LLM-Orchestrated Conformance Checking in Stroke Care Without Computer-Interpretable Guidelines
Researchers have developed a framework using Large Language Models (LLMs) to check if patient care aligns with clinical guidelines, even when those guidelines aren't in a machine-readable format. This system extracts patient data from unstructured texts and interprets rules from guideline documents to assess compliance. In a study of stroke care at Alessandria Hospital, the LLM-based approach found that over 86% of patient traces adhered to the guidelines. AI
IMPACT Enables automated healthcare compliance checks using unstructured data, potentially improving quality and efficiency.