Thomas Thatapudi, Chief Information Officer for AGS Health, recently shared his insights on one of the industry’s most transformative developments: agentic automation. He explained what agentic automation really means, particularly in contrast to traditional robotic process automation (RPA), and explored how it’s reshaping revenue cycle management (RCM). With real-world examples, strategic foresight, and a clear-eyed focus on financial outcomes, Thomas offers a compelling vision of how artificial intelligence (AI) agents can mimic human judgment, streamline operations, and deliver measurable value to healthcare organizations.
Q: What does “agentic automation” mean, especially in the context of healthcare RCM? How is it different from traditional automation?
A: This is an exciting question because automation has been around for a while. Historically, healthcare organizations have used robotic process automation, which automates simple, rule-based tasks. Scripts are written for repetitive actions that don’t require any human judgment.
Agentic automation is an exciting, pivotal shift. Agentic automation mimics human logic, judgment, and decision-making. These systems understand context and make decisions, like a seasoned persona. More complex tasks previously reserved for human experts can be handled effectively with better accuracy, speed, and cost-effectiveness.
Q: How can agentic automation be applied in the healthcare revenue cycle? Can you give some real-world examples?
A: We’re in a period of rapid discovery, and new use cases are emerging very fast. One promising area is accounts receivable (A/R). We're already using AI to triage cases: complex, high-dollar accounts go to more experienced human agents, while simpler ones are handled by automation.
For example, we're building agentic AI models to call insurance payers. These AI agents can navigate phone menus, input claim IDs, and wait on hold. When a representative answers, the AI can connect a human agent to complete the call. In some cases, especially with straightforward A/R calls involving low-dollar amounts, AI agents can handle the entire call. They can gather the required answers and update the electronic health record (EHR).
Q: Many healthcare leaders are familiar with RPA. How is agentic automation an evolution beyond RPA in terms of capabilities and impact on revenue cycle operations?
A: Healthcare leaders have used RPA over the last 15 years, but it has been limited in its scope. It handles a particular problem that doesn’t involve judgment and is completely rule-based. This kind of automation is a point solution that is not usually repeatable or scalable.
Agentic automation can take the work further, mimicking how a human understands workflows, makes decisions, and handles exceptions. There is a shift from thinking in siloed parameters to integrated decision-making within a single intelligent system. For example, instead of a human looking at a dashboard, consulting a manager, and then acting, the AI agent reads the analytics, decides the next best action, and acts—all autonomously. Additional paradigms will continue to emerge as we see the evolution of AI over the next two to four years.
Q: What are the key benefits healthcare organizations can expect from agentic automation, both in terms of financial outcomes and operational improvements?
A: It always comes back to value and operating with best-in-class margins, which enable healthcare organizations to do what they do best: deliver clinical care to their patients.
Healthcare organizations face constant margin pressure as payers deny more claims, regulations grow, and costs increase. Agentic automation can help deliver value, including:
- Faster turnaround times
- Faster collections
- Reduced denial rates
- Improved coding accuracy
- Increased staff productivity
Technologies and investments are the right solutions when they translate to better financial outcomes and operational efficiency. Innovations must tie back to financial outcomes to ensure they bring significant value to our customers.
Q: For healthcare organizations just beginning to explore the potential of agentic automation, what advice would you give on how to get started and the initial steps they should take?
A: The first step is getting your data AI-ready. Right now, critical data lives in silos including EHRs, billing systems, analytics dashboards, and third-party providers. This fragmented data isn't AI-friendly or “talking” to each other, and there is no data governance.
Once the assets are together and the data is AI-ready, focus on high return on investment (ROI) applications, including:
- Predicting denials
- Streamlining prior authorization processes
- Automating clinical documentation
- Performing autonomous coding
Have shorter innovation paths and proceed with humility. If something doesn’t work, move on. Always tie initiatives to ROI because, without ROI, the technology and solutions don’t matter.
Hear more from Thomas about leveraging the power of agentic automation to elevate your healthcare revenue cycle management operations and improve financial outcomes.
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