KM; Department of Medicine, Division of General Internal Medicine, University of Washington, and Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, Washington (A.R., K.M.N.).
Source: Annals of internal medicine [Ann Intern Med] 2026 Jun; Vol. 179 (6), pp. 765-772. Date of Electronic Publication: 2026 Apr 17.
Publication Type: Journal Article; Comparative Study
Journal Info: Publisher: American College of Physicians--American Society of Internal Medicine Country of Publication: United States NLM ID: 0372351 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1539-3704 (Electronic) Linking ISSN: 00034819 NLM ISO Abbreviation: Ann Intern Med Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Rapid Evaluation of Artificial Intelligence Technology Used for Ambient Dictation in Primary Care: Comparing the Quality of Documentation of Artificial Intelligence-Generated and Human-Produced Clinical Notes.
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  Data: <searchLink fieldCode="AU" term="%22Reddy+A%22">Reddy A</searchLink>; Department of Medicine, Division of General Internal Medicine, University of Washington, and Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, Washington (A.R., K.M.N.).<br /><searchLink fieldCode="AU" term="%22Gunnink+E%22">Gunnink E</searchLink>; Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, Washington (E.G., C.L.W.).<br /><searchLink fieldCode="AU" term="%22Wheat+CL%22">Wheat CL</searchLink>; Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, Washington (E.G., C.L.W.).<br /><searchLink fieldCode="AU" term="%22Pawlikowski+S%22">Pawlikowski S</searchLink>; VA Office of Primary Care, Washington, DC; and Department of Medicine, Loyola University Chicago Stritch School of Medicine, Chicago, Illinois (S.P.).<br /><searchLink fieldCode="AU" term="%22Payne+CM%22">Payne CM</searchLink>; VA Simulation Learning, Evaluation, Assessment, and Research Network, Orlando, Florida (C.M.P., S.W.).<br /><searchLink fieldCode="AU" term="%22Wiltz+S%22">Wiltz S</searchLink>; VA Simulation Learning, Evaluation, Assessment, and Research Network, Orlando, Florida (C.M.P., S.W.).<br /><searchLink fieldCode="AU" term="%22Hubert+TL%22">Hubert TL</searchLink>; Discovery, Education and Affiliate Networks, Veterans Health Administration, U.S. Department of Veterans Affairs, Washington, DC (T.L.H.).<br /><searchLink fieldCode="AU" term="%22Kirsh+S%22">Kirsh S</searchLink>; Discovery, Education and Affiliate Networks, Veterans Health Administration, U.S. Department of Veterans Affairs, Washington, DC; Case Western Reserve University, Cleveland, Ohio (S.K.).<br /><searchLink fieldCode="AU" term="%22Carey+E%22">Carey E</searchLink>; VA Digital Health Office, National AI Institute, Washington DC (E.C., D.H.).<br /><searchLink fieldCode="AU" term="%22Hill+D%22">Hill D</searchLink>; VA Digital Health Office, National AI Institute, Washington DC (E.C., D.H.).<br /><searchLink fieldCode="AU" term="%22Nelson+KM%22">Nelson KM</searchLink>; Department of Medicine, Division of General Internal Medicine, University of Washington, and Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, Washington (A.R., K.M.N.).
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  Data: <searchLink fieldCode="JN" term="%220372351%22">Annals of internal medicine</searchLink> [Ann Intern Med] 2026 Jun; Vol. 179 (6), pp. 765-772. <i>Date of Electronic Publication: </i>2026 Apr 17.
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