Utilization management AI decisions face URAC and NCQA audit requirements. InferTrust™ provides tamper-evident records proving each AI determination was made co
Utilization management decisions, including concurrent review, retrospective review, and discharge planning, increasingly incorporate AI to process clinical data and recommend determinations. URAC and NCQA accreditation standards are evolving to address AI governance in UM workflows, and plans that cannot demonstrate verifiable oversight face accreditation risk.
InferTrust™ Payer captures the full decision event at each AI-assisted UM determination: the model configuration, the clinical criteria and InterQual or MCG guidelines in effect, the recommendation produced (UM_APPROVE, UM_DENY, UM_PARTIAL, UM_PEER_REVIEW, or UM_APPEAL_TRIGGERED), and the subsequent human review actions. Each record is cryptographically bound into the hash chain, making it tamper-evident and independently verifiable.
Accreditation bodies evaluate whether organizations have adequate oversight of AI in clinical operations. InferTrust™ provides the evidence layer: auditors can verify that every AI-assisted UM decision was governed by a specific policy, processed through a configured workflow, and subject to appropriate human oversight. This moves UM AI governance from narrative descriptions to verifiable proof.
UM denials are a frequent source of litigation and regulatory complaints. When an organization can produce a cryptographically verifiable record showing exactly how the AI evaluated a case, which criteria were applied, and what human review followed, it significantly strengthens its legal defensibility compared to organizations that can only produce mutable application logs.