Academic Journal
Environment Scan of Generative AI Infrastructure for Clinical and Translational Science.
| Τίτλος: | Environment Scan of Generative AI Infrastructure for Clinical and Translational Science. |
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| Συγγραφείς: | Idnay B; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA., Xu Z; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA., Adams WG; Department of Pediatrics, Boston Medical Center, Boston, MA, USA; Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, USA., Adibuzzaman M; Oregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, OR, USA., Anderson NR; Department of Public Health Sciences, University of California, Davis, Davis, CA, USA., Bahroos N; Keck School of Medicine, University of Southern California, Los Angeles, CA, USA., Bell DS; Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA., Bumgardner C; Department of Pathology and Laboratory Medicine, University of Kentucky College of Medicine, Lexington, KY, USA., Campion T; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.; Clinical and Translational Science Center, Weill Cornell Medicine, New York, NY, USA., Castro M; Division of Pulmonary, Critical Care and Sleep Medicine, University of Kansas School of Medicine, Kansas City, KS, USA., Cimino JJ; Department of Biomedical Informatics and Data Science, Heersink School of Medicine, University of Alabama, Birmingham, AL, USA., Cohen IG; Harvard Law School, Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics, Harvard University, Cambridge, MA, USA., Dorr D; Oregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, OR, USA., Elkin PL; Department of Biomedical Informatics, University at Buffalo, Buffalo, NY, USA., Fan JW; Center for Clinical and Translational Science, Mayo Clinic, Rochester, MN, USA., Ferris T; Technology and Digital Solutions, Stanford Medicine, Stanford University, Stanford, CA, USA., Foran DJ; Center for Biomedical Informatics, Rutgers Cancer Institute, New Brunswick, NJ, USA., Hanauer D; Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, MI, USA., Hogarth M; Altman Clinical and Translational Research Institute (ACTRI), University of California San Diego, La Jolla, CA, United States., Huang K; Department of Biostatistics and Health Data Science, School of Medicine, Indiana University, Indianapolis, IN, USA., Kalpathy-Cramer J; Division of Artificial Medical Intelligence in Ophthalmology, University of Colorado, Aurora, CO, USA., Kandpal M; Center for Clinical and Translational Science, Rockefeller University Hospital, Rockefeller University, New York, NY, USA., Karnik NS; AI.Health4All Center, Center for Clinical & Translational Science, and Department of Psychiatry, University of Illinois Chicago, Chicago, IL, USA., Katoch A; Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA., Lai AM; Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA., Lambert CG; Division of Translational Informatics, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA., Li L; Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA., Lindsell C; Duke Clinical Research Institute, Duke University, Durham, NC, USA., Liu J; Department of Population Health, Virginia Commonwealth University, Richmond, VA, USA., Lu Z; Division of Intramural Research, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA., Luo Y; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA., McGarvey P; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA., Mendonca EA; Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA., Mirhaji P; Institute for Clinical Translational Research, Albert Einstein College of Medicine, New York, NY, USA., Murphy S; Department of Neurology, Mass General Brigham, Somerville, MA, USA., Osborne JD; Department of Medicine, University of Alabama, Birmingham, AL, USA., Paschalidis IC; College of Engineering and Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA., Harris PA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Prior F; Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA., Shaheen NJ; Division of Gastroenterology and Hepatology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA., Shara N; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA., Sim I; Department of Medicine, University of California, San Francisco, San Francisco, CA, USA., Tachinardi U; Department of Biostatistics, Health Informatics and Data Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA., Waitman LR; Department of Biomedical Informatics, Biostatistics, and Medical Epidemiology, School of Medicine, University of Missouri, Columbia, MO, USA., Wright RJ; Department of Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Zai AH; Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, MA, USA., Zheng K; Department of Informatics, University of California, Irvine, Irvine, CA, USA., Lee SS; Department of Medical Humanities and Ethics, Columbia University, New York, NY, USA., Malin BA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Natarajan K; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA., Price WN 2nd; Michigan Law School, University of Michigan, Ann Arbor, MI, USA., Zhang R; Division of Computational Health Sciences, Medical School, University of Minnesota, Minneapolis, MN, USA., Zhang Y; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA., Xu H; Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA., Bian J; Department of Neurology and McKnight Brain Institute, College of Medicine, University of Florida, Gainesville, FL, USA., Weng C; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.; The Irving Institute for Clinical and Translational Research, Columbia University, New York, NY, USA., Peng Y; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.; Clinical and Translational Science Center, Weill Cornell Medicine, New York, NY, USA. |
| Πηγή: | ArXiv [ArXiv] 2024 Sep 28. Date of Electronic Publication: 2024 Sep 28. |
| Τύπος έκδοσης: | Journal Article; Preprint |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Country of Publication: United States NLM ID: 101759493 Publication Model: Electronic Cited Medium: Internet ISSN: 2331-8422 (Electronic) Linking ISSN: 23318422 NLM ISO Abbreviation: ArXiv Subsets: PubMed not MEDLINE |
| Περίληψη: | 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 Clinical and Translational Science Award (CTSA) Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. With the rapid advancement of GenAI technologies, including large language models (LLMs), healthcare institutions face unprecedented opportunities and challenges. This research explores the current status of GenAI integration, focusing on stakeholder roles, governance structures, and ethical considerations by administering a survey among leaders of health institutions (i.e., representing academic medical centers and health systems) to assess the institutional readiness and approach towards GenAI adoption. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The study highlights significant variations in governance models, with a strong preference for centralized decision-making but notable gaps in workforce training and ethical oversight. Moreover, 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 also reveals concerns regarding GenAI bias, data security, and stakeholder trust, which must be addressed to ensure the ethical and effective implementation of GenAI technologies. This study offers valuable insights into the challenges and opportunities of GenAI integration in healthcare, providing a roadmap for institutions aiming to leverage GenAI for improved quality of care and operational efficiency. |
| Competing Interests: | COMPETING INTERESTS I.G. Cohen is a member of the Bayer Bioethics Council, the Chair of the ethics advisory board for Illumina, and an advisor for World Class Health. He was also compensated for speaking at events organized by Philips with the Washington Post, by the Doctors Company, and attending the Transformational Therapeutics Leadership Forum organized by Galen Atlantica. He has been retained as an expert in health privacy, gender-affirming care, and reproductive technology lawsuits. |
| Σχόλια: | Update in: Npj Health Syst. 2025;2(1):4. doi: 10.1038/s44401-024-00009-w.. (PMID: 39872195) |
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| Grant Information: | UM1 TR004404 United States TR NCATS NIH HHS; T15 LM007079 United States LM NLM NIH HHS; UL1 TR001412 United States TR NCATS NIH HHS; R25 LM014213 United States LM NLM NIH HHS; UL1 TR001866 United States TR NCATS NIH HHS; UM1 TR004789 United States TR NCATS NIH HHS; T15 LM012495 United States LM NLM NIH HHS; UM1 TR004909 United States TR NCATS NIH HHS; UL1 TR002384 United States TR NCATS NIH HHS; UL1 TR001873 United States TR NCATS NIH HHS; UL1 TR001449 United States TR NCATS NIH HHS; R21 AA026954 United States AA NIAAA NIH HHS |
| Contributed Indexing: | Keywords: Clinical and Translational Research; GenAI; LLM |
| Entry Date(s): | Date Created: 20251001 Date Completed: 20251013 Latest Revision: 20260916 |
| Update Code: | 20260916 |
| PubMed Central ID: | PMC12478420 |
| PMID: | 41031081 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 2331-8422 |
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