AI Compliance & Audit for Healthcare
Healthcare AI systems face the strictest regulatory scrutiny on earth — EU AI Act high-risk classification, FDA lifecycle oversight, HIPAA security requirements, and emerging frameworks across Latin America.
EthiCompass evaluates every clinical AI system across 7 scientifically validated dimensions, producing the immutable evidence regulators, patients, and your board require.
Healthcare AI regulation is converging globally. Whether you operate in Berlin, Boston, or São Paulo, regulators are requiring the same thing: defensible evidence that your AI systems are safe, fair, and transparent.
European Union
Medical device AI classified as high-risk under Article 6(1)(b). Compliance with Articles 9 – 15 required by August 2027. Notified bodies will conduct integrated audits covering both MDR/IVDR and AI Act requirements simultaneously.
Maximum penalty: EUR 35 million or 7% of global turnover.
United States
1,250+ AI medical devices authorized by FDA. New lifecycle guidance requires ongoing bias monitoring — not just one-time submission. HIPAA Security Rule update mandates AI system inventories and encrypted processing. Colorado AI Act takes effect June 2026.
HIPAA penalty: $1.5M – $15M per violation category.
Latin America
Health AI classified as high-risk under Brazil ' s AI regulation bill. ANVISA and Mexico ' s COFEPRIS signed mutual recognition for AI medical devices in August 2025. LGPD classifies health data as sensitive — explicit consent required.
LGPD penalty: Up to 2% of Brazilian revenue.
Documented Failures
These are not hypothetical risks. These are documented failures that are shaping healthcare AI regulation worldwide.
CLINICAL BIAS
Widely deployed sepsis prediction tools showed a 67% false alert rate and significant performance degradation across racial groups. Result: patient harm, wasted clinical resources, regulatory investigations into algorithmic bias.
EthiCompass dimension: Discrimination & Fairness
DIAGNOSTIC INEQUITY
Diagnostic AI trained predominantly on lighter skin tones showed 15–20% accuracy drops on darker skin, leading to delayed or missed diagnoses for underserved populations.
EthiCompass dimension: Robustness & Resilience
DOCUMENTATION HALLUCINATION
Multiple health systems have reported hallucinated medical information appearing in AI-assisted clinical documentation — creating malpractice liability and patient safety risks.
EthiCompass dimension: Factuality & Accuracy
INSURANCE AUTOMATION BIAS
AI-driven prior authorization systems have been shown to deny claims at higher rates in lower-income ZIP codes — triggering regulatory investigations in multiple US states.
EthiCompass dimension: Discrimination & Fairness
Our evaluation framework was developed by PhD researchers and validated through peer-reviewed publications. Each dimension maps to specific regulatory requirements across EU, US, and Latin American healthcare frameworks.
01
Detects demographic bias in clinical algorithms, diagnostic accuracy gaps across patient populations, and discriminatory patterns in resource allocation AI.
EU AI Act Art 10, FDA bias monitoring, Colorado AI Act
02
Flags inappropriate, insensitive, or harmful content in AI-generated patient communications, clinical summaries, and patient-facing health information.
HIPAA patient rights, California AB 3030, Brazil 2338
03
Ensures every clinical AI recommendation includes traceable reasoning — which inputs contributed, what thresholds were applied, and why the recommendation was made.
EU AI Act Art 13, FDA PCCP, Brazil 2338
04
Detects PHI exposure in AI outputs, enforces minimum-necessary principles, and verifies that AI systems do not leak sensitive health data across processing boundaries.
HIPAA Security Rule, LGPD, EU AI Act + GDPR
05
Identifies hallucinated medical information, verifies clinical claims against medical knowledge bases, and flags AI outputs that contradict established medical evidence.
FDA clinical accuracy, MDR clinical evaluation, ANVISA RDC 751
06
Tests AI system stability under adversarial inputs, data drift, and edge cases — ensuring clinical AI performs reliably across diverse patient populations and conditions.
EU AI Act Art 15, FDA lifecycle monitoring, DORA
07
Maps AI system behavior directly to applicable regulations — EU AI Act articles, HIPAA provisions, LGPD requirements, FDA guidance — producing audit-ready compliance evidence.
All applicable frameworks: multi-jurisdictional
High-Risk Applications
Healthcare organizations deploy AI across clinical, operational, and patient-facing workflows. Each creates distinct compliance obligations.
