Harnessing Large Language Models to Promote Attainment of ACGME Competencies in Child Psychiatry

Abstract

Artificial intelligence and large language models (LLMs) such as ChatGPT are spurring both enthusiasm and trepidation within the medical education community. Here, we explore the application of LLMs in medical education in child and adolescent psychiatry in pursuit of the Accreditation Council for Graduate Medical Education (ACGME) Program Requirements for Graduate Medical Education. In particular, we demonstrate how one might leverage LLMs to achieve ACGME competencies in clinical skills in the major treatment modalities. We use the voice feature of the ChatGPT app to simulate a patient interaction during which the provider must engage in crisis intervention. We discuss the realistic nature of the scenario produced by ChatGPT, the ability of ChatGPT to serve as a clinical coach, and the opportunities afforded by prompt engineering. Interacting with LLMs throughout medical education in child psychiatry both promotes innovation and fosters an understanding of their limitations in clinical care. Fluency in the language of these models is of the utmost importance as their influence in health care continues to expand.

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