Implementation
Practical deployment workflow for voice AI: EMR connectivity, call routing logic, staff training, escalation protocols, and go-live sequencing for multi-location practices.
Pilot after-hours first to prove reliability, build staff confidence, and iron out EMR sync issues before peak hours depend on it.
Shift your team from answering every call to verifying AI summaries, updating charts, and handling exceptions. They still control what enters the record.
You define what triggers urgent routing, who gets paged, and what happens if the on-call is unavailable. The AI follows your protocols, not the other way around.
Call structure captured
Patient name, phone, appointment request, clinical summary returned for staff verification
Urgent calls escalated
Intelligent keywords trigger immediate on-call routing per your rules
EMR sync confirmed
Appointments and demographics write to your EHR; clinical summaries returned for staff review and filing
Schedule controls preserved
Real-time availability sync ensures AI never books an unavailable slot
Voice AI connects to your EMR in real time. When a patient calls, the system queries your appointment book to see what slots are open with which providers. As your staff books or cancels appointments, the AI's view of availability updates instantly.
Your staff verifies every new appointment in the AI summary before it's written to the chart. If the date, time, or patient details are wrong, your team corrects it—the AI never overrides your data. This is why staff review is a core part of the workflow, not an optional step.
Yes, and it's recommended. After-hours allows you to test EMR connectivity, train your staff on the review workflow, and prove call capture works before integrating with peak-hours desk traffic. Once you're confident, expand to business hours.
The AI returns the captured information in a structured summary. Your staff sees exactly what was understood, can listen to the call recording, and corrects any errors before filing. This is why listening to recordings and spot-checking summaries is part of your QA process.
Use Case
After-hours call handling
Start your AI deployment during off-hours to prove reliability before peak integration.
Workflow
Patient intake
Understand how voice AI captures intake data and returns it for staff review.
Product
Meet Katie, the AI receptionist
See the voice AI system at the centre of this deployment model.
See how MedReception AI handles after-hours calls, scheduling, intake, and patient communication for medical practices like yours.