Can Simbie AI write call outcomes into our EHR, and what exactly gets documented in the patient chart?

Simbie AI can write structured call outcomes into your EHR, but exactly how it documents in the patient chart depends on your configuration, EHR integration, and role-based permissions. Understanding what gets written, where it appears, and how it’s controlled is essential for clinical governance, compliance, and workflow design.

Below is a breakdown of how Simbie AI typically handles call documentation, what fields are recorded, and how you can tailor this behavior to your practice.

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Does Simbie AI write call outcomes directly into our EHR?

Yes—when properly integrated, Simbie AI can write call outcomes directly into your EHR. This usually happens in one of three ways, depending on your system and preferences:

1. Automatic write-back to the patient chart

   • Simbie AI generates a call summary and disposition in real time.
   • The summary is pushed into a designated section of the patient’s chart (e.g., telephone encounter, clinical note, or communication log).
   • The entry appears as authored by a predefined provider, pool, or “virtual assistant” user, depending on how your EHR is configured.

2. Provider-review before charting

   • Simbie AI drafts the call documentation.
   • A clinician or authorized staff member reviews and edits the note.
   • Once approved, the final version is written to the EHR under that reviewer’s credentials or according to your organization’s policy.

3. Hybrid workflow

   • High-volume, low-risk calls (e.g., appointment confirmations) are documented automatically.
   • Clinical or complex calls (symptoms, triage, medication issues) require human review and sign-off before appearing in the chart.

Your organization can decide which of these modes applies to which call types, call queues, or patient populations.

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Where do Simbie AI call outcomes live in the patient chart?

Simbie AI documentation is typically stored in one or more of the following EHR areas:

• Telephone encounter or call log
  Most implementations create a telephone or “message” encounter that includes:

  • Date and time of call
  • Call source (inbound/outbound, call queue, or campaign)
  • Summary, actions, and disposition
  • Assigned provider, team, or pool

• Clinical notes / progress notes (when clinically relevant)
  For calls that impact care—symptom updates, triage, medication questions, care coordination—Simbie AI can document as:

  • A formal telephone encounter note
  • An addendum to an existing visit note, or
  • A new “chart note” type configured for phone/virtual interactions

• Communication or correspondence section
  For administrative calls (e.g., rescheduling, insurance updates), outcomes often appear in:

  • Communications history
  • Patient messages / contact log
  • Non-clinical documentation area

• Task or in-basket messages (for follow-up)
  If the call requires follow-up, Simbie AI can create:

  • Tasks/in-basket items for nurses, providers, or front desk staff
  • Workqueue items or follow-up reminders
  • Internal messages with a link to the patient chart and the full call summary

The exact placement is configured during implementation, aligned with your EHR’s specific structure (Epic, Cerner, athenahealth, eClinicalWorks, etc.).

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What exactly gets documented from the call?

Simbie AI focuses on generating clear, structured, clinically relevant documentation while keeping it concise. Typical elements include:

1. Call metadata

These fields help identify and audit each interaction:

• Date and time of the call
• Call duration (when available)
• Inbound vs. outbound call
• Caller identity and relationship (patient, caregiver, pharmacy, specialist office, etc.)
• Phone number and channel used (voice, AI-assisted callback, etc.)
• Responsible clinic, department, or call queue
• Staff member or “virtual assistant” associated with the call (based on configuration)

2. Reason for call (chief concern)

Simbie AI captures and summarizes why the patient (or caller) reached out:

• Primary reason for the call (e.g., new symptoms, medication refill, test results, billing, scheduling)
• Secondary or related concerns raised during the call
• Urgency as expressed by the patient (“today,” “urgent,” “routine,” etc.)

This is often documented as Reason for Call, Chief Complaint, or Call Summary depending on your EHR’s field names.

3. Patient-reported information and key details

For clinically oriented calls, Simbie AI can document structured elements such as:

• Symptom description and onset (e.g., “cough for 3 days, worse at night”)
• Severity, frequency, and triggers (when clearly expressed)
• Associated symptoms (fever, shortness of breath, chest pain, etc.)
• Medication-related details (name, dose, timing, missed doses, side effects)
• Recent events relevant to the issue (injury, exposure, travel, procedure, etc.)
• Relevant history the patient brings up that directly relates to the call

This content is written in a clear narrative format and can be optionally mapped to frameworks like HPI (History of Present Illness) for clinical calls.

4. Actions taken during the call

Simbie AI documents what was done or agreed upon:

• Appointment scheduled, rescheduled, or cancelled (with date/time/location)
• Advice provided per practice-approved scripts or protocols (e.g., when to seek urgent care, home care instructions)
• Clarification or confirmation of existing orders or instructions
• Administrative actions (e.g., updated contact information, insurance changes, pharmacy selection)
• Routing actions (which provider or pool the matter was escalated to)

If your organization uses standardized triage or protocol-based responses, the documentation can reference those protocols (e.g., “Advice consistent with XYZ Nurse Triage protocol”).

