A Future of Self-Directed Patient Internet Research: Large Language Model-Based Tools Versus Standard Search Engines.

Journal: Annals of biomedical engineering
PMID: 40025252

Abstract

PURPOSE: As generalist large language models (LLMs) become more commonplace, patients will inevitably increasingly turn to these tools instead of traditional search engines. Here, we evaluate publicly available LLM-based chatbots as tools for patient education through physician review of responses provided by Google, Bard, GPT-3.5 and GPT-4 to commonly searched queries about prevalent chronic health conditions in the United States.

Authors

  • Arya Rao
    Harvard Medical School, Boston, MA, USA.
  • Andrew Mu
    Harvard Medical School, Boston, MA, USA.
  • Elizabeth Enichen
    Harvard Medical School, Boston, MA, USA.
  • Dhruva Gupta
    Harvard Medical School, Boston, MA, USA.
  • Nathan Hall
    Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, MA, USA.
  • Erica Koranteng
    Harvard Medical School, Boston, MA, USA.
  • William Marks
    Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Massachusetts General Hospital, Boston, MA, USA.
  • Michael J Senter-Zapata
    Harvard Medical School, Boston, MA, USA.
  • David C Whitehead
    Harvard Medical School, Boston, MA, USA.
  • Benjamin A White
    Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Sanjay Saini
    Harvard Medical School, Boston, MA, USA.
  • Adam B Landman
    Harvard Medical School, Boston, MA, USA.
  • Marc D Succi
    Harvard Medical School, Boston, MA, USA. msucci@mgh.harvard.edu.

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