Case Study

UST's Conversational AI solution helped U.S. healthcare system accelerate call resolution by 63%

This healthcare system needed an innovative solution to streamline and accelerate patient and provider support calls. UST implemented an automated Conversational AI solution using natural language processing. Now, 90% of inquiries are resolved in the first call in as few as 45 seconds.


This hospital system, located in the southwestern region of the U.S., operates more than a dozen hospitals and clinics serving a population of nearly five million people. The healthcare system has received accolades for providing top-notch patient-centered care.


Needed innovative technologies to enhance phone support for patients and providers

The healthcare system staffs two support teams to answer inbound calls when patients have questions about services and medical information, like scheduling appointments and checking test results. The support teams also field inquiries from providers, typically with questions about functionality in the electronic health records (EHR) system.

Because support teams must understand the health system’s clinical operations, across nearly 20 distinct healthcare facilities, as well as the navigation and capabilities of the organization’s integrated EHR system, support personnel require specialized skills and training. Depending on the complexity of the inquiry, call resolution timeframes may take longer than the patient or caregiver deems appropriate, causing frustration.

With those issues in mind, the healthcare system’s IT team wanted to explore new, innovative ways to improve support operations, increase the efficiency and productivity of support staff, decrease operating costs, and enhance experiences for patients and providers.


Conversational AI solution provided frictionless service desk support for most common healthcare calls

UST Contineohealth experts implemented a Conversational Artificial Intelligence (AI) solution based on a long-standing relationship between UST and the organization. The project team mapped end-to-end call center processes and created personas corresponding to about 80% of incoming call scenarios. When patients and caregivers call the support center, the solution uses natural language processing to route calls to a voice AI application that can answer the most commonly asked questions. When the caller needs additional help, the automated solution provides options to escalate the call for more specific self-service information or to a human support person.

The Conversational AI solution was initially designed to resolve 80% of inquiries. The UST Contineohealth team monitors real-time call analytics and deploys additional self-service AI call scenarios to optimize service desk processes and address the changing support needs of patients and providers.


Streamlined support processes enhanced patient and provider experiences

By augmenting the support teams with an automated Conversational AI solution, the healthcare system: