Overview
We built a medical assessment engine for a healthcare organization that needed to process structured patient data and generate risk stratification reports. The system had to meet strict regulatory requirements for data handling, auditability, and clinical accuracy.
Technical Challenges
Healthcare software operates under constraints that most software doesn't face: every data access must be logged, every decision must be explainable, and the system must degrade gracefully rather than produce incorrect results.
Data Pipeline Architecture
The assessment pipeline processes data through multiple stages:
- Ingestion — Structured data intake with schema validation
- Normalization — Converting disparate data formats to a canonical model
- Assessment — Rule-based evaluation with configurable risk thresholds
- Review — Human-in-the-loop validation for edge cases
- Reporting — Generation of structured assessment reports
Compliance and Auditability
Every data access, transformation, and decision point is logged with:
- User identity and role
- Timestamp and data snapshot
- Decision rationale and confidence scores
- Override history when clinicians modify automated assessments
Results
- Processing: 10,000+ assessments per day
- Accuracy: 94% agreement with specialist panel review
- Audit: Complete traceability for every assessment decision
- Compliance: Full regulatory audit passed on first review