Generative Artificial Intelligence for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations: An ISPOR Working Group Report.

Journal: Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
PMID: 39536966

Abstract

OBJECTIVES: To provide an introduction to the uses of generative artificial intelligence (AI) and foundation models, including large language models, in the field of health technology assessment (HTA).

Authors

  • Rachael L Fleurence
    National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD, United States. Electronic address: Rachael.fleurence@nih.gov.
  • Jiang Bian
    Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, United States of America.
  • Xiaoyan Wang
    Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China.
  • Hua Xu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Dalia Dawoud
    National Institute for Health and Care Excellence, London, United Kingdom; Cairo University, Faculty of Pharmacy, Cairo, Egypt.
  • Mitchell Higashi
    ISPOR-The Professional Society for Health Economics and Outcomes Research, Lawrenceville, NJ, USA.
  • Jagpreet Chhatwal
    Institute for Technology Assessment, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Center for Health Decision Science, Harvard University, Boston, MA, United States.

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