Streamlining Healthcare Compliance with AI

Independent Health collaborated with LangChain and Unstructured to address the complexities of managing the "Certificate of Coverage" (CoC), a detailed document crucial for policyholders. By exploring a Retrieval-Augmented Generation (RAG)-based architecture, they aimed to simplify the process of answering insurance policy questions. The study compared a baseline RAG with a nuanced Semi-Structured RAG architecture that utilizes Unstructured's data ingestion and transformation capabilities along with LangChain's Multi-Vector Retrieval. This approach effectively processes semi-structured data from CoC documents, which often consist of structured tables mixed with natural language text. The evaluation, conducted using LangChain’s platform LangSmith, demonstrated that the Semi-Structured RAG outperformed the baseline by accurately answering three out of four questions, highlighting the importance of tailored storage and retrieval strategies for semi-structured data. This initiative underscores the potential of advanced data processing tools to enhance document handling in healthcare insurance, ultimately improving service quality for policyholders.