AI Scribe for Telehealth — Virtual Visit Documentation
AI Scribe for Telehealth
The visit is virtual. The note is still written before it ends.
Peerbits engineers AI scribe solutions purpose-built for telehealth — capturing virtual-visit audio directly from your video platform, generating a structured draft note, and delivering the physician-reviewed documentation to supported EHR environments. Designed to fit into existing telehealth workflows.
DR. PATEL · PHYSICIAN
PATIENT · HOME
97%
accuracy capturing telehealth audio
<60s
note ready after call ends
8+
telehealth platforms supported
0
workflow changes required
Definition
What Is an AI Scribe for Telehealth?
An AI scribe for telehealth captures the audio of a virtual visit, generates a structured draft clinical note, and supports delivery of the physician-reviewed note to a connected EHR — engineered specifically for the audio and workflow conditions of video and virtual-care encounters, which differ from an in-person visit.
This page focuses on telehealth-specific technical and workflow conditions. For the underlying capabilities in general, see ambient listening and clinical note generation.
The Problem
Why Telehealth Needs Purpose-Built AI Documentation
A documentation tool built for an in-person exam room and simply pointed at a video call carries assumptions that don't hold for telehealth:
Compressed Audio
Video call audio passes through VoIP codecs that compress the signal speech recognition models rely on, differently than an in-room microphone.
Network Interruptions
Connection drops create genuine gaps in the audio record — a condition that essentially doesn't occur in an in-person visit.
Disconnected Systems
Many telehealth platforms sit outside the EHR, so documentation and the chart can live in separate systems requiring a manual bridge.
Format Diversity
Virtual care includes synchronous video, asynchronous submissions, and remote-monitoring follow-ups — each with different documentation inputs.
Peerbits does not publish unattributed industry growth or time-savings statistics on this page. If your organization has internal data on post-call documentation burden, we're glad to build the business case around it during scoping.
Mechanism
How AI Scribe Works During a Virtual Visit
- 1
STEP 1
Capture
Audio is captured from the video platform's call stream, at the physician's endpoint.
- 2
STEP 2
Transcribe
Speech is converted to text using a model tuned for compressed, VoIP-transmitted clinical audio.
- 3
STEP 3
Structure
Clinical entities are extracted and organized into the target note format as the call progresses or shortly after it ends.
- 4
STEP 4
Review
The physician reviews the draft against the source, edits as needed, and signs it. This step is required in every deployment Peerbits engineers.
- 5
STEP 5
EHR Delivery
The signed note is delivered to the connected EHR through a FHIR-based integration, where supported.
Technical Foundation
Built for Telehealth Audio
Compressed Audio Handling
Speech recognition tuned for common VoIP codecs used by video call platforms, rather than a model trained only on uncompressed, in-room audio.
Speaker Separation
Diarization identifies physician and patient speech independently, routing each to the correct note section. Speaker identification is not guaranteed to be error-free in every audio condition.
Network Interruptions
When a connection drop creates a gap in the transcript, the affected section is flagged as incomplete for physician review and completion. The system does not invent or infer clinical content to fill a gap — nothing is fabricated to make the note appear complete.
Peerbits does not publish unverified accuracy benchmarks on this page. Recognition performance on your specific platform and network conditions should be validated during a pilot.
Interoperability
Telehealth Platform Integrations
| Platform | Integration Method | Notes |
|---|---|---|
| Zoom for Healthcare | SDK-based | Integrates via Zoom's healthcare SDK; current certification status should be confirmed before citing publicly. |
| Doxy.me | API / browser-based | Not a native embedded integration — connects via API and a browser-level integration. |
| Microsoft Teams (Health) | Teams Health API | For Teams Health virtual visit deployments; not a native embedded integration. |
| Teladoc Health | Enterprise API | Example of a possible API-based integration; current deployed customer status should be verified before citing. |
| Amwell / MDLive | REST API | Example of a possible API-based integration; current deployed customer status should be verified before citing. |
| Custom / White-Label Platforms | WebRTC SDK | For proprietary video infrastructure — integration scope depends on the platform's media architecture and SDK access. |
Every entry above marked with a named platform partnership REQUIRES PEERBITS VERIFICATION before being represented as a current, deployed integration versus a supported integration pattern.
Interoperability
EHR & Healthcare Interoperability
A telehealth note only creates value once it reaches the patient's actual chart — which may live in a completely different system than the video platform. Peerbits engineers this bridge using FHIR-based APIs, so a signed note is written back into the correct patient record regardless of whether the EHR and telehealth platform are the same vendor. The specific resources, authentication method, and write-back permissions available depend on the target EHR's own configuration. See EHR integration and our Epic SMART on FHIR case study for a concrete example of this pattern.
Documentation & Coding
Telehealth Documentation & Coding
Telehealth E&M documentation involves place-of-service codes (POS 02/10) and modifiers (95/93) that don't apply to in-person visits. AI-assisted coding suggestions can incorporate these into the documentation workflow, with physician or coder review before submission — the system supports the coding workflow, it does not make an unreviewed final billing decision. Payer and jurisdictional telehealth billing rules change frequently and should be confirmed against current CMS and payer guidance.
Use Cases
AI Scribe Use Cases Across Virtual Care
Live Video Consultations
The core synchronous telehealth visit — audio captured and structured into a note for physician review shortly after the call.
