Workflow
Fresno practices drop the daily confirmation-call block: the AI reads back each booking on the call, reminders send themselves, staff work only exceptions.
By MedReception AI, physician-built by Paul Toomey, MDPublished
Most Fresno front desks reserve a stretch of every afternoon for tomorrow's list: pull the schedule, dial, leave a voicemail, mark it, try again later. When each appointment is confirmed at the moment it is booked and reminders send on their own, that block stops being a fixed cost. The same staff hours go to check-in, referrals, and the phones that are still ringing.
Instead of calling everyone to find the few who need attention, staff work a short list: the patient with no mobile number, the one who declined texts, the one who called asking to move. The routine confirmations are already done, and the list comes from the call summaries rather than from a printout.
The AI does not change an existing appointment. When a patient calls to move or cancel during office hours, the AI transfers them straight to your front desk, so the person who can see the schedule handles it in one conversation. When the office is closed or nobody can pick up, the AI records the request as a tracked message in your portal rather than a voicemail, and staff open the day with a short list of slots to release and patients to call back. Practices that want the AI to take reschedules directly can raise it with us during implementation; it is not turned on by default.
Whether the booking came in during a Monday morning rush or on a Saturday night, the caller hears the same complete read-back and receives the same reminders. A rushed confirmation, or a skipped one, is no longer something the practice has to police.
Read-back on every booking
Date, time, provider, and office confirmed with the caller before hang-up
Reminders on your schedule
Text or email, timed by your practice, sent without a staff member dialing
Exception list in the call summary
No mobile number, declined texts, or a reschedule request flagged for staff
Reschedule requests routed, not lost
Straight to the desk in office hours, a tracked portal message after hours
For routine appointments, no: confirmation happens at booking and reminders send automatically. What remains is an exception list — patients without a mobile number, patients who declined text reminders, and anyone who has called asking to change their time. Most practices keep one person responsible for that list, but it is a few minutes of the day rather than a block of the afternoon.
Yes. The read-back includes which office the patient is booked at and which provider they will see, and the caller confirms each item before the call ends. For Fresno practices with more than one site, that is exactly the error the day-before call was catching, and it is now caught at the moment of booking instead of the day before.
Every AI call is logged with a transcript and a structured summary. The summary shows the booking details that were read back and flags anything staff need to act on: no mobile number given, reminders declined, or a request to move the appointment. Staff work from that flagged list rather than from the full schedule.
The AI does not change an existing appointment. During office hours it puts the caller straight through to your front desk, with no intake questions first, so your staff can move the visit while the patient is still on the line. If the office is closed or nobody can pick up, the AI takes the patient's name, date of birth and what they need, and the request becomes a tracked message in your portal rather than a voicemail. Staff release the slot and call the patient back when they open. If your practice would rather have the AI take reschedules directly, that is something to discuss with us during implementation; it is not turned on by default.
Both, because they catch different failures. The read-back at booking is where the patient confirms the details are right, which catches the wrong office, wrong day, or wrong provider. The reminder closer to the visit catches forgetting. A practice trying to reduce no-shows needs both, and the AI delivers both without adding work to the desk.
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