What should an AI agent for orthopedics actually do?
For orthopedic groups, patient access can become complicated quickly. A caller may need help finding the right provider, understanding whether their insurance is accepted, scheduling the right type of visit, checking on a referral, requesting records, or getting help with an existing visit.
That makes orthopedics a good example of why the term “AI receptionist” can undersell what healthcare organizations actually need.
Answering the phone is useful, but the real value comes from understanding what the patient is trying to accomplish and helping them get to the right next step.
Orthopedic scheduling requires more than finding an open time
In many orthopedic practices, scheduling is not as simple as choosing the next available slot. The right visit may depend on the patient’s condition, the type of specialist they need, the location, the visit type, or whether they are a new or returning patient.
An AI agent needs to understand that context before it can help the patient effectively.
Maya can identify what the patient needs, work within an organization’s scheduling rules, and help find appropriate availability. She can also book the visit directly into the organization’s existing system.
That means a patient can move from an initial question to a booked visit in the same conversation, rather than being transferred, placed on hold, or asked to call someone else.
Patient calls extend far beyond scheduling
Across more than 1 million healthcare calls handled by Maya, only 30% were directly related to booking and scheduling. Patients also called about billing and insurance, clinical questions and results, clinic information, prescriptions, records, and documents.
For an orthopedic group, those categories can translate into a wide range of needs. A patient may be checking whether a referral was received, asking whether a particular provider treats their condition, trying to understand insurance coverage, or requesting imaging records before an upcoming visit.
A useful AI agent needs to recognize those different needs and know which ones it can resolve directly and which ones require staff involvement.
AI should reduce work, not create another to-do list
One concern with new healthcare AI technology is that it can simply move work from one place to another. A system may answer the phone, for example, but then leave staff with a long list of messages to review.
The goal should be the opposite.
Maya is designed to resolve routine requests directly whenever possible. When a request does need a person, she can capture the reason for the call and pass along the relevant context so staff do not have to restart the conversation from the beginning.
That helps reduce unnecessary phone tag while making it easier for patients to get to the right person when human support is genuinely needed.
Look beyond the “AI receptionist” label
For orthopedic organizations evaluating AI receptionists, voice agents, or patient access technology, the most important question is what the AI can do after it understands the patient’s request.
Can it identify the type of care the patient needs? Can it find the right availability and book a visit? Can it handle routine insurance or payment questions? Can it recognize when a request needs staff and route it with context?
Those capabilities are what separate a tool that answers the phone from an AI agent that can actually help patients navigate their care.
Because Maya is built on top of Solv’s decade of experience integrating into healthcare workflows, she is able to take action across a broad range of capabilities — from managing bookings to answering FAQs and facilitating payments.
Read the full Off the Hook report for more insights from more than 1 million patient calls handled by Maya.
