Automated Patient Intake Scoping System
Securing and Accelerating Scoping Workflows in Medical Networks
The Problem
Our client, a high-volume healthcare provider network, struggled with manual clinical intake scoping, which delayed diagnostic scheduling and introduced human error into EHR entries. Staff spent over 25 minutes per patient manually verifying symptoms and clinical documentation prior to diagnostic routing.
What We Built
Inovex AI designed and deployed a HIPAA-compliant conversational scoping agent that automates patient intake assessment. The system conducts secure symptoms verification, cross-references historical records, and translates natural language inputs into structured HL7/FHIR payloads for EHR ingestion. We built a validation layer that isolates clinical queries, ensuring all critical patient records are securely logged and indexed. The scoping system runs in a sandboxed, eBPF-monitored environment to guarantee maximum data privacy and threat isolation.
Tech Stack
- 🐍 Python (Backend Core)
- ⚡ FastAPI (High-Speed API)
- 🧠 LlamaIndex (RAG Framework)
- 🐘 PostgreSQL (PgVector Store)
- 🏥 FHIR / HL7 APIs
- 🐳 Docker (Sandbox Runtime)
Quantified Outcomes
Intake Scoping Time Saved
FHIR Generation Accuracy
Security or HIPAA Issues
"The custom scoping agent built by Inovex AI transformed our intake pipeline. By automating HL7 extraction and validation, our clinical coordinators now spend their time treating patients instead of manually reviewing scoping notes." — Director of Clinical Operations, Regional Diagnostic Network