Evaluating the Performance of Large Language Models on Palliative Care Test Questions: A Mixed Methods Study

The authors aimed to evaluate the performance of large language models (LLMs) on palliative care-related test questions and their ability to explain their answer choices. The study found that both LLMs answered 96% of the questions correctly and produced explanations that were rated more favorably than those from the established answer key. Reviewer feedback highlighted themes such as clarity and educational value in the LLM-generated explanations.