Ambient scribe
Microsoft Dragon Copilot
Microsoft Dragon Copilot supports clinician-controlled documentation and nursing workflows. Clinicians approve the output. Declining encounter recording may still allow later AI processing of clinician dictation, and revocation does not remove data already anonymized.
Published September 8, 2026 as an AI-assisted draft. The public report separates documented facts, agency judgments and unresolved questions.
Summary judgment · 36 out of 100 toward patient-directed
Microsoft Dragon Copilot clinician documentation and nursing workflows, deployed by healthcare organizations. Institutional AI affecting the patient record, not a patient-operated assistant.
Mixed, institution-led
Microsoft Dragon Copilot supports clinician-controlled documentation and nursing workflows. Clinicians approve the output. Declining encounter recording may still allow later AI processing of clinician dictation, and revocation does not remove data already anonymized.
Patient agency
How this tool changes agency
Better documentation may support subsequent patient review, but the product assigns the patient no direct evidence-inspection or editing workflow in these materials. Clinician benefit is not evidence of increased patient authorship.
Local consent wording, access to transcripts, AI-specific correction routes, patient-facing release of outputs, and actual enforcement.
Patient agency assessment
Who sets and changes the goal?
The clinician sets the documentation task and approves its consequences. Refusing encounter recording can change capture method, but is not the same as preventing later AI processing of clinician dictation.
What can the patient understand, question, or do?
Better documentation may support subsequent patient review, but the product assigns the patient no direct evidence-inspection or editing workflow in these materials. Clinician benefit is not evidence of increased patient authorship.
Can the patient evaluate the conditions of use?
The lifecycle and revocation limits are specifically disclosed. Effective consent still depends on what the healthcare organization tells the patient and how requests are handled.
Text findings
Conditions of use
Published controls and their limits
The lifecycle and revocation limits are specifically disclosed. Effective consent still depends on what the healthcare organization tells the patient and how requests are handled.
What remains unknown?
Not tested or not established
Local consent wording, access to transcripts, AI-specific correction routes, patient-facing release of outputs, and actual enforcement.
Who evaluated this?
AI-assisted public-source draft
Vendor statements describe published conditions, not independently verified behavior. No clinical, security, accessibility, or legal validation is claimed. Earlier evidence remains dated in the report and history.
Sources checked
- https://learn.microsoft.com/en-us/industry/healthcare/dragon-copilot/whitepapers/privacy
- https://learn.microsoft.com/en-us/industry/healthcare/dragon-copilot/about/faqs
Source-specific findings and retrieval limitations are recorded in the full report.
Review provenance
Criteria
CAIHL-derived HugoScore framework and September 7 qualitative review priorities. Draft v1.2 numerical anchors remain unadopted.
Reviewer
AI-assisted public-source reassessment prepared in OpenAI Codex.
AI / model
OpenAI Codex / GPT-6
Human review
Hugo Campos authorized publication of these AI-assisted draft reassessments on September 8, 2026. This does not claim comprehensive human verification of every finding.
Review date
2026-09-08
Limitations
Local consent wording, access to transcripts, AI-specific correction routes, patient-facing release of outputs, and actual enforcement. No live product use, patient-data upload, account creation, code audit, clinical evaluation, or independent implementation validation.
Review method
Focused public-source reassessment using CAIHL: patient authority, critical capacity, and informed control. Existing evidence plus one focused primary-source pass and at most one targeted follow-up. No live product testing. Numerical scores remain provisional editorial placements, not a new calculation.
AI-assisted draft · Medium for product governance (AI-assisted draft)