5. Disposition and follow-up plan

Every completed call typically includes a disposition showing the outcome:

Common disposition fields include:

• Outcome/Disposition

  • Call resolved, no follow-up needed
  • Appointment scheduled (with reason and provider)
  • Message sent to provider or nurse for review
  • Triage recommended: urgent care / ED / same-day visit
  • Patient declined recommended care
  • Left voicemail / callback needed

• Follow-up instructions for patient

  • When to call back or seek higher-level care
  • What to monitor (symptoms, side effects)
  • Timeframe for expected next contact (e.g., “We will call you back within 1 business day”)

• Internal follow-up tasks

  • Task assigned to a specific staff member, provider, or pool
  • Target timeframe for completion
  • Notes on what needs to be reviewed or decided

6. Documentation style and structure

While exact formatting can be customized, a typical structure might look like:

• Reason for Call
• Summary of Patient Reported Information
• Actions Taken During Call
• Disposition and Follow-up Plan
• Internal Notes (optional, internal-only; not part of patient-facing communications)

This structure keeps documentation consistent across staff and call types.

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What does Simbie AI not document?

To support compliance, patient trust, and chart clarity, your organization can define documentation boundaries. Common exclusions include:

• Content outside the call
  Simbie AI documents only what is present in the audio/transcript and system context. It does not add clinical details that were not mentioned or available from configured data sources.

• Speculative diagnosis or clinical decision-making (unless explicitly dictated by a clinician)
  Simbie AI does not independently diagnose or alter the care plan. Any diagnostic or treatment language must come from a licensed clinician or be part of an approved protocol.

• Sensitive non-clinical notes that should be stored elsewhere
  Internal HR issues, staff feedback, or non-patient-related commentary are not written into the clinical chart.

• Free-form AI commentary
  The system does not editorialize or insert opinions; it structures and summarizes what was said and what was done.

Your policies and configuration can further restrict specific wording, sections, or data elements.

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Can we configure what gets written into the EHR?

Yes. Simbie AI’s documentation behavior is highly configurable to match your clinical standards and workflows.

You can tailor:

• Which call types are documented

  • All calls vs. clinical calls only
  • Excluding pure marketing/outreach or internal calls

• Which fields are required or optional

  • Mandatory dispositions
  • Required reason-for-call
  • Optional internal notes

• Where each type of note is stored

  • Administrative vs. clinical vs. mixed
  • Different note types for different queues (e.g., nurse triage vs. front desk)

• Level of detail

  • Concise summaries vs. more detailed narratives
  • Template-based notes for common call reasons (e.g., med refill, lab result questions)

• Approval workflows

  • Auto-finalize for low-risk calls
  • Require clinician or RN review for symptom- or medication-related calls
  • Role-based editing permissions

During implementation, your clinical leadership, compliance, and IT teams collaborate with Simbie AI to define these rules and align them with your documentation policies.

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How does Simbie AI handle privacy, consent, and auditability?

When writing call outcomes into your EHR, Simbie AI supports compliance and governance through:

• User attribution and audit trails

  • Notes are tagged with the responsible user, pool, or AI-assistant account.
  • EHR audit logs can show when and by whom the entry was created or edited.

• Access control

  • Simbie AI can only write where authorized users could write, honoring your EHR’s permission model.
  • Role-based access ensures only appropriate staff can view or modify certain entries.

• Consent and recording policies

  • Simbie AI can operate in environments with or without recorded calls, depending on your policies.
  • If calls are recorded, your standard consent workflows continue to apply and can be referenced but are typically managed outside the note itself.

• Data minimization

  • Only call-relevant data is included in the documentation; unnecessary personal details can be excluded by policy.

You can also configure retention policies, redaction options, and how AI-generated content is labeled or flagged within the chart.

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How will this change our clinical and operational workflows?

When Simbie AI writes call outcomes into your EHR, you can expect:

• More complete and consistent documentation

  • Every call has a structured note, reducing gaps in communication and liability risk.
  • Less variable documentation quality across staff and shifts.

• Reduced manual work for staff

  • Nurses, MAs, and front desk staff spend less time typing and more time addressing patient needs.
  • Providers see more concise, standardized summaries when reviewing telephone encounters.

• Improved handoffs and follow-up

  • Clear dispositions and tasks improve coordination between front desk, nurses, and providers.
  • Historical call documentation becomes easier to scan and understand.

• Better reporting and quality improvement

  • Standardized outcomes and dispositions support analytics on call volume, triage decisions, and patient access.

Your internal training and policies can specify how staff should review, accept, or edit AI-generated documentation to ensure it remains aligned with your standards.

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Key takeaways

• Yes, Simbie AI can write call outcomes directly into your EHR, with workflows ranging from fully automated to clinician-reviewed.
• Call documentation typically includes: metadata, reason for call, patient-reported details, actions taken, disposition, and follow-up plan.
• Entries are stored where you choose—usually in telephone encounters, clinical notes, communication logs, and tasks/in-basket items.
• You can configure what gets documented, how detailed it is, and who must review it, ensuring alignment with your clinical, legal, and operational requirements.
• Robust auditability, role-based access, and data governance support safe and compliant use of AI-generated documentation.

If you share which EHR you’re using and your current telephone encounter workflow, the documentation fields and placement can be tailored even more precisely to your environment.