The Digital Standardized Patient: An Artificial Intelligence Coach for Cultural Dexterity in Surgical Care.

Journal: Journal of the American College of Surgeons
Published Date: Jul 24, 2025

Abstract

BACKGROUND: Cultural dexterity, defined as the ability to effectively respond to diverse patient backgrounds, is crucial for equitable surgical care. Standardized patient (SP) encounters are proven tools for cultivating these skills but are resource-intensive and limited in scope. Large language models (LLMs) offer a scalable solution. This study evaluates the feasibility and perceived effectiveness of an LLM-based SP platform (SP-LLM) for cultural dexterity training among general surgery residents.

Authors

  • Arya S Rao
    Harvard Medical School, Boston, MA, USA.
  • Richard S Lee
    Department of Psychiatry & Behavioral Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
  • Ethan Bott
    Harvard Medical School, Boston, MA.
  • Sharon Jiang
    MIT-IBM Watson AI Lab, Cambridge, MA, USA.
  • Qiao Jiao
    Harvard Medical School, Boston, MA.
  • Brittany M Dacier
    Center for Surgery and Public Health, Department of Surgery, Brigham and Women's Hospital, Boston, MA.
  • Adil Haider
    Aga Khan University, Karachi, Pakistan.
  • Susan Farrell
    Harvard Medical School, Boston, MA.
  • Gezzer Ortega
    Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Marc D Succi
    Harvard Medical School, Boston, MA, USA. msucci@mgh.harvard.edu.

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