Documenting AI Chat Reviews in Clinical Records: Templates and Sample Notes

When a patient hands you a printout of an AI chat, what goes in the chart—and why it matters right now

Hook: Patients increasingly use large language models (LLMs) for health questions. Clinicians face real choices: ignore the chat, counsel from memory, or document a careful review. Each choice affects patient safety, continuity of care and legal exposure. This article gives practical, ready-to-use progress note templates and the legal and EHR strategies you need in 2026.

Why documenting AI chat reviews matters in 2026

In late 2024–2025 the routine use of consumer-facing AI assistants accelerated into clinical workflows: patients bring transcripts from chatbots, clinicians start using AI summarizers, and health systems pilot LLM-based intake tools. Regulators and professional societies emphasized transparency and documentation in 2025, and EHR vendors rolled out metadata fields and FHIR-friendly APIs to attach external content. That means documentation is no longer optional—it's part of risk management, clinical reasoning and the audit trail.

Top-level goals for any note that documents review of a patient’s AI chat

• Capture provenance: what the patient shared and where it came from.
• Record consent: patient agreement to share and have clinician review the AI output.
• Summarize clinical relevance: what in the chat altered assessment or plan.
• Document decisions: risk mitigation, referrals, tests, follow-up.
• Preserve an audit trail: timestamps, who reviewed what, and whether redactions were made.

Key elements every progress note should include

Below are the discrete fields you should capture in the medical record when you review a patient’s AI conversation. Use these as checkboxes inside your note template or EHR structured data entry.

1. Identifier — patient name, MRN, date/time of review, clinician name and role.
2. Source & provenance — platform name if known (e.g., ChatGPT, Generic AI assistant), how delivered (printout, PDF, screenshot, patient portal link).
3. Consent — patient's verbal or written consent to review and include the transcript.
4. Transcript handling — whether you attached the original to the record, redacted PHI, or summarized it only.
5. Summary of content — concise clinical summary highlighting symptoms, concerns, recommendations AI gave that are clinically relevant.
6. Clinical assessment — your interpretation, diagnostic reasoning, and how you evaluated AI statements.
7. Risk assessment & safety plan — suicidality, harm, medication issues and any immediate actions.
8. Plan — tests, referrals, education provided, documentation of refusal if applicable.
9. Follow-up — timing and responsible provider.
10. Audit metadata — file checksum or hash, reviewer ID, and retention notes.

How to phrase documentation: suggested language and rationale

Use language that is precise, neutral, and clinically focused. Avoid copying long verbatim AI output into the note unless clinically necessary; instead attach the transcript as an exhibit and summarize relevant parts in the body of the note.

Suggested phrasing examples

• Provenance: "Patient provided a PDF of an AI chat (platform: patient reports 'GenoAI', delivered via patient portal) on 01/08/2026."
• Consent: "Patient consented to clinician review and inclusion of the chat in the medical record (verbal consent documented)."
• Handling: "Full transcript attached to chart as 'AI_Chat_010826.pdf'; redacted patient identifiers per privacy protocol."
• Summary: "AI suggested medication X for symptom Y; patient reports following AI suggestion prior to visit."
• Assessment & Plan: "Clinician reviewed AI suggestions. Declined to endorse unverified medication change; ordered labs A and B, provided safer alternative and scheduled follow-up in 1 week."

Sample progress note templates clinicians can adapt

Below are modular templates. Copy-paste and adapt to your specialty and EHR. Each sample includes the minimal elements you should record.

1) Primary care – brief progress note (SOAP style)

S: Patient brings PDF of AI chat (platform reported by patient: "ChatX"). Patient states chat recommended starting Drug A for fatigue. Patient began Drug A 3 days ago and reports mild nausea.
O: Vitals stable. No acute distress. Medication list updated to include Drug A (patient-initiated).
A: Documented review of AI chat. No contraindication found for Drug A, but drug interaction with existing Drug B possible. Nausea likely side effect. Clinician does not endorse unsupervised medication changes based solely on AI output.
P: Stopped Drug A today. Ordered BMP and LFTs, counseled patient on side effects and proper prescribing pathways, provided printed guidance about verifying AI health advice. Follow-up call in 48 hours for lab results. Transcript attached to chart as 'AIchat_YYYYMMDD.pdf' (redacted for identifiers). Consent to include transcript documented.

2) Behavioral health – psychotherapy progress note (BIRP style)

Behavior: Patient presented a screenshot of an AI chat discussing self-harm ideation and coping strategies (patient reports using ChatBot Z on 01/05/2026).
Intervention: Clinician reviewed transcript with patient. Validated patient's distress; contrasted AI suggestions with evidence-based safety planning. Documented that AI provided non-evidence-based medication advice and unsafe steps.
Response: Patient acknowledged misunderstanding; agreed to follow therapist's safety plan. No acute safety risk at time of visit. Immediate resources provided.
Plan: Safety plan updated and uploaded to chart. Behavioral health team notified. Full transcript attached; redacted. Consent to include chat documented (verbal). Next psychotherapy session scheduled in 4 days.

3) Emergency / urgent assessment – focused risk note

Patient presented to ED after following AI instructions to self-administer high-dose OTC medication. On arrival: vital signs... Clinician reviewed AI transcript (attached as 'ED_AI_YYYYMMDD'). Documented immediate toxicology consult and activated regional poison control. Patient informed that AI content is included in medical record and may be shared with public health or safety authorities as required. Signed consent obtained when stable. Disposition: admitted for observation.

