Every industry has a revenue cycle, but healthcare is one of the few where revenue cycle has become an entire operational discipline. Why? Because healthcare payment is uniquely complex, shaped by payer rules, CPT and ICD-10 coding, modifiers, regulatory requirements, documentation expectations, eligibility rules, authorization requirements, denials, and constant change. For decades, healthcare organizations have tried to manage that complexity with rules engines, decision trees, EDI, RPA, and manual workflows. Those tools helped, but they often only addressed pieces of the problem. When payer rules change, formats shift, or exceptions appear, traditional automation can break down and push the work back to people. In this Office Hours episode, Stuart Newsome is joined by Monte Sandler, Chief Operating Officer at WebPT, for a thought-leadership conversation on why healthcare RCM has remained so difficult to automate, why many organizations are skeptical after past technology disappointments, and how AI may finally help modernize the revenue cycle in a more dynamic, human-in-the-loop way. The conversation will explore what makes healthcare different from other industries, where traditional automation has fallen short, how AI should be realistically understood, and why the future of RCM is less about replacing people and more about helping teams work smarter, faster, and with better support.

Thursday, May 14, 2026, 11:30 am PT / 1:30 pm CT / 2:30 pm ET

Learning Objectives

By the end of this session, attendees will be able to:

  1. Explain why healthcare revenue cycle remains difficult to automate due to payer complexity, coding requirements, documentation expectations, authorization rules, and constant change.
  2. Differentiate traditional automation from AI-enabled revenue cycle support, including where rules engines, decision trees, EDI, and RPA fall short.
  3. Identify practical ways AI can modernize RCM operations while supporting human expertise, improving workflow resilience, and helping teams manage complexity more effectively.

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