HealthCare GraphRAG

Inspiration

The inspiration for this project came from working at my dad's friend's hospital, where I noticed significant revenue leakage stemming from denied insurance claims. Many denials were preventable but difficult to identify without advanced analytics.

What it does

This GraphRAG system transforms healthcare revenue cycle data into a knowledge graph, allowing hospital administrators to query it in natural language. It identifies patterns in denied claims, tracks revenue by diagnosis, and offers insights to reduce claim denials and optimize reimbursement rates.

How I built it

I built it using Synthea's synthetic healthcare dataset, NetworkX for graph modeling, ArangoDB for storage, and integrated GPT-4 with LangChain for natural language processing. The system visualizes patient journeys and uses a tool-based approach to intelligently route different query types.

Challenges we ran into

The main challenges included serializing complex healthcare data for graph storage, designing meaningful graph relationships that accurately model the revenue cycle, and developing dynamic query generation that produces appropriate AQL queries based on natural language questions.

Accomplishments that we're proud of

Successfully implementing GPU-accelerated graph analytics for large datasets and creating an intuitive interface that enables non-technical healthcare administrators to gain financial insights without knowing graph query languages.

What we learned

We learned how graph databases excel at revealing hidden relationships in healthcare data, how to design effective GraphRAG systems that combine structured and unstructured data, and the importance of domain-specific knowledge in healthcare revenue optimization.

What's next

Next steps include implementing predictive denial risk scoring, expanding to more healthcare datasets, adding real-time claim status monitoring, and developing specialized algorithms to recommend specific interventions for denied claims. And further expanding to more hospitals!