4) Consent-only encounter / patient shares chat, clinician defers review

Patient uploaded AI transcript to portal and requested clinician review. Patient informed clinician will review at next visit. Patient consented to upload and storage of the file in the medical record. Transcript attached as 'Portal_AI_YYYYMMDD'. No clinical decisions made at this time.

Consent language templates (short and expanded)

Use institutional policy to decide whether consent must be written. Below are two versions you can put in a visit note or a portal message.

Short consent (verbal)

"Patient consented to clinician review and inclusion of AI chat transcript in the medical record. Patient understands clinician may use information to guide care and that the transcript may be retained per health record policy. (Verbal consent documented.)"

Expanded consent (written/portal)

"I give permission for my clinician and care team to review and include the attached AI chat transcript in my medical record. I understand the transcript may contain personal or sensitive information. I authorize redaction of unnecessary identifiers before archival, and acknowledge the transcript may be accessed by those with access to my medical record, may be used for direct care, quality review, or legal requests. I understand the clinician may not endorse all AI-provided advice and will provide clinical recommendations based on standard care."

EHR best practices and creating a defensible audit trail

Modern EHRs support attachments and structured metadata; use them. The following steps protect patient privacy and create a clear audit trail for legal review:

• Attach the original file rather than pasting long transcripts into free text. Keep originals immutable when possible.
• Record metadata: date/time of upload, uploader identity (patient vs staff), source platform name (if known), file checksum or hash.
• Redaction logs: if you remove PHI from screenshots, document what and why in the note.
• Access control: restrict access to sensitive mental health transcripts in accordance with state rules (e.g., psychotherapy notes protection where applicable).
• Use structured fields: leverage new EHR fields for 'External Health Data' or 'Patient-Provided AI Content' when available to enable search and reporting.
• Versioning: label attachments so updates are clearly dated (AIchat_v1, AIchat_v2).

Legal considerations and common medicolegal questions

Below are practical legal issues clinicians and compliance teams often ask about when AI chats appear in the record.

Is the AI chat part of the medical record?

Yes, if the clinician or patient uploads the transcript and it is stored in the EHR it becomes part of the record. That means it's subject to discovery and privacy rules. Document consent and any redactions.

Can I refuse to review or include an AI chat?

Clinicians can set scope of practice limits (e.g., refuse to rely on AI-provided diagnoses). If you choose not to review the transcript, document that decision and the patient's preferences. If refusal could harm the patient (e.g., safety concerns), prioritize review and escalate as appropriate.

What about third-party storage and HIPAA?

If patients used a consumer AI tool, that tool may not be a HIPAA-covered entity. Inform patients of potential privacy risks when sharing PHI with commercial AI services. When attaching content to the EHR, ensure your local policy on PHI redaction and retention is followed.

Subpoenas and legal discovery

Once in the record, transcripts may be subpoenaed. Keep documentation of provenance, consent, and any redactions to support compliance with legal requests.

Special populations: minors and capacity

For minors and patients lacking capacity, follow state law regarding parental access and surrogate decision-makers when adding AI transcripts. Document capacity assessments and who provided consent.

Clinical reasoning examples — short vignettes showing documentation choices

Real-world examples make how to document clearer.

Vignette 1: Harmful AI advice averted

Patient used an AI tool which recommended stopping insulin. Clinician documented review, attached transcript, implemented emergency plan, and started patient on close monitoring. Note logged timestamp, clinician actions, and follow-up. The documentation supported safe care and later defended the decision when questioned by the patient's family.

Vignette 2: AI as a conversation starter

Patient obsessed with AI-provided diagnostic labels. Clinician used transcript to understand patient's worries, documented therapeutic refocus, and scheduled a medication review. The note recorded that AI content did not alter the clinical diagnosis but helped guide psychoeducation.

Advanced strategies and future-facing recommendations (2026 trends)

Expect these changes during 2026 and plan accordingly:

• Structured AI content fields: EHR vendors will standardize fields for patient-provided AI content (FHIR profiles and terminology tags).
• Automated summarizers: Increasing use of certified LLM summarizers that produce clinician-checked summaries with metadata and confidence scores.
• Interoperability: Claims and clinical decision support systems may query patient-shared AI transcripts for reconciliation; design your documentation to be machine-readable.
• Compliance automation: Tools to flag unredacted PHI or protected psychotherapy notes before archival.
• Education & credentialing: Expect training modules and continuing education credits about incorporating AI-origin data into clinical records.

Quick checklist for clinicians (use at point of care)

• Ask: How was this AI chat generated and why did the patient use it?
• Obtain and document consent to review and store the transcript.
• Attach the original file where possible; mark as patient-provided.
• Summarize clinically relevant parts in your note—do not paste the whole transcript unless needed.
• Document clinical decisions, safety measures, and follow-up clearly.
• Log metadata: uploader, timestamp, file name, and redaction actions.
• Coordinate with compliance for sensitive or legal concerns.

Final thoughts: make documentation a safety and continuity tool

AI chat transcripts are a growing part of the information clinicians must evaluate. Good documentation turns patient-provided AI content into actionable clinical data: it improves safety, clarifies reasoning for colleagues and auditors, and respects patients’ rights. Use the templates above as starting points and work with your compliance, legal and IT teams to create organization-level policies that map to your EHR's capabilities.

Call to action

Adapt one of the templates in this article now: document the provenance, obtain consent, and attach the original. Share a copy with your compliance officer and suggest adding a structured "Patient‑Provided AI Content" field in your EHR. If you’d like a downloadable checklist or EHR-ready snippet tailored to your specialty, contact your clinical informatics team or download our free template pack from thepatient.pro.

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