text: **JAMA Network Open | Emergency Medicine**
  
  evaluation frameworks may not address the anticipated effect LLM performance limitations could 
  have on patient safety.38-41 
  
  In this study, we aim to expand on prior work of clinical summarization to rigorously evaluate 
  
  the outcomes of a fine-tuned model developed to generate accurate and safe summaries of the care 
  
  rendered during an ED visit, with the long-term goal of integrating automated, structured EM-to-IP 
  
  handoff notes into an EHR-based electronic handoff admission workflow (see eAppendix 1 in 
  
  Supplement 1). We fine-tune pretrained LLMs on well curated datasets of structured and 
  
  unstructured EHR data from the ED encounter to summarize the patient’s ED care. We improved the 
  
  correctness of model generations and customized the summaries in a structured format designed 
  
  by a team of EM and internal medicine physician leaders for optimal usefulness. We proposed a novel 
  
  patient safety-focused LLM evaluation framework to examine the LLM-generated handoff notes’ 
  
  quality and accuracy and the downstream patient safety implications of any identified inaccuracies. 
  
  To evaluate noninferiority, we compared the LLM-generated handoff notes with the preexisting 
  
  physician-written EM-to-IP handoff notes as the active control, using both the proposed patient 