Generative AI in healthcare payments is top of mind for revenue cycle leaders. In a recent study, 90% say they plan to invest further in AI soon.
But how many RCM professionals fully understand how AI and gen AI impact healthcare payments?
“It’s okay if you don’t!” said Chris Schremser, Waystar’s Chief Technology Officer, at the 2024 Waystar True North™ client conference. “We shouldn’t be shy when it comes to asking questions about artificial intelligence or gen AI. It’s the only way to uncover what’s possible — and then put those innovations to work.”
In his session — The foundation and future of AI + gen AI in healthcare payments — Schremser covered:
- Key findings from the Waystar + Modern Healthcare report on AI and its ROI
- How organizations are using AI to:
- Maximize reimbursement
- Improve efficiency
- Prevent denials
- Enhance patient financial care
- Use cases for gen AI, including:
- Claim rule generation
- Medical necessity evaluation
- Monitoring payer behavior
- Infrastructure requirements for successful gen AI in healthcare payments:
- Technology
- Data
- Expertise
- Execution
Critically, Schremser also offered a simple explanation of the evolution of AI in healthcare payments, as well as four key facts RCM teams need to know now.
Watch (or listen to) the session on demand or read on for a primer.
The evolution of AI + gen AI in healthcare payments
Most healthcare finance leaders who are using AI have seen positive returns.
“AI leads to smarter decision-making, faster execution, and fewer errors,” says Schremser. “Generative AI allows us to take tasks that were historically impossible and make them very hard. Make no mistake — these things are still really, really hard. But they are now possible, and that’s the distinction.”
How does generative AI in healthcare payments work?
In the simplest terms, these technologies build on one another.
When all the different pieces of AI work together correctly, we can get machines to:
- Work like humans to complete tasks automatically (artificial intelligence)
- Identify patterns in data and make predictions (machine learning, neural networks)
- Decide if their predictions are right or wrong and make changes (deep learning); and
- Create new content with little to no human intervention (generative AI).
4 key facts about AI + gen AI in healthcare payments
In addition to discussing the evolution of AI in healthcare payments, Schremser revealed Waystar’s 2025 roadmap and these critical truths:
- If you train a model on bad data, you get bad results.
- It will never be cost-effective to use gen AI to solve small problems.
- Efficient AI only involves humans for review, verification, or complex issues.
- If gen AI doesn’t show ROI, it’s a waste of time.
“The truth is generative AI is really expensive, so if we’re using it to solve small problems, we’re wasting our time,” says Schremser. “But, if we can use gen AI to create things we can review, edit, and approve — while the system checks everything else in the background — the return on investment is high.”
