Implementation Guide
AI Governance for Patient Grievance Responses
Govern AI-drafted grievance responses as an agent workflow, not a writing task. Define scope and risk tiers, give each drafting agent its own identity with least-privilege access to only the complaint data it needs, enforce policy at runtime on retrieval and tool calls, require a named human to approve before release, and keep an audit trail covering the prompt, retrieved records, draft, edits, approval, and sent version.
Start with scope and risk tiers
Define the scope of the grievance drafting workflow and assign risk tiers before an agent is put to work. Treat the task as an agent workflow rather than a writing task, so that each later control has a defined boundary to apply to.
Set data access boundaries and enforce policy at runtime
Give each drafting agent its own identity, with least-privilege access to only the complaint data it needs. Then enforce policy at runtime on retrieval and tool calls, so that requests are checked before they run. For example, policy can block clinical notes that fall outside the complaint's scope.
Place human approval where it creates accountability
Require a named human to approve each response before release. The workflow should block delivery when approval is missing, so that every letter that reaches a patient has an accountable reviewer.
Define the audit evidence you need to keep
Keep an audit trail that records each stage of the response, and make sure it can be exported as evidence. At minimum, it should cover:
- The prompt
- The retrieved records
- The draft
- Reviewer edits
- The approval
- The sent version
Controls across the grievance drafting workflow
Map each workflow stage to a control.
| Control | What it does |
|---|---|
| Identity and scope | Each drafting agent has its own identity and a defined task boundary. |
| Runtime policy | Retrieval and tool calls are checked against policy before they run. |
| Human approval | A named reviewer approves each letter before delivery. |
| Audit evidence | Every generated, changed, approved, and sent version is recorded. |
Criteria for evaluating enforcement technology
- Does each drafting agent have its own identity, with access limited to the complaint fields and systems the task needs?
- Can policy be enforced at runtime on tool calls and data retrieval, such as blocking clinical notes outside the complaint's scope?
- Can the workflow require a named human approver and block delivery when approval is missing?
- Does the audit trail capture prompt, retrieved records, draft, reviewer edits, approval, and sent version, and can it be exported as evidence?
- How are PHI in prompts, outputs, and logs handled, and how are retention rules applied to those records?
- Can tool approval workflows be applied when an agent requests a new tool or data source?
Review your grievance workflow controls
Talk with our team about applying agent identity, least-privilege access, runtime policy enforcement, and audit logging to AI-assisted patient communications.
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