What It Is

The Quality Management System (QMS) module provides the infrastructure for auditable, evaluable, and regulation-ready AI-assisted healthcare. It encompasses logging, monitoring, evaluation metrics, and compliance documentation across all GacruxAI products.

Rather than retrofitting compliance after deployment, QMS is built into the platform architecture. Every AI inference, user correction, and clinical outcome can be traced, measured, and reported for internal quality improvement and external regulatory requirements.

QMS Artifacts Include

Audit Logs: Timestamped inference records with user edits
Accuracy Reports: AI vs. final documentation concordance
Error Analysis: Categorized correction patterns by specialty
Compliance Docs: GDPR DPIAs, security assessments, SOC 2 prep

Who It's For

Stakeholders responsible for safe, compliant AI deployment in healthcare

Clinical Governance Teams

Medical directors, quality leads, and governance officers who need to demonstrate safe AI adoption to trust boards and regulators. Access dashboards showing AI accuracy and user override rates.

Information Governance

Data protection officers, IG leads, and security teams evaluating AI platforms for GDPR, NHS DSPT, and data handling requirements. Pre-built DPIA templates and data flow documentation.

Healthcare Administrators

Practice managers and operational leads tracking adoption metrics, usage patterns, and cost-benefit analysis. Reporting tools for procurement justification and efficiency measurement.

Core Components

Four pillars of quality management for clinical AI

1

Audit Trail

Complete logging of AI outputs, user edits, and final documentation. Traceable from inference to clinical record for incident investigation or quality review.

2

Evaluation Metrics

Standardized accuracy measurement: AI-to-human concordance rates, correction frequency by field, and specialty-specific performance benchmarks.

3

Compliance Docs

Pre-prepared documentation for GDPR Article 35 DPIAs, NHS DSPT submissions, and regulatory assessments. Updated as platform evolves.

4

Incident Response

Defined escalation pathways for AI errors, data breaches, or safety concerns. Root cause analysis templates and corrective action tracking.

Regulatory Alignment

Building toward compliance with evolving healthcare AI regulations

Data Protection

  • GDPR: Privacy-first architecture with data minimization, purpose limitation, and subject rights support
  • NHS DSPT: Alignment with Data Security and Protection Toolkit requirements
  • HIPAA: Technical safeguards for US deployment contexts

AI-Specific Frameworks

  • EU AI Act: Preparing for high-risk AI system requirements (documentation, human oversight, accuracy)
  • MHRA Software: Monitoring UK medical device classification for clinical decision support
  • FDA SaMD: Foundational compliance for US Software as Medical Device pathway

Note: GacruxAI products are designed with privacy-first architecture aligned to GDPR and HIPAA requirements. Formal certifications are on the product roadmap as we scale deployment. Current products are documentation tools that assist clinicians-final clinical decisions remain with the healthcare professional.

Status & Roadmap

Building quality infrastructure alongside product development

Current Status

  • Audit logging active in ClinixSummary
  • GDPR-aligned data handling implemented
  • Evaluation dashboards in development

Planned Features

  • NHS DSPT self-assessment completion
  • SOC 2 Type II certification
  • Real-time accuracy monitoring dashboard