What’s next for healthcare contact centers? Five AI insights from Community Health Network

Contact centers represent one of healthcare’s biggest opportunities for transformation. Community Health Network (CHN) is leading efforts to modernize patient access through AI while keeping people at the center of its innovation. 

“We were looking at different solutions to improve and accelerate what we were already doing,” says Jon Leon, Patient Access Manager at CHN. The health system launched AI workflows for outbound voice calls to schedule appointments and mammography orders – a step that shaped their broader AI strategy.

Here are five AI takeaways to upgrade your healthcare contact center.

1. Make AI approachable 

CHN staff were initially skeptical of using AI voice to connect with patients. “A robot calling patients we’ve spoken to for 30 years?” Leon recalls. But as they saw their call volume decrease, the tone changed. 

“Anything that reduces their 110 calls a day is welcome,” he says. “That’s the mindset to have a productive conversation with my frontline staff as much as with my executives.” 

Inbound faxes remain a significant part of the scheduling process. But by routing faxes through an automated workflow to generate an order in the EMR and trigger an outbound scheduling call to the patient, the process becomes seamless for CHN. “None of that involves a human. That's huge," he adds.

To refine their contact center use cases, Leon emphasizes involving those closest to the technology: “We gather their feedback, generate new ideas, and build solutions from the ground up.” AI assists with the workload, and that’s been viewed as a positive change across CHN.

2. Stay focused on the patient experience

With the technology in place, CHN focused on the call experience, starting with AI-powered mammography scheduling for two reasons: the workflow offered quick feedback and provided sufficient volume without being overly complex. 

However, the organization identified a few call quality concerns early on. “The AI Voice Agent was robotic and sometimes repetitive,” says Leon. "The scheduling call was too slow."

CHN improved the AI voice experience by making it sound more natural, adding subtle background noise, reducing overly polite phrasing, and keeping questions to the point. “Just gather the details and move the call along,” he advises.

Small adjustments led to big lifts in both patient engagement and call satisfaction.

3. Define success early on with stakeholders

As AI use expanded, CHN realized a shared definition of AI success was missing. In the live-agent contact center, every connected call resulted in a scheduled appointment. When AI took over, any drop from that appointment success rate felt like a failure.

CHN played the AI Voice Agent calls back for leadership. “Listening to the calls made it clear we should keep going. And once you have the template – ask five questions, schedule the visit, and conclude the call – you can apply it to other visit types like ultrasound.”

Keeping communication channels open contributes to success. “Patients care about getting scheduled and removing unnecessary questions,” says Leon. 

CHN combined similar questions, such as condensing two breast abnormality questions into one, to save time and improve the experience. “Each second matters.”

4. Stay flexible; don’t be afraid to pivot your AI strategy

But as the organization quickly learned, flexibility and quick thinking are equally important. A fire at one site created major scheduling challenges and limited access to mammography services. 

Mammography slots were booked months in advance, and patients endured long calls only to be told there were no appointments available. “At that moment, we realized AI may not work,” adds Leon.

To address capacity concerns, CHN shifted from “AI should schedule” to “AI should get patients scheduled, and fast.” That led to two changes:

• Warm-transfer calls when patients request a specific facility, and
• Offering appointments at partner radiology locations, even if CHN isn’t scheduling them directly.

“That mindset shift was a turning point.”

5. Design AI with tomorrow’s workflows in mind

CHN is thinking ahead about ways to capture more patient interactions with the help of AI. For example, most patients call back from a missed outbound AI call, generating thousands of inbound calls each day.

Leon’s vision: place AI at the very front of the call experience. “If the patient needs a mammogram, AI schedules it. If they need something else, transfer them. But not through three different systems or experiences.” The goal for CHN is clear: provide a process that establishes better care and outcomes by delivering the call immediately rather than days later.

As AI use reaches a comfortable state, new ideas surface: digital assistants for inbound volume, automated order ingestion into the EHR, and immediate outbound scheduling offers.

“The closer you schedule after the order is placed, the higher the likelihood the patient completes the test,” Leon says. And faster scheduling prevents commercial patients from shopping for services or delaying needed care. “That's an exciting conversation to have if we're talking about the future.”

AI is reshaping the healthcare contact center

AI gives CHN the scalability, efficiency, and patient-centered experience needed to stay competitive. Leon’s takeaways reflect how early challenges and meaningful wins shape a more modern, accessible blueprint for healthcare contact centers.

Learn more about CHN’s AI expansion here.