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Performance of Three Conversational Artificial Intelligence Agents in Defining End-of-Life Care Terms

Sonal Admane, Min Ji Kim, Akhila Reddy, Michael Tang, Yuchieh Kathryn Chang, Kao Swi Karina Shih, Maxine De La Cruz, Sammuel Jumary Cepeda, Eduardo Bruera, David Hui

Research output: Contribution to journal › Article › peer-review

Abstract

Background: Conversational artificial intelligence agents, or chatbots, are a transformational technology understudied in end-of-life care. Methods: OpenAI’s ChatGPT, Google’s Bard, and Microsoft’s Bing were asked to define “terminally ill,” “end of life,” “transitions of care,” “actively dying,” and provide three references. Outputs were scored by six physicians on a scale of 0-10 for accuracy, comprehensiveness, and credibility. Flesch-Kincaid Grade Level and Flesch Reading Ease (FRE) were used to calculate readability. Results: Mean (standard deviation) scores for accuracy were 9 (1.9) for ChatGPT, 7.5 (2.4) for Bard, and 8.3 (2.4) for Bing. Comprehensiveness scores averaged 8.5 (1.7) for ChatGPT, 7.3 (2.1) for Bard, and 6.5 (2.3) for Bing. Credibility was low with a mean score of 3 (1.8). The mean FRE score was 41.7, and the mean grade level was 14.1, indicating low readability. Conclusion: Chatbot outputs had important deficiencies that necessitated clinician oversight to prevent misinformation.

Original languageEnglish (US)
Pages (from-to)1102-1107
Number of pages6
JournalJournal of palliative medicine
Volume28
Issue number8
DOIs
StatePublished - Aug 1 2025

Keywords

  • conversational artificial intelligence
  • end-of-life care
  • large language models
  • palliative care

ASJC Scopus subject areas

  • General Nursing
  • Anesthesiology and Pain Medicine

Divisions

  • Palliative Care

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