In this study, we introduce PharmacyGPT, a novel framework to assess the capabilities of large language models (LLMs) such as ChatGPT and GPT-4 in emulating the role of clinical pharmacists. Our methodology encompasses the utilization of LLMs to generate comprehensible patient clusters, formulate medication plans, and forecast patient outcomes. We conduct our investigation using real data acquired from the intensive care unit (ICU) at the University of North Carolina Chapel Hill (UNC) Hospital. Our analysis offers valuable insights into the potential applications and limitations of LLMs in the field of clinical pharmacy, with implications for both patient care and the development of future AI-driven healthcare solutions. By evaluating the performance of PharmacyGPT, we aim to contribute to the ongoing discourse surrounding the integration of artificial intelligence in healthcare settings, ultimately promoting the responsible and efficacious use of such technologies.

翻译：本研究提出了PharmacyGPT，一个新颖的框架，用于评估ChatGPT和GPT-4等大型语言模型在模拟临床药师角色方面的能力。我们的方法包括利用大型语言模型生成可理解的患者聚类、制定用药方案并预测患者结果。我们使用来自北卡罗来纳大学教堂山分校医院重症监护室的真实数据开展研究。我们的分析为大型语言模型在临床药学领域的潜在应用与局限性提供了宝贵见解，对患者护理及未来人工智能驱动的医疗解决方案开发具有启示意义。通过评估PharmacyGPT的性能，我们旨在促进关于人工智能融入医疗场景的持续讨论，最终推动此类技术的负责任且高效的应用。