News Release

Generative AI to transform inpatient discharge summaries to patient-friendly language and format

JAMA Network Open

Peer-Reviewed Publication

JAMA Network

About The Study: The findings of this study of 50 discharge summaries suggest that large language models can be used to translate discharge summaries into patient-friendly language and formats that are significantly more readable and understandable than discharge summaries as they appear in electronic health records. However, implementation will require improvements in accuracy, completeness, and safety. Given the safety concerns, initial implementation will require physician review. 

Authors: Jonah Zaretsky, M.D., of NYU Langone Health in New York, is the corresponding author. 

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/ 

(doi:10.1001/jamanetworkopen.2024.0357)

Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

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Embed this link to provide your readers free access to the full-text article This link will be live at the embargo time http://jamanetwork.com/journals/jamanetworkopen/fullarticle/10.1001/jamanetworkopen.2024.0357?utm_source=For_The_Media&utm_medium=referral&utm_campaign=ftm_links&utm_term=031124

About JAMA Network Open: JAMA Network Open is an online-only open access general medical journal from the JAMA Network. On weekdays, the journal publishes peer-reviewed clinical research and commentary in more than 40 medical and health subject areas. Every article is free online from the day of publication. 

 


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