How Montage Health reduced referral times from 23 days to two days with AI

Referrals are essential for connecting patients to care, but in many health systems, outdated workflows make the process unnecessarily slow and frustrating. Staff spend hours transcribing faxed referrals into their EHR, often leading to missed details and weeks-long delays. Patients, in turn, have to wait weeks for scheduling and care—sometimes losing the motivation to follow through.

That changed for Montage Health when they implemented AI-powered referral automation. Today, referrals are processed in just 1.5 days, freeing staff to focus on meaningful patient interactions and providing faster access to care for their community.

This blog explores how Montage Health achieved these results, key lessons learned, and their actions to scale automation for even greater impact.

The challenge: outdated workflows delayed care

At its core, a referral should make it easy for patients to access the care they need. But that wasn’t the reality at Montage Health, where processes were manual, fragmented, and time-intensive.

Before automation:

• Staff were overwhelmed. Key team members spent hours processing incoming faxed referrals, with one dedicating an entire day every week to transcribing information into Epic.
• Patients endured long delays. Turnaround times stretched to 23 days or more, causing patients to lose momentum or drop off entirely while waiting for follow-ups.
• Department inefficiencies grew. From duplicated manual entry to outdated processes built for older systems, bottlenecks slowed down the entire care ecosystem.

These inefficiencies weren’t just operational headaches; they directly delayed care delivery frustrating staff and patients.

The solution: piloting referral automation

Montage Health didn’t try to transform its entire referral process in one go. Instead, they focused on small, targeted pilot programs where they could refine workflows, measure impact, and prove automation’s value before scaling.

Healthy Together program: choosing a low-risk pilot with high impact

Healthy Together, a free diabetes education program for families, became the first pilot site for automation. The program’s referral workflow relied entirely on faxed forms, and one team member would dedicate an entire day weekly to manually transcribing them, a time-consuming process with no built-in follow-ups, often leading to unengaged participants.

Montage chose Healthy Together as its starting point because it had manageable referral volumes, no insurance authorizations, and predictable workflows. “By starting with simpler workflows, we could focus on proving value and refining processes,” explained Faith Balaban, who led the project.

The change was immediate. With automation fully deployed:

• Referrals were processed in just 1.5 days, down from 23.
• 80% of referrals became completely touchless, no longer requiring manual intervention.
• The staff member who once handled transcription was reallocated to a more impactful, patient-focused role, enhancing care delivery.

Beyond improving operational metrics, the faster referrals led to better program participation. Families received follow-up calls within two days of their referral, keeping the program top of mind and increasing engagement.

Breast Care Center: scaling automation for high-volume workflows

Building on the success of Healthy Together, the Breast Care Center, a high-volume department handling thousands of annual referrals, was chosen as the next pilot. Before automation, staff at the front desk were overwhelmed by competing demands like patient check-ins, phone calls, and transcribing referral forms, which caused delays and bottlenecks.

With referral automation in place:

• 10,500 referrals (including mammograms and ultrasounds) were processed in just six months.
• Staff saved over 1,200 hours, allowing them to focus on higher-value patient-facing responsibilities.
• Errors in data transcription dropped noticeably, ensuring a smoother scheduling process and fewer downstream disruptions.

Faith emphasized that the department’s success didn’t depend solely on the technology. “It wasn’t just about putting the automation in place—it was about working alongside teams to ensure the system exceeded expectations and built trust.”

Regular tracking of metrics like turnaround times and accuracy created buy-in across the team, helping staff see the system’s capability. “Seeing improvement week after week motivated teams to lean into the system,” Faith said.

The results: faster access, happier staff, stronger outcomes

Automation has delivered measurable benefits for patients, staff, and operations at Montage Health.

For patients, Referrals are now scheduled within days rather than weeks. This faster turnaround improved follow-through rates, ensuring patients received timely care. In the Healthy Together program, faster follow-ups encouraged families to stick with the program, resulting in a 15% increase in participation.

For staff: Automation significantly reduced the time spent on repetitive tasks. Freed from data entry, teams regained nearly 1,200 hours, which was redirected toward patient-focused work and other high-value activities.

For operations: Automation reduced transcription errors, streamlined department workflows, and helped standardize processes across teams. These improvements saved time and reduced operational risk, ensuring departments could manage higher referral volumes without additional resources.

“Speed isn’t just a metric—it changes outcomes,” shared program leader Meg Dingae. “Whether it’s getting patients into vital screenings or starting diabetes management, faster referrals mean better care.”

Lessons learned

Montage Health’s referral transformation wasn’t just about technology—a clear strategy and thoughtful execution drove it. Faith and Meg shared the lessons they learned along the way:

1. Start small but strategically. Pilot programs like Healthy Together served as low-risk opportunities to validate workflows, demonstrate ROI, and build organizational confidence in automation.
2. Engage stakeholders early. Regular collaboration with frontline staff ensured they felt invested and empowered. Weekly check-ins and progress reviews were key to addressing concerns and refining workflows.
3. Track and share metrics. Useful data like turnaround times, error rates, and staff hours saved built momentum across teams and leadership, showing tangible improvements and sustaining engagement.
4. Challenge legacy workflows. Many processes, originally designed to serve outdated systems, were reexamined and optimized to align with the efficiency automation provided.

Faith explained the importance of flexibility while scaling: “For radiology, the volume was much higher than in our pilots, so we adjusted rollout timelines to ensure department leaders were comfortable. Having weekly check-ins allowed us to calibrate in real-time.”

What’s next: scaling referral automation

After early pilots, Montage is now scaling automation across its medical group and hospital departments. Expansion plans include:

• Implementing automation across specialty care referrals, ensuring all departments benefit from standardized, efficient processes.
• Rolling out automation in behavioral health services, where small teams stand to gain the most from reduced administrative workload.
• Centralizing workflows for patient access teams, which handle the majority of radiology and hospital-wide referrals.

Montage Health is developing reusable templates for workflows and metrics to maintain momentum and simplify future rollouts. These tools will help ensure expansion is scalable while still addressing the unique needs of each department.

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