Telepsychiatry
DAP-formatted session documentation, generated in the background rather than requiring the clinician to type during the session.
Asynchronous Telehealth
For store-and-forward visits — dermatology, optometry, follow-up care — patient-submitted information can pre-populate the Subjective section for physician completion.
RPM Follow-Up Visits
Remote patient monitoring readings discussed during the call can be incorporated into the Objective section alongside the conversation.
Virtual Specialist Consultations
Consult notes structured from the virtual visit and routed back to the requesting physician.
After-Hours & On-Call Visits
Documentation support designed to reduce, though not eliminate, documentation deferred to the next morning.
Security, Privacy & AI Governance
Telehealth Security, Privacy and AI Governance
PHI Handling
Audio and derived text are encrypted in transit and at rest using current industry-standard protocols.
Audio Retention
Retention duration for raw audio after processing is a configuration decision defined per deployment and organizational policy.
Patient Disclosure & Consent
Patients should be informed that AI-assisted documentation is in use during the visit. Consent and disclosure requirements depend on your organization's policy and applicable jurisdiction — Peerbits does not provide legal advice on this point, and disclosure language should be reviewed by your compliance team.
Physician Review
Every note is a draft until the physician reviews, edits, and signs it. This applies identically to telehealth and in-person visits.
Audit Trail
Call metadata — duration, platform, and physician sign-off timestamp — can be logged to support an audit trail without necessarily retaining audio.
BAA & HIPAA-Aligned Design
Peerbits designs telehealth documentation systems to support HIPAA requirements, with BAA processes scoped appropriately per engagement.
Peerbits engineers telehealth AI scribe systems to support HIPAA requirements and healthcare data-handling best practices. Specific certifications (including any SOC 2 status), audit results, and compliance posture vary by engagement and must be confirmed directly with Peerbits — this page does not represent a certification or compliance guarantee. Cross-state and telehealth licensing compliance remains the responsibility of the healthcare organization and its providers; Peerbits' documentation can capture information relevant to that requirement, such as patient location, but does not itself make an organization compliant.
Comparison
AI Scribe for Telehealth vs Traditional Approaches
| Capability | Manual Post-Call Charting | Generic AI Transcription | In-Person AI Scribe (Unadapted) | Peerbits AI Scribe for Telehealth |
|---|---|---|---|---|
| Works with video call audio | Not applicable | Raw text only | Not optimized for VoIP | Tuned for compressed telehealth audio |
| Structured output | Physician writes it | Unstructured text | Partial | Structured SOAP/H&P/DAP |
| Telehealth-specific coding support | Manual | Not covered | Not covered | Incorporated into workflow, reviewed |
| RPM data incorporation | Manual transcription | Not covered | Not covered | Can be incorporated into Objective, where configured |
| EHR delivery when telehealth platform and EHR differ | Manual bridge | Not covered | Varies | FHIR-based delivery, where supported |
Peerbits' Role
Peerbits Healthcare & Telehealth Technology Experience
Peerbits is a healthcare product engineering and integration company. Telehealth-specific AI scribe engineering draws on VoIP-aware speech recognition, healthcare API and FHIR interoperability across disconnected telehealth-and-EHR systems, and secure architecture for PHI captured outside a traditional in-room setting.
Our most directly relevant project is the Epic SMART on FHIR integration, demonstrating the FHIR R4 connectivity and governed write-back pattern that telehealth-to-EHR delivery depends on. Our broader healthcare engineering work, including remote patient monitoring and healthcare cloud infrastructure projects, reflects the same engineering discipline, though these are not themselves telehealth AI scribe deployments. A dedicated telehealth AI scribe case study, once available with verified customer outcomes, will be prioritized here.
Workflow
Start to Signed Note in Four Steps
Start the Video Call
Open your telehealth platform as normal; capture begins with the call.
Conduct the Visit
Talk to your patient as you normally would — the system listens to both sides of the call.
Review the Note
A structured draft is ready for review shortly after the call ends.
Push to EHR
Once signed, the note is delivered to the patient's EHR record through the connected integration.
Real outcomes from healthcare AI deployments
See how health systems are using Peerbits AI Scribe to reclaim physician time and improve documentation quality.
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Frequently asked questions
Patients should be informed that an AI documentation tool is active during the visit. Consent language can be incorporated into your existing telehealth consent flow — the specific language and disclosure requirements should be reviewed by your compliance and legal team for your jurisdiction, since Peerbits does not provide legal advice.
A connection drop that creates a gap in the transcript results in that section being flagged as incomplete for the physician to review and fill in. The system does not fabricate or infer clinical content to cover a gap.
A telehealth note can be configured to capture the patient's physical location at the time of the call, which may be relevant to your organization's licensing documentation. Peerbits' software supports capturing this information — it does not itself determine or guarantee your organization's regulatory compliance.
A WebRTC SDK integration is supported for proprietary telehealth platforms, capturing the physician-side audio stream at the media layer. Implementation timeline and scope depend on your platform's architecture and are confirmed during scoping.
Telehealth-specific coding elements — place of service codes, applicable modifiers — can be incorporated into the coding suggestions presented for physician or coder review. Payer and CMS telehealth billing policy changes frequently and should be verified against current guidance rather than assumed static.
Yes — for async visits, patient-submitted information can pre-populate the Subjective section, with the physician completing Assessment and Plan during review.
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