Redefining Patient Access Through Agentic AI in Healthcare Call Centers
The Access Challenge Healthcare Cannot Ignore
Even with expanded digital tools, healthcare call centers are still the main and often most strained access point for patients. Whether confirming or rescheduling an appointment, patients continue to rely on phone calls. According to a 2025 Relatient data analysis across clients, up to 15% of scheduled appointments still result in calls to confirm basic details. These repetitive calls consume valuable staff time .
Agentic AI is a type of voice technology that offers relief by understanding a request, deciding the best action, and completing it within defined rules. In healthcare call centers, this means interpreting patient intent and carrying out the task safely, accurately, and consistently.
Not All AI Is Created Equal
Many voice technologies greet callers and route them to staff but stop short of resolving the request. While useful, they still depend on human intervention.
Agentic AI acts independently. It interprets intent, applies rules such as visit-type logic and provider preferences, and completes the task when possible.
This approach has allowed some organizations to resolve up to 20% of inbound calls without staff involvement, particularly for predictable scheduling tasks like reschedules and confirmations.
The Hidden Complexity Behind Patient Calls
Many inbound calls may seem simple such as reschedules or availability checks, but each is shaped by a web of operational rules. Factors such as which visit types are allowed at certain locations, which providers accept specific appointments, and the booking windows or departmental flows that must be followed all influence what can be done. Basic automation struggles with these constraints. Agentic AI succeeds because it is built to operate within them.
“You do not really have an AI problem. You have a scheduling problem. And you need to evaluate what is the right tool for it,” shared Paul Troutt, VP of Product at Relatient.
The value lies not just in speaking and responding but in acting in accordance with real-world scheduling policies. The more structured and rules-based the environment, the more effectively it can operate.
Lessons from Early Adopters
Implementing an agentic AI is about supporting staff, not replacing them. The most effective programs start with workflows that are consistent and well-documented, where automation can improve the patient experience without disruption. Many organizations begin with appointment cancellations, reschedules, and confirmations, then expand as they prove reliability.
With Relatient’s Dash Voice AI, for example, more than half of rescheduling requests are now handled without staff involvement, and half of patients offered a self-scheduling link via text accept it. “We’ve seen that if you do it well, patients don’t even realize they’re speaking to AI,” said Olivia Collazo, Patient Access Manager at Raleigh Orthopaedic. “The experience just feels seamless.”
Another important takeaway: automation is most effective when it reflects what a human scheduler would do. Staff report fewer call transfers and reduced burnout, freeing them up to focus on more complex or time-sensitive needs.
Agentic AI as a Long-Term Strategy for Scalable Access
The healthcare call center has long been viewed as a cost of doing business. With agentic AI, it becomes a driver of efficiency and patient satisfaction. When AI resolves routine requests autonomously, it reduces hold times and abandonment rates, improves first-call resolution, all while modernizing access and relieving pressure on healthcare call centers. The future of patient access is not just automated, it is intelligent.
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