Evaluating Large Language Models for Safe and Effective Use in Healthcare Large language models (LLMs) like ChatGPT show promise for transforming healthcare delivery through natural language processing applications. However, concerns exist regarding the potential for generating misinformation, lacking transparency, and perpetuating biases. This presents challenges for the safe and ethical adoption of LLMs in clinical settings. A comprehensive framework is proposed to evaluate LLMs’ utility and governance when applied in healthcare. The framework incorporates natural language processing metrics along with assessment of translational value across capability, utility, and adoption dimensions. Governance components emphasizing fairness, transparency, trustworthiness, and accountability provide oversight for responsible LLM use. Together, these layers allow thorough, multifaceted analysis of benefits and risks to guide appropriate LLM adoption while ensuring patient safety. The suggested framework aids stakeholders in realizing LLMs’ potential while proactively addressing limitations, supporting informed decisions around their healthcare integration.