Economics and Equity of Large Language Models: Health Care Perspective.

Radha Nagarajan¹, Midori Kondo², Franz Salas³, Emre Sezgin⁴, Yuan Yao⁵, Vanessa Klotzman⁶, Sandip A Godambe¹, Naqi Khan⁷, Alfonso Limon¹, Graham Stephenson⁸, Sharief Taraman⁹, Nephi Walton¹⁰, Louis Ehwerhemuepha¹, Jay Pandit¹¹, Deepti Pandita⁸, Michael Weiss¹, Charles Golden¹, Adam Gold¹, John Henderson¹, Angela Shippy¹², Leo Anthony Celi¹³, William R Hogan¹⁴, Eric K Oermann¹⁵, Terence Sanger¹, Steven Martel^1,16

¹Children's Hospital of Orange County, Orange, CA, United States.

²Fred Hutch Patient Care, Seattle, WA, United States.

³Amazon Web Services, Detroit, MI, United States.

⁴Nationwide Children's Hospital, Columbus, OH, United States.

⁵Amazon Web Services, San Francisco, CA, United States.

⁶University of California Irvine, Irvine, CA, United States.

⁷Amazon Web Services, Seattle, WA, United States.

⁸University of California Irvine Health, Irvine, CA, United States.

⁹Cognoa LLC, Palo Alto, CA, United States.

¹⁰National Institutes of Health, Bethesda, MD, United States.

¹¹Scripps Research Translational Institute, La Jolla, CA, United States.

¹²Amazon Web Services, Houston, TX, United States.

¹³Massachusetts Institute of Technology, Cambridge, MA, United States.

¹⁴Medical College of Wisconsin, Milwaukee, WI, United States.

¹⁵NYU Langone Medical Center, New York, NY, United States.

¹⁶Physicians Specialty Faculty, Orange, CA, United States.

PubMed PMC DOI PDF

Abstract

Large language models (LLMs) continue to exhibit noteworthy capabilities across a spectrum of areas, including emerging proficiencies across the health care continuum. Successful LLM implementation and adoption depend on digital readiness, modern infrastructure, a trained workforce, privacy, and an ethical regulatory landscape. These factors can vary significantly across health care ecosystems, di…

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