AI Agent Governance for Behavioral Health Utilization Review
AI agents used in behavioral health utilization review require a distinct, auditable non-human identity, least-privilege access scoped to each workflow stage, runtime policy enforcement at the tool-call level, and immutable audit logs, with a licensed clinical reviewer approving any adverse determination before it is finalized.
Why Agentic UR Requires a Different Governance Model
Mapping UR Workflow Stages to Governance Mechanisms
Each stage of a behavioral health UR workflow carries a different data exposure and decision risk, and governance controls should be scoped accordingly rather than applied as one blanket permission set.
Agent Identity and Least-Privilege Permissions
Core Governance Pillars for Agentic UR
Agent Identity
Distinct, non-human credentials separate from any human reviewer's identity.
Least-Privilege Access
Data access scoped to each UR workflow stage, not the full EHR or claims system.
Tool-Call Enforcement
Runtime policy checks on every EHR, claims, or UM system call an agent makes.
Immutable Audit Trail
Logged record of data accessed, model version, and output for each determination.
Evaluation Criteria Before Production Use
Compliance and clinical operations teams should confirm the following before allowing an AI agent to participate in behavioral health utilization review:
- Does the agent operate under a distinct, auditable non-human identity rather than a shared or human credential?
- Is data access scoped per UR workflow stage, limited to the minimum elements needed for that stage?
- Is every agent tool call, including EHR queries and claims lookups, captured in an immutable audit trail?
- Does a licensed clinical reviewer approve adverse determinations before they are finalized?
- Can permission scopes be verified as enforced at runtime, not only documented in policy?
Evaluate Runtime Governance Before Deploying AI Agents in UR
Compliance teams need to confirm agent identity, permission scoping, and audit logging are enforced at runtime, not just described in policy, before an AI agent touches behavioral health utilization review data.
Explore Runtime Governance