Environment scan of generative AI infrastructure for clinical and translational science

Betina Idnay; Zihan Xu; William G. Adams; Mohammad Adibuzzaman; Nicholas R. Anderson; Neil Bahroos; Douglas S. Bell; Cody Bumgardner; Thomas Campion; Mario Castro; James J. Cimino; I. Glenn Cohen; David Dorr; Peter L. Elkin; Jungwei W. Fan; Todd Ferris; David J. Foran; David Hanauer; Mike Hogarth; Kun Huang; Jayashree Kalpathy-Cramer; Manoj Kandpal; Niranjan S. Karnik; Avnish Katoch; Albert M. Lai; Christophe G. Lambert; Lang Li; Christopher Lindsell; Jinze Liu; Zhiyong Lu; Yuan Luo; Peter McGarvey; Eneida A. Mendonca; Parsa Mirhaji; Shawn Murphy; John D. Osborne; Ioannis C. Paschalidis; Paul A. Harris; Fred Prior; Nicholas J. Shaheen; Nawar Shara; Ida Sim; Umberto Tachinardi; Lemuel R. Waitman; Rosalind J. Wright; Adrian H. Zai; Kai Zheng; Sandra Soo Jin Lee; Bradley A. Malin; Karthik Natarajan; W. Nicholson Price; Rui Zhang; Yiye Zhang; Hua Xu; Jiang Bian; Chunhua Weng; Yifan Peng

doi:10.1038/s44401-024-00009-w

Environment scan of generative AI infrastructure for clinical and translational science

Betina Idnay
, Zihan Xu
, William G. Adams
, Mohammad Adibuzzaman
, Nicholas R. Anderson
, Neil Bahroos
, Douglas S. Bell
, Cody Bumgardner
, Thomas Campion
, Mario Castro
, James J. Cimino
, I. Glenn Cohen
, David Dorr
, Peter L. Elkin
, Jungwei W. Fan
, Todd Ferris
, David J. Foran
, David Hanauer
, Mike Hogarth
, Kun Huang

Jayashree Kalpathy-Cramer, Manoj Kandpal, Niranjan S. Karnik, Avnish Katoch, Albert M. Lai, Christophe G. Lambert, Lang Li, Christopher Lindsell, Jinze Liu, Zhiyong Lu, Yuan Luo, Peter McGarvey, Eneida A. Mendonca, Parsa Mirhaji, Shawn Murphy, John D. Osborne, Ioannis C. Paschalidis, Paul A. Harris, Fred Prior, Nicholas J. Shaheen, Nawar Shara, Ida Sim, Umberto Tachinardi, Lemuel R. Waitman, Rosalind J. Wright, Adrian H. Zai, Kai Zheng, Sandra Soo Jin Lee, Bradley A. Malin, Karthik Natarajan, W. Nicholson Price, Rui Zhang, Yiye Zhang, Hua Xu, Jiang Bian, Chunhua Weng, Yifan Peng

Department of Biomedical Informatics

Columbia University
Cornell University
Boston University
Oregon Health and Science University
University of California at Davis
University of Southern California
University of California at Los Angeles
University of Kentucky
University of Kansas
University of Alabama at Birmingham
Harvard University
Mayo Clinic Rochester, MN
Stanford University
Rutgers - The State University of New Jersey, New Brunswick
University of Michigan, Ann Arbor
University of California at San Diego
Indiana University
University of Colorado Anschutz Medical Campus
Rockefeller University
University of Illinois at Chicago
Pennsylvania State University
Washington University St. Louis
University of New Mexico
Ohio State University
Duke University
Virginia Commonwealth University
National Institutes of Health
Northwestern University
Georgetown/Howard Universities Center for Clinical and Translational Sciences
Cincinnati Children's Hospital Medical Center
Albert Einstein College of Medicine
Partners HealthCare
Vanderbilt University
University of Arkansas for Medical Sciences
University of North Carolina at Chapel Hill
University of California at San Francisco
University of Cincinnati
University of Missouri
Icahn School of Medicine at Mount Sinai
University of Massachusetts Medical School
University of California at Irvine
University of Minnesota Twin Cities
Yale University
University of Florida
Indiana University
Regenstrief Institute Inc

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the CTSA Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis reveals that 53% of institutions identified data security as a primary concern, followed by lack of clinician trust (50%) and AI bias (44%), which must be addressed to ensure the ethical and effective implementation of GenAI technologies.

