Automated Data Use Agreement (DUA) Compliance Check Workflow

Manual DUA compliance checks are slow, error-prone, and create significant liability. This workflow embeds a rule engine that validates every cohort query and data export against the specific terms of each IRB-approved DUA (e.g., approved researchers, data fields, purpose limitations, retention periods). It blocks non-compliant actions before they occur, creating a continuous, auditable control layer that satisfies regulators and legal counsel.

Researchers no longer wait days for manual compliance sign-off. The workflow integrates directly with data exploration tools (e.g., i2b2, TriNetX, custom portals) and APIs, providing near-instant, programmatic approval for compliant queries. This removes a major friction point in the research lifecycle, enabling faster hypothesis testing and cohort discovery without sacrificing governance.

Instead of manually compiling evidence for audits, the workflow automatically generates a complete, immutable audit trail. Every check, its rationale (citing specific DUA clauses), and the resulting action (allow/block/flag) is logged with user, timestamp, and data context. This creates inspection-ready reporting on demand, slashing the administrative cost of compliance demonstrations by IRBs and privacy officers.

By automating the enforcement of granular consent stipulations (e.g., 'opt-out of secondary research', 'genomic data only for cancer studies'), the workflow enables research operations at scale while maintaining patient trust. It allows data stewards to safely grant broader data access to researchers, confident that the system itself will enforce the most restrictive applicable rules, unlocking more data utility without increasing risk.

The workflow is built as an orchestration layer that connects to your existing systems. It pulls active DUA terms from IRB management systems (like Huron IRB or Click), ingests real-time consent status from patient portals or EHRs, and exposes compliance APIs to data query platforms. Implementation focuses on API agents, event-driven logic in LangGraph or Temporal, and synchronous validation hooks—not replacing core systems.

Beyond blocking violations, the workflow analyzes query patterns to identify systemic risks—like a researcher frequently testing the boundaries of a DUA or a surge in requests for a sensitive data field. It alerts compliance officers to these patterns, enabling proactive policy refinement or training. This shifts the operating model from reactive firefighting to intelligent, data-driven governance.

The core rule system that ingests structured Data Use Agreements (DUAs) and patient consent forms from IRB platforms (e.g., IRBNet, Veeva SiteVault) and clinical systems. It translates legal stipulations—such as approved research purposes, data fields, expiration dates, and re-contact permissions—into executable policy objects. This engine is queried for every patient data access, ensuring actions are contractually authorized before any PHI is retrieved or processed.

A dedicated orchestration agent that intercepts each cohort query (e.g., 'find all Stage III NSCLC patients with EGFR exon 19 deletions'). It decomposes the request into its constituent data elements and intended use, then calls the policy engine for an authorization check. The agent logs the rationale, attaches the governing DUA ID, and either green-lights the query for execution or flags it for human review, preventing unauthorized data exposure at the point of request.

A monitoring subsystem that analyzes query logs, data egress patterns, and user behavior against the active policy baseline. It uses pattern recognition to detect potential violations, such as a user attempting to aggregate data beyond the scope of a DUA or accessing a cohort after a consent withdrawal. Confirmed or high-risk anomalies trigger immediate alerts to compliance officers via Slack, ServiceNow, or email with full context for investigation.

An automated documentation workflow that creates an immutable, query-by-query audit trail. For every compliance decision, it records the user, patient cohort, data elements accessed, the specific DUA or consent clause invoked, and the system's rationale. This log is formatted into inspection-ready reports for IRB or regulatory audits, providing defensible evidence of continuous compliance oversight without manual log compilation.

The control plane for exceptions and overrides. When the validation agent flags a query as non-compliant or of uncertain authorization, it is routed to a configured review queue in a system like Jira or ServiceNow. Designated compliance officers or principal investigators receive the request with the agent's reasoning and can approve, deny, or request modification. Approved exceptions are logged with human rationale, maintaining oversight while allowing for necessary flexibility.

Pre-built API agents and adapters that maintain live sync with source systems of truth. These connectors pull updated DUAs from IRB management software, ingest consent status changes from the EHR or eConsent platform, and push violation alerts back into operational systems like a CTMS or security incident platform. This bidirectional integration ensures the compliance layer operates on current, authoritative data without creating siloed manual updates.