Clinical Workflow
Migraine prevention requires tracking which drugs a patient has tried, tolerated, and abandoned. An AI receptionist asks and documents preventive medication history—including doses, duration, and reasons for discontinuation—so your clinician has a complete picture before the visit.
Every preventive drug tried, tolerated, or abandoned is documented on the call. Your clinician doesn't discover mid-visit that a patient took topiramate for 2 months and stopped due to weight gain—it's already in the summary.
The AI asks not just what the patient takes, but how well it works: did it reduce frequency by half, cut severity, or have no effect? Your clinician gets context for optimizing therapy.
Side effects, cost, missed doses, or perceived inefficacy are all reasons patients abandon preventive therapy. Capturing these guides your clinician toward better tolerated options.
Your clinician doesn't spend 10 minutes taking a medication history they've already received. They review the summary and focus on dose optimization, escalation, or combination therapy.
Complete preventive history captured on first call
Current and prior medications, doses, duration, efficacy, and reasons for discontinuation all documented
Patient perspective on efficacy recorded
Frequency reduction, severity change, and side effect burden all captured in patient's words
Medication reconciliation ready for clinician review
Structured summary prevents duplicate questions and supports clinical decision-making
EMR-ready format for filing
Staff review and file the summary; nothing is auto-populated without clinical verification
The AI captures: drug name, current dose (if applicable), frequency, start date, whether currently taking, prior doses tried, duration of each trial, reason for stopping (side effect, ineffectiveness, cost, etc.), and patient's assessment of how well it worked. This is more detail than most phone intake captures—and less than a full clinical interview.
Yes. The AI is trained on common migraine preventives: propranolol, timolol, topiramate, valproic acid, amitriptyline, venlafaxine, erenumab, fremanezumab, and others. If a patient mentions a drug, the AI recognizes it and asks for dose and experience.
The AI can ask for descriptions: 'a beta-blocker for blood pressure,' 'an injection monthly,' 'a pill that caused weight gain.' If the patient is truly unsure, the AI documents what was reported and notes uncertainty for your clinician to clarify.
Your clinician receives the summary before or during the visit. They can see at a glance what has been tried and why previous attempts failed, which informs decisions on whether to optimize the current drug, switch to a different class, or add a second preventive.
No. The AI returns a structured, EMR-pasteable summary of the medication history. Your staff reviews it and files it in the EMR (or integrates it into an existing medication reconciliation section). The clinician can then edit or add clinical context before finalizing the chart.
See how MedReception AI handles after-hours calls, scheduling, intake, and patient communication for medical practices like yours.
Want the numbers first? See plans and pricing