Original language	English
Article number	4
Journal	npj Health Systems
Volume	2
Issue number	1
DOIs	https://doi.org/10.1038/s44401-024-00009-w
State	Published - Dec 2025

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Idnay, B., Xu, Z., Adams, W. G., Adibuzzaman, M., Anderson, N. R., Bahroos, N., Bell, D. S., Bumgardner, C., Campion, T., Castro, M., Cimino, J. J., Cohen, I. G., Dorr, D., Elkin, P. L., Fan, J. W., Ferris, T., Foran, D. J., Hanauer, D., Hogarth, M., ... Peng, Y. (2025). Environment scan of generative AI infrastructure for clinical and translational science. npj Health Systems, 2(1), Article 4. https://doi.org/10.1038/s44401-024-00009-w

@article{601d5b6ad6064d6092743ceedfa86bf9,

title = "Environment scan of generative AI infrastructure for clinical and translational science",

abstract = "This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the CTSA Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis reveals that 53\% of institutions identified data security as a primary concern, followed by lack of clinician trust (50\%) and AI bias (44\%), which must be addressed to ensure the ethical and effective implementation of GenAI technologies.",

author = "Betina Idnay and Zihan Xu and Adams, \{William G.\} and Mohammad Adibuzzaman and Anderson, \{Nicholas R.\} and Neil Bahroos and Bell, \{Douglas S.\} and Cody Bumgardner and Thomas Campion and Mario Castro and Cimino, \{James J.\} and Cohen, \{I. Glenn\} and David Dorr and Elkin, \{Peter L.\} and Fan, \{Jungwei W.\} and Todd Ferris and Foran, \{David J.\} and David Hanauer and Mike Hogarth and Kun Huang and Jayashree Kalpathy-Cramer and Manoj Kandpal and Karnik, \{Niranjan S.\} and Avnish Katoch and Lai, \{Albert M.\} and Lambert, \{Christophe G.\} and Lang Li and Christopher Lindsell and Jinze Liu and Zhiyong Lu and Yuan Luo and Peter McGarvey and Mendonca, \{Eneida A.\} and Parsa Mirhaji and Shawn Murphy and Osborne, \{John D.\} and Paschalidis, \{Ioannis C.\} and Harris, \{Paul A.\} and Fred Prior and Shaheen, \{Nicholas J.\} and Nawar Shara and Ida Sim and Umberto Tachinardi and Waitman, \{Lemuel R.\} and Wright, \{Rosalind J.\} and Zai, \{Adrian H.\} and Kai Zheng and Lee, \{Sandra Soo Jin\} and Malin, \{Bradley A.\} and Karthik Natarajan and Price, \{W. Nicholson\} and Rui Zhang and Yiye Zhang and Hua Xu and Jiang Bian and Chunhua Weng and Yifan Peng",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.",

