Ambient Scribe Audio Retention Policy: Governing Recordings After the Note Is Signed
Set deletion shortly after note signature as the default for ambient scribe audio, and allow retention only as a documented, time-bound exception with a named purpose, owner, and access rule. Enforce the policy in the contract and in every system that holds audio, including backups and subprocessors, and require deletion evidence you can audit. Confirm jurisdiction-specific legal requirements with counsel before finalizing.
Treat the signed note as a lifecycle trigger
When the clinician signs the note, the primary purpose of the ambient scribe audio has been met. Treat that signature as the event that triggers a lifecycle decision for the recording, rather than leaving the audio in place by default.
Post-signature audio lifecycle
- TriggerClinician signs the note and the primary purpose of the audio is met.
- DecisionDelete by default, or retain under a documented exception.
- EnforcementContract terms and technical controls across every storage location.
- EvidenceDeletion logs, attestations, and audit records that verify the policy.
Three post-signature retention options
After signature, audio is either deleted, retained for a fixed period, or retained indefinitely. The vendor questions later in this guide use the same three outcomes. The recommended default is deletion shortly after note signature, with any retention treated as an exception.
| Outcome after signature | Recommended position |
|---|---|
| Deleted | Default. Delete shortly after note signature. |
| Retained for a fixed period | Allowed only as a documented, time-bound exception with a named purpose, owner, and access rule. |
| Retained indefinitely | Not consistent with a time-bound exception, so it should not be a standing default. |
Criteria for justifying any retention
Retention should be permitted only when the exception is written down and limited in time. Each exception should record:
- A named purpose for keeping the audio.
- A named owner who is accountable for the retained audio.
- An access rule that defines who may reach the audio.
- A time limit, so that the exception ends rather than continuing indefinitely.
Enforce deletion in every place audio lives
A policy only holds if it is enforced in the contract and in every system that holds audio, including backups and subprocessors. Use this checklist to confirm that technical controls cover each location.
- Inventory each storage location, cache, backup, and subprocessor that handles audio.
- Set a retention timer tied to the signature event, with a documented maximum.
- Define backup expiry behavior and its maximum duration.
- Restrict and log access to retained audio by role.
- Provide a legal hold mechanism that pauses deletion and records who invoked it.
- Record each deletion event in a log the enterprise can review.
Audit evidence and where runtime governance fits
Require deletion evidence that you can audit. Acceptable forms include deletion logs, attestations, and audit records that verify the policy was applied, including the log of each deletion event that the enterprise can review.
Runtime governance fits here by applying policy enforcement and audit logging to AI workflows that handle sensitive data, so that lifecycle controls are enforced and recorded as the workflow runs.
Questions to put to ambient scribe vendors
Use these questions to verify how a vendor handles audio after the note is signed.
- Is audio deleted, retained for a fixed period, or retained indefinitely after signing, and can we configure this?
- Is audio used for model training, quality review, or product improvement, and is that opt-in, opt-out, or prohibited by contract?
- Which storage locations, backups, caches, logs, and subprocessors hold audio, and does deletion reach each one?
- What deletion evidence can you provide: logs, certificates, or attestations?
- How do legal holds, disputes, and discovery requests affect retained or deleted audio?
- What happens to audio and derived data when the contract ends?
Define lifecycle controls for AI-processed data
Talk with our team about applying runtime policy enforcement and audit logging to AI workflows that handle sensitive data.
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