Why urgent care needs more than an AI receptionist
For urgent care organizations, the phone is not just a support channel. It is often one of the first places patients reveal that they are looking for care.
A patient may call to ask whether a clinic is open, whether their insurance is accepted, how long the wait is, or whether the location offers X-rays. They may never explicitly say, “I want to book a visit,” but the question itself can signal that they are deciding where to go.
That is why the opportunity for AI in urgent care goes beyond answering the phone. A strong healthcare AI agent should be able to recognize patient intent, answer the initial question, and help the patient take the next step while they are still engaged.
Patient calls are a source of visit demand
Across more than 1 million calls handled by Maya, 30% were directly related to booking and scheduling. Even that number does not capture every opportunity to turn a conversation into care.
Someone asking about insurance, services, availability, or clinic hours may still be deciding whether to visit. If the answer to their question is yes, the natural next step is often to help them find care.
Maya can do both. She can answer the question and, when appropriate, surface visit availability and help the patient book without asking them to hang up, visit another site, or call back later.
For urgent care groups, that turns the phone from a purely operational channel into another way to capture patient demand.
Phone demand peaks when clinic teams are already busy
The challenge is that patient calls do not arrive evenly throughout the day. Nearly 40% of daily calls in Solv’s analysis came in between 8 and 11am, which is often the same period when urgent care teams are managing morning check-ins, walk-ins, and patients already inside the clinic.
Another 24% of calls happened outside standard business hours, when staff may not be available at all.
That creates a difficult tradeoff for healthcare teams. The patient calling may be an opportunity for a new visit, but the staff member answering the phone may also be responsible for helping a patient who is already standing in front of them.
An AI agent removes some of that tension by handling calls concurrently and around the clock. Patients can get answers and take action without waiting for a staff member to become available.
Turning more calls into booked visits
The strongest measure of success is not simply how many calls an AI agent answers. It is what happens as a result of those conversations.
At Little Spurs Pediatric Urgent Care, only 1.8% of inbound phone calls resulted in a booked visit before Maya. After launching Maya, phone bookings increased 5x. Today, Maya books 55 additional visits per location each month. Read the Little Spurs Case Study →
That growth comes from being able to recognize when a caller may be looking for care and help them book while the intent is still there. Instead of answering a question and ending the conversation, Maya can help turn that conversation into a completed visit booking.
More than a phone answering tool
Booking is only one part of the job. Patients also call urgent care organizations about insurance, billing, clinic information, prescriptions, records, and clinical questions.
Because Maya is connected across Solv’s broader platform, she can support more of those needs and route the ones that require a person with context. That makes her more than a virtual receptionist or answering service.
For urgent care organizations, the opportunity is not simply to keep up with the phone. It is to use AI to make the phone a more effective part of patient access, growth, and operations.
Read the full Off the Hook report for more insights from more than 1 million patient calls handled by Maya.