AI-Assisted Diagnosis & Treatment
Clinical decision support systems are classified as high-risk under the EU AI Act and regulated as medical devices. Multi-jurisdictional requirements apply across every market where these systems are deployed.
Compliance requirements
EthiCompass evaluates diagnostic accuracy across patient populations, bias in treatment recommendations, explainability of clinical reasoning, and continuous performance monitoring.
AI-Generated Messaging at Scale
Patient-facing AI generates appointment reminders, test result notifications, and care instructions. Each message carries PHI exposure risk, health literacy failures, and regulatory liability.
Compliance requirements
EthiCompass evaluates PHI exposure, health literacy levels, medical accuracy, and consent compliance across every AI-generated patient communication.
Software as a Medical Device Lifecycle
SaMD products require continuous compliance across their entire lifecycle — from initial authorization through ongoing monitoring. Regulatory convergence means a single product may need to satisfy EU, US, and Brazilian requirements simultaneously.
Compliance requirements
EthiCompass evaluates SaMD performance drift, algorithm change impact, cross-population robustness, and generates the continuous evidence lifecycle regulators require.
Underwriting, Prior Auth, Claims Processing
AI systems used in insurance underwriting, prior authorization, and claims adjudication face regulatory scrutiny for discriminatory outcomes and lack of transparency in automated decisions.
Compliance requirements
EthiCompass evaluates pricing fairness across demographics, denial pattern analysis, explainability of coverage decisions, and compliance with automated decision-making regulations.
AI-Assisted Records & Revenue Cycle
AI-assisted clinical documentation and medical coding creates new risk categories — from hallucinated medical information in patient records to coding errors that trigger fraud investigations.
Compliance requirements
EthiCompass evaluates clinical accuracy of AI-generated notes, hallucination detection, coding consistency, and maintains immutable audit trails for every AI-assisted document.
Peer-Reviewed Methodology
In healthcare, peer-reviewed methodology is not a differentiator — it is a prerequisite. Regulators, notified bodies, and clinical safety officers demand defensible, transparent evaluation frameworks. Proprietary black-box scoring is not acceptable when patient safety is at stake.
EthiCompass ' s 7-dimension framework was developed by PhD researchers in AI ethics, clinical bias detection, and regulatory compliance. It is validated through peer-reviewed publications — not vendor whitepapers. The framework produces 39+ quantitative metrics across 7 dimensions, each mapped to specific regulatory requirements in the EU, US, and Latin America.
When an FDA reviewer, a notified body auditor, or a HIPAA compliance officer asks how you evaluate your clinical AI systems, you need a methodology that has been subjected to the same rigor they apply to clinical evidence. That is what peer-reviewed validation provides.
OneCheck
Your Clinical AI Compliance Baseline
Know where you stand in 3 weeks.
Best for: Healthcare organizations that need to understand their clinical AI compliance posture across multiple jurisdictions.
Enterprise
Full PlatformContinuous Clinical AI Compliance
Ongoing monitoring for every AI system in production.
Best for: Health systems and medtech companies deploying AI at scale that need continuous compliance assurance across multiple regulations and jurisdictions.
Risk Category
EU AI Act Non-Compliance
Exposure
Up to €35M or 7% global turnover
With EthiCompass
Continuous conformity evidence across Art 9–15
Risk Category
MDR/IVDR Violation
Exposure
Market withdrawal + €5M–€20M
With EthiCompass
Integrated AI + medical device compliance documentation
Risk Category
HIPAA Breach
Exposure
$1.5M–$15M per violation category
With EthiCompass
PHI exposure monitoring across all AI outputs
Risk Category
FDA Enforcement
Exposure
Warning letter + market suspension
With EthiCompass
Lifecycle monitoring aligned with PCCP framework
Risk Category
LGPD Violation
Exposure
Up to 2% of Brazilian revenue
With EthiCompass
Automated consent verification and data minimization
Risk Category
State-Level AI Laws
Exposure
Varies: $10K–$20K per violation
With EthiCompass
Multi-jurisdictional mapping updated continuously
Healthcare AI compliance is not a US problem, a European problem, or a Latin American problem. It is a global obligation. EthiCompass provides the only scientifically validated methodology that maps your clinical AI systems to regulatory requirements across every jurisdiction where you operate.