InferTrust Clinical: Cryptographic Proof for Every Healthcare AI Decision

HIPAA-compliant audit trails for every clinical AI decision. Radiology triage, decision support, FDA SaMD compliance. Evidence that survives malpractice discovery.

Healthcare AI Pain Points

Healthcare organizations deploying AI face regulatory, legal, and operational challenges that generic observability tools were never designed to address.

Malpractice Exposure: When AI assists a clinical decision that leads to patient harm, the provider needs to prove what the AI recommended and whether a human overrode or followed the recommendation. Without verifiable records, the provider is defenseless in discovery.
FDA SaMD Compliance: Software as a Medical Device requires documented quality systems and the ability to trace every output back to the exact software version. The FDA Predetermined Change Control Plan (PCCP) framework demands version tracking that manual processes cannot sustain.
HIPAA Audit Trail Requirements: HIPAA requires audit trails for systems that access or process PHI. Traditional logging creates copies of sensitive data. InferTrust Clinical hashes inputs without storing PHI.
Post-Market Surveillance: Once an AI medical device is in production, the manufacturer must monitor its performance continuously. Decision records with confidence scores and escalation rates provide the evidence base for post-market surveillance.
Interoperability and EHR Integration: Clinical AI pulls data from EHR systems and returns recommendations. The handoff between systems creates gaps in accountability. InferTrust Clinical signs at the inference boundary, capturing exactly what the model saw and decided regardless of upstream data flow.

What InferTrust Clinical Captures

For each type of healthcare AI decision, InferTrust Clinical records specific fields in its cryptographically signed decision record.

Radiology AI Triage

Model version
Study type
Confidence score
Triage priority assigned
Policy in force
Timestamp and sequence ID
Input hash covers imaging features without storing the image

Clinical Decision Support

Model version
Patient feature hash (no PHI)
Recommendation action (alert, suggest, suppress)
Confidence score
Clinical policy version
Timestamp

Prior Authorization AI

Model version
Coverage criteria hash
Determination (approve, deny, pend)
Confidence score
CMS/payer policy version
Timestamp

Compliance Mapping

How InferTrust Clinical maps to the specific requirements of healthcare regulatory frameworks.

Regulation	Requirement	What InferTrust Clinical Provides
HIPAA Security Rule	Technical safeguards: encryption, access controls, audit controls	Cryptographic audit trail, no PHI in decision records (input hashing), tamper-evident logs
FDA 21 CFR Part 820 (QSR)	Design controls, production controls, CAPA	Model version tracking, policy version tracking, drift detection via confidence distribution monitoring
FDA SaMD PCCP	Predetermined change control plans for AI/ML devices	Cryptographic binding of model version to every inference, enabling automated verification that only approved versions are in production
Joint Commission	Ongoing Professional Practice Evaluation	Decision records that support AI-assisted clinical performance monitoring

Healthcare AI Workflows

Radiology Triage Workflow

Image acquired
AI model processes study
InferTrust captures inference (model version, confidence, triage priority, input hash)
Signed record sealed
If confidence above threshold: priority assigned automatically with proof
If below threshold: escalated to radiologist with proof of escalation

Clinical Decision Support Workflow

Clinician opens patient record
CDS model runs on patient data
InferTrust captures inference
Signed record sealed
Alert or recommendation displayed to clinician
Clinician action recorded