AI Follow-up Agent
Bring patients back without building another staff queue
Work missed calls, recall, and approved patient follow-up with a clear status for every attempt and a staff handoff when the conversation needs judgment.
How a follow-up queue runs
The workflow in the diagram above, in practice: every attempt follows a contact policy your team approves, and every patient ends with a clear status.
- 01
Start with an approved list
The practice defines which patients belong in the workflow and confirms the source of the list.
- 02
Set the contact policy
Your team approves the timing, number of attempts, channel, and message. Consent requirements stay part of the setup.
- 03
Work each patient to a status
The agent records whether the patient scheduled, asked for a callback, declined, opted out, or did not respond.
- 04
Exceptions reach staff
Questions about care, benefits, balances, or complaints move to the practice with the context already captured.
What the Follow-up Agent handles
A reminder sent is not the same as a patient reached. The agent works the queue so your team works the exceptions.
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Missed-call recovery
Missed calls become a worked outreach queue instead of a sticky note.
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Hygiene and preventive recall
Due and overdue recall worked on the practice's schedule.
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Unscheduled care follow-up
Approved follow-up for unscheduled or incomplete treatment.
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Confirmations and reschedules
Appointment confirmation and rescheduling prompts within office rules.
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Responses and callbacks
Patient replies, opt-outs, and callback requests recorded as they land.
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Handoffs with context
Questions outside the workflow go to staff with the conversation so far.
A smaller, clearer staff worklist
The Follow-up Agent does not give clinical advice, and it does not remove human follow-up — it reserves staff time for the conversations where a person makes the difference.
Front-desk teams shouldn't have to read every transcript or replay every call. They see who responded, what changed, and what still needs action.
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Clinical questions
Recorded and routed by the practice's handoff rule — never answered by the agent.
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Declines and opt-outs
Recorded, then outreach stops or changes according to the approved policy and applicable requirements.
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Complaints and sensitive issues
Moved to the practice with the context already captured.
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The practice sets the policy
Audience, timing, channel, message, attempt limits, and stop conditions are all yours to approve.
Measure progress without inflated ROI claims
A practice can track the workflow itself — and apply its own financial assumptions.
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Patients in each workflow
Who was added to each approved outreach queue.
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Attempts and responses
Contact attempts made and each patient's response status.
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Visits scheduled
Appointments scheduled or rescheduled from follow-up.
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Callbacks and open questions
Callback requests and unresolved questions awaiting staff.
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Opt-outs and stopped outreach
Where outreach ended, with the stop reason recorded.
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Staff time on exceptions
Where human attention actually went.
Revenue impact depends on the practice, the patient mix, and completed care. EigenH AI reports workflow outcomes so the practice can apply its own financial assumptions.
Frequently Asked Questions
Yes. The practice controls the source list, eligibility rules, timing, and stop conditions for each workflow.