Generative AI is rewriting the playbook for revenue cycle management operations at hospitals and health systems. Yet, many organizations are still considering modernizing their RCM systems solely through automation.
This was a theme of a roundtable sponsored by AKASA at the Becker’s Hospital Review 15th Annual Meeting and facilitated by Amy Raymond, senior vice president for revenue cycle operations and deployments at AKASA.
Three key takeaways:
- Technology is being widely used to improve RCM processes, but much of it falls short. Despite huge investments made in revenue cycle technology, many organizations still face issues such as failing to optimize diagnostic-related groups — a key component of the mid-revenue cycle.
- Optimizing the mid-cycle is key to improving margins. This is the only part of the revenue cycle that organizations can fully control, unlike payer-dependent prior authorization and denials management. “The mid-cycle offers a direct path to impact but is often overlooked,” Ms. Raymond said.
- GenAI can improve the accuracy and efficiency of clinical documentation improvement and coding. These are two areas in organizations’ mid-cycle operations where optimization is key to boosting margins. GenAI can enhance these areas through improved compliance, improved metrics and revenue yield.
“The advent of GenAI unlocks the ability to interact with the medical record in a programmatic, automated manner,” an executive at a Midwest health system that recently partnered with AKASA said. “There can be up to 99 secondary diagnosis codes on any given claim. Being able to capture the right combination of those codes accurately and reliably is at the center of our ability to be reimbursed correctly.”
“It’s a huge advancement to be able to expand the ability of your workforce once they are working alongside GenAI,” Ms. Raymond said, reflecting on the impact of GenAI on the roles of mid-cycle team members.
