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Project template

Use case

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Process Regulated Data with Full Compliance

This project proposal demonstrates secure, compliant data streaming and processing for regulated industries such as healthcare. The Quix platform can process patient data, clinical metrics, and operational insights while maintaining strict audit trails and data lineage. Built for healthcare teams who need guaranteed data integrity and transparent processing, the system includes HIPAA-compliant data transformation services and PII protection measures. Each component provides full code visibility and comprehensive audit logging.

Use cases:

PII protection

Created by:

Quix

An architecture diagram showing a real time data preprocessing pipeline or DAG

Main project components

Clinical System CDC

Subscribe to changes from Electronic Health Records (EHR) and clinical databases with guaranteed data consistency

Patient Monitor Feed

Process real-time data streams from medical devices and patient monitoring systems.

Clinical Data Standardization

Transform varied healthcare data formats into FHIR-compliant structures while maintaining data lineage.

PII Protection Service

Process standardized FHIR data to detect and handle Protected Health Information according to compliance requirements, with full audit logging.

Clinical Metrics Processing

Calculate real-time clinical quality measures and operational KPIs with transparent processing steps.

Azure Monitor Sink

Stream audit logs, data lineage, and compliance events directly to Azure Monitor. Captures all data transformations, access patterns, and PII handling events with detailed timestamps and Azure AD identities. Supports configurable retention policies for HIPAA compliance and integrates with Microsoft Sentinel for security analytics.

Secure Data Lake Export

Write processed clinical data to HIPAA-compliant storage with end-to-end encryption

Technologies used

Using this template

This is a proposal for a project template that demonstrates a secure and compliant data pipeline for clinical data. This data could be used for analytics, training machine learning models, to trigger external services such as alerting systems.

The proposed components emphasize:

Complete visibility into data processing through Git-tracked code
ISO certification compliance built into each step
Comprehensive audit trails for all data movements
Transparent PII handling with documented procedures
End-to-end data lineage tracking

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