Unlocking New Revenue Potential with AI Agents at an Academic Medical Center
June 12, 2025
Academic medical centers face ongoing financial pressures, balancing research and education with operational demands. Recent reductions in NIH funding have increased these challenges, making it harder to maintain high standards. Hiring more staff to handle administrative tasks is often not an option due to budget and workforce constraints.
At the Medical University of South Carolina (MUSC Health), leaders adopted a different approach by integrating AI-powered automation with their revenue cycle operations. This shift aimed to reduce staff burden while identifying new revenue opportunities.
A Change in Approach
MUSC Health operates 760 care locations across South Carolina. The health system was challenged by a high support staff-to-provider ratio, a 28% workforce attrition rate, and over 100 open roles in revenue cycle operations alone. Instead of focusing on hiring more people, leadership asked: “How can technology change what’s possible?”
Key steps to support automation adoption included:
- Making automation a core strategy rather than a temporary fix
- Communicating clear goals and vision for automation initiatives
- Measuring success through continuous improvement targets—aiming for 30%, 40%, or even 50% gains over current performance
Deploying AI Agents at Scale
MUSC Health introduced AI Agents—digital workers capable of automating complex, multi-step tasks with adaptability. These agents have transformed revenue cycle operations by focusing on three pillars:
- Interoperability: Seamless integration with existing workflows, EHRs, and patient data systems to avoid disruption and enhance patient experience
- Productivity: Automation of high-volume, low-value tasks to free staff for patient-centered and strategic work
- Scalability: Moving beyond pilots to enterprise-wide solutions that deliver consistent results
Operational Gains and Revenue Impact
AI Agents now handle tasks such as eligibility checks, insurance verification, copay collection, and appointment reminders across MUSC Health’s enterprise. The results speak for themselves:
- Pre-visit completion rates increased from 25% to 47%, an 88% improvement
- No-show rates dropped from 14% to 8% through targeted reminders
- Time-of-service copay collections rose to 52%, up from 44%
As MUSC’s Executive Director of Digital Strategy and Operations notes, “Everything goes back to the revenue cycle. You can’t do anything with technology if you don’t include the revenue cycle.”
For healthcare leaders interested in how AI can enhance operational efficiency and revenue capture, exploring automation platforms like Notable’s AI Agents provides valuable insights. Further learning opportunities are available through AI-focused courses and certifications, such as those offered at Complete AI Training.
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