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Use of large language models to optimize poison center charting.

Nikolaus MatslerLesley PepinShireen BanerjiChristopher HoyteKennon Heard
Published in: Clinical toxicology (Philadelphia, Pa.) (2024)
In this study, we demonstrate that large language models can generate coherent summaries of real-world poison center calls that are often acceptable for entry to the medical record as is. When errors were present, these were often fixed with the addition or deletion of a word or phrase, presenting an enormous opportunity for efficiency gains. Our future work will focus on implementing this process in a prospective fashion.
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