Confidential healthcare platform
Real-time clinical guidance over a 10,000-rule graph database
What needed solving
Acute-care clinicians needed real-time, rule-based suggestions at the point of care, with strict PHI handling and sub-second response over thousands of interdependent rules.
How I built it
Modeled 10,000+ clinical rules in Neo4j, matched them with ElasticSearch + Redis caching for sub-second retrieval, streamed suggestions via Socket.io, and kept PHI client-side.
The details
Clinical Decision Support System for acute-care settings, delivering real-time, rule-based suggestions via a sidebar. A Neo4j graph models complex rule relationships, an ElasticSearch + Redis engine retrieves matches in sub-second time, and PHI is stripped client-side before transmission.
- Neo4j graph database for 10,000+ interdependent clinical rules
- ElasticSearch rule matching with fuzzy symptom variations
- Redis caching for sub-second retrieval at scale
- PHI compliance: client-side stripping before any API call
- Real-time sidebar suggestions via Socket.io
We can build something that lasts.
Tell me what you are building. I will come back with an honest take on approach, scope and timeline, usually within 24 hours.