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Accelerating Hope
How intelligent automation is streamlining the referral process
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Sometimes, one seemingly insignificant moment divides life into before and after. For Karen Koellner, it was the simple act of leaning over in bed to grab her phone charger that changed everything.
The pain was sudden and sharp as she shifted onto her side. She got up and walked to the mirror to see what was wrong. That’s when she discovered a lump under her arm. "I instantly was like, 'Oh my gosh, I must have cancer,’" she says.
The next morning she was on the phone with her doctor, who sent a referral to Mayo Clinic’s Arizona campus. She braced herself for what often comes next in moments like these: waiting. She was told it could take up to a week to receive a call back.
For patients facing a possible life-altering diagnosis, the referral process can feel like suspended time. But Karen’s phone rang just two hours later, thanks to intelligent automation working quietly behind the scenes.
Finding Hope in a Time of Uncertainty
When something feels wrong, reassurance can’t come fast enough. Getting an appointment on the calendar is the first step toward answers.
"Patients are worried whether or not they're going to get in to be seen," says Erin Layman, operations manager at Mayo Clinic. Timeliness matters just as much. Mayo Clinic in Arizona alone receives more than 60,000 referrals per year, a number that continues to grow.
Until recently, processing those referrals required a time-consuming manual system.
"It took maybe two or three people to validate the faxes," says Gabriel Hernandez, patient liaison at Mayo Clinic. "It could be anywhere from a few pages to a hundred pages, and someone had to scan through each page to determine what each fax concerned."
Because of this lengthy process, there could be delays in callbacks. When patients are seeking care for potentially life-threatening conditions, those setbacks can mean prolonged fear, mounting uncertainty and critical lost time. "Some of these are serious cancer diagnoses, so it's a matter of life and death for some patients," Gabriel adds.
For an organization grounded in providing hope and healing to as many patients as possible, these delays demanded a solution. Mayo Clinic moved quickly to transform the system. That's where generative artificial intelligence (AI) entered the picture.
The Age of Automation
At the scale Mayo Clinic operates, having a human scan every page of every fax to locate key clinical details and determine urgency simply wasn’t sustainable. Referrals were arriving faster than they could be manually processed.
With generative AI’s help, Erin says information can now be quickly extracted from a variety of different documents and summarized into a cover sheet that is reviewed by one of Mayo Clinic’s agents for accuracy. "Then that individual can move it forward to the next step in the process," he says.
This technology doesn’t replace people. Instead, it empowers them by reducing administrative burden to focus on what matters most: the patient.
When the new automated system launched in July 2024, the impact was immediate. With the technology in place, referrals for patients with serious or complex medical conditions are now reviewed and processed in less than 24 hours.
Mayo Clinic trialed its new automated referral system in Phoenix, Arizona, and Rochester, Minnesota. The plan is to expand it to the Jacksonville, Florida, campus in 2026.
A Faster Path to Care
Gabriel says patients are frequently surprised to hear back so quickly. Karen was no exception.
Because the intelligent referral processing system flagged her case as urgent, staff acted quickly. By the next day, appointments were scheduled across multiple specialties and her care team was already coordinating next steps.
Karen’s intuition was right: She was later diagnosed with stage 3 breast cancer. Today, she is cancer-free.
"Time is so important when you get a cancer diagnosis," Karen says.
Erin says Mayo Clinic invested in this technology because patients needed it.
"With this automation, patients are getting the help they need sooner," he says. "For the patients, that means hope."
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