Community healthcare providers operate at the front line of patient access. They serve diverse populations across multiple clinics, manage high call volumes, and support patients who often need fast answers about appointments, services, and next steps.
For one large U.S. community healthcare provider - serving diverse primary and specialty care populations across multiple clinics - the contact center had become a critical part of the patient journey but also a growing operational bottleneck. Patients were calling to check upcoming appointments, schedule new visits, reschedule existing ones, cancel appointments, or get answers to routine questions.
At the same time, call center agents had to search across fragmented knowledge sources, route calls between teams, and handle repetitive requests - increasing workload, slowing response times, and creating friction for patients.
The organization wanted to modernize patient access without making the experience feel impersonal. Its goals were to:
The provider’s call center was receiving a large volume of routine patient requests. Many patients were calling simply to check upcoming appointments or manage appointment changes. These interactions were important, but they consumed agent time and slowed access for patients who needed more complex support.
Knowledge access was another challenge. Call center teams relied on information spread across internal documentation and systems. This created manual searches, inconsistent answers, and unnecessary transfers. For new or rotating agents, finding the right procedure or approved answer could take time, increasing handle time and adding friction to the patient experience.
The organization also had limited digital self-service. Patients who wanted to complete simple tasks outside normal call center flows had few options. This increased phone traffic and made the contact center the default channel for requests that could be completed via self-service.
The provider partnered with Druid AI to deploy AI agents that support both patients and call center staff.
The first AI agent acts as a patient support agent, available through chat in the patient portal and voice through the contact center platform. It helps patients authenticate, view upcoming appointments, schedule appointments, reschedule appointments, cancel appointments, ask FAQs, and transfer to a human agent when needed.
The second AI agent acts as a call center knowledge assistant, embedded in Microsoft Teams. It gives staff instant access to approved call center documentation stored in SharePoint, helping human agents answer procedural questions faster and more consistently.
Together, the two agents created a more scalable patient access model:
Start with high-volume, low-complexity patient requests.
The provider focused first on appointment-related workflows because these were among the most common reasons patients contacted the call center. Checking upcoming appointments, scheduling, rescheduling, and cancellations were simple enough to automate but valuable enough to generate a measurable impact.
Patient access automation works best when paired with human handoff.
The AI agent handled routine workflows, but patients could still be transferred to a human agent when needed. This preserved trust while reducing avoidable call volume.
Agent assist matters as much as patient self-service.
The provider did not only automated patient-facing interactions. It also equipped call center staff with a knowledge assistant in Microsoft Teams, helping them retrieve approved answers faster and reduce manual search time.
Appointment rescheduling is a major source of value.
The 29% rescheduling rate shows that patients used the AI agent not only to book new visits, but also to manage appointment changes on their own. By making these interactions self-service, the provider reduced avoidable phone calls, eased pressure on the contact center, and freed staff to focus on more complex patient needs.
Positive feedback is a key adoption signal.
The 90% positive feedback received suggests that patients were comfortable using AI for routine healthcare access tasks when the experience was easy, practical, and connected to real workflows.