PharmacyGPT: The AI Pharmacist
This work addresses the potential and limitations of AI in clinical pharmacy for improving patient care and healthcare solutions, though it appears incremental as it applies existing LLMs to a new domain.
The study introduced PharmacyGPT to evaluate large language models like ChatGPT and GPT-4 in emulating clinical pharmacists, using real ICU data from UNC Hospital to assess their capabilities in patient clustering, medication planning, and outcome forecasting.
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.