year = "2025",

month = dec,

doi = "10.1038/s44401-024-00009-w",

language = "English",

volume = "2",

journal = "npj Health Systems",

issn = "3005-1959",

publisher = "Springer Nature",

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Idnay, B, Xu, Z, Adams, WG, Adibuzzaman, M, Anderson, NR, Bahroos, N, Bell, DS, Bumgardner, C, Campion, T, Castro, M, Cimino, JJ, Cohen, IG, Dorr, D, Elkin, PL, Fan, JW, Ferris, T, Foran, DJ, Hanauer, D, Hogarth, M, Huang, K, Kalpathy-Cramer, J, Kandpal, M, Karnik, NS, Katoch, A, Lai, AM, Lambert, CG, Li, L, Lindsell, C, Liu, J, Lu, Z, Luo, Y, McGarvey, P, Mendonca, EA, Mirhaji, P, Murphy, S, Osborne, JD, Paschalidis, IC, Harris, PA, Prior, F, Shaheen, NJ, Shara, N, Sim, I, Tachinardi, U, Waitman, LR, Wright, RJ, Zai, AH, Zheng, K, Lee, SSJ, Malin, BA, Natarajan, K, Price, WN, Zhang, R, Zhang, Y, Xu, H, Bian, J, Weng, C & Peng, Y 2025, 'Environment scan of generative AI infrastructure for clinical and translational science', npj Health Systems, vol. 2, no. 1, 4. https://doi.org/10.1038/s44401-024-00009-w

TY - JOUR

T1 - Environment scan of generative AI infrastructure for clinical and translational science

AU - Idnay, Betina

AU - Xu, Zihan

AU - Adams, William G.

AU - Adibuzzaman, Mohammad

AU - Anderson, Nicholas R.

AU - Bahroos, Neil

AU - Bell, Douglas S.

AU - Bumgardner, Cody

AU - Campion, Thomas

AU - Castro, Mario

AU - Cimino, James J.

AU - Cohen, I. Glenn

AU - Dorr, David

AU - Elkin, Peter L.

AU - Fan, Jungwei W.

AU - Ferris, Todd

AU - Foran, David J.

AU - Hanauer, David

AU - Hogarth, Mike

AU - Huang, Kun

AU - Kalpathy-Cramer, Jayashree

AU - Kandpal, Manoj

AU - Karnik, Niranjan S.

AU - Katoch, Avnish

AU - Lai, Albert M.

AU - Lambert, Christophe G.

AU - Li, Lang

AU - Lindsell, Christopher

AU - Liu, Jinze

AU - Lu, Zhiyong

AU - Luo, Yuan

AU - McGarvey, Peter

AU - Mendonca, Eneida A.

AU - Mirhaji, Parsa

AU - Murphy, Shawn

AU - Osborne, John D.

AU - Paschalidis, Ioannis C.

AU - Harris, Paul A.

AU - Prior, Fred

AU - Shaheen, Nicholas J.

AU - Shara, Nawar

AU - Sim, Ida

AU - Tachinardi, Umberto

AU - Waitman, Lemuel R.

AU - Wright, Rosalind J.

AU - Zai, Adrian H.

AU - Zheng, Kai

AU - Lee, Sandra Soo Jin

AU - Malin, Bradley A.

AU - Natarajan, Karthik

AU - Price, W. Nicholson

AU - Zhang, Rui

AU - Zhang, Yiye

AU - Xu, Hua

AU - Bian, Jiang

AU - Weng, Chunhua

AU - Peng, Yifan

PY - 2025/12

Y1 - 2025/12

N2 - This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the CTSA Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis reveals that 53% of institutions identified data security as a primary concern, followed by lack of clinician trust (50%) and AI bias (44%), which must be addressed to ensure the ethical and effective implementation of GenAI technologies.

AB - This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the CTSA Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis reveals that 53% of institutions identified data security as a primary concern, followed by lack of clinician trust (50%) and AI bias (44%), which must be addressed to ensure the ethical and effective implementation of GenAI technologies.

UR - https://www.scopus.com/pages/publications/105030965241

U2 - 10.1038/s44401-024-00009-w

DO - 10.1038/s44401-024-00009-w

M3 - Article

AN - SCOPUS:105030965241

SN - 3005-1959

VL - 2

JO - npj Health Systems

JF - npj Health Systems

IS - 1

M1 - 4

ER -

Environment scan of generative AI infrastructure for clinical and translational science

Abstract

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