Fast Track to Better Margins: How GenAI Is Transforming the Mid-Cycle

At Becker’s Hospital Review’s 15th Annual Meeting, AKASA brought together healthcare finance and technology leaders for a candid and energizing lunchtime executive roundtable on the future of the revenue cycle.

The session, “Fast Track to Better Margins: GenAI in the Mid-Cycle,” led by Amy Raymond, SVP of revenue cycle operations and deployment at AKASA, zeroed in on a critical focus: the mid-cycle.

Packed with real-world insights, peer conversations, and a compelling case study from Cleveland Clinic, this roundtable marked a turning point in how health systems are thinking about — and acting on — generative AI (GenAI) in revenue operations.

This talk inspired a tremendous amount of introspection about what is possible in the mid-cycle.

~ Chief Information Officer and Roundtable Attendee

Why the Mid-Cycle Matters More Than Ever

The mid-cycle — where clinical documentation and coding intersect — is uniquely positioned for transformation. Unlike front-end processes (e.g., authorizations) and back-end tasks (e.g., denials), the mid-cycle is fully within a health system’s control.

Amy Raymond emphasized this point: “You can’t always predict the payers. But you can control your documentation and coding.”

Yet 68% of healthcare leaders say that DRG optimization remains an unsolved problem. That’s billions in leakage — due to missed documentation, overlooked quality metrics, inefficient query processes, and more — hiding in plain sight.

GenAI promises to change that.

Polling the Room: Where Are We Now?

Two live polls of the room revealed just how much the conversation has shifted over the past year:

• Poll 1: Where is your organization currently in its GenAI journey within the revenue cycle?
  The majority in the room were in “exploration” mode, while a promising number reported they were actively piloting solutions.
• Poll 2: What is your biggest mid-cycle pain point?
  The top concerns were:
  • Current technology not meeting goals and needs
  • Staffing challenges
  • High rate of coding denials

These pain points set the stage for a deeper discussion.

Many heads in the room nodded when one attendee said, “A year ago, we were all scared of GenAI. Now we’re ready to embrace it. This is Season Two.”

Breaking Down GenAI

Before attendees dove into table discussions, Raymond grounded the room with a candid and accessible explanation of what generative AI actually is — and, just as importantly, what it’s not.

“GenAI isn’t just smarter automation,” she clarified. “It reads and understands — full context, not just in keywords. If a vendor hands you a bunch of crosswalks, rules, and checklists, that’s not GenAI.”

She explained how traditional AI tools often rely on rigid rule sets or keyword matching. These approaches struggle with complex documentation, often flagging coding and CDI opportunities that lead to false positives and clinician frustration.

In contrast, GenAI models like AKASA’s leverage large language models (LLMs) that are trained to understand the full clinical picture.

Your coders are a mile deep and an inch wide in their expertise. A GenAI model must reflect that — it has to be trained on the full code sets, clinics, and guidelines, then tailored to your documentation, workflows, and case mix.

~Amy Raymond, SVP of Revenue Cycle Operations and Deployment at AKASA

One of the most compelling aspects of AKASA’s approach is transparency. “Part of the fear around AI is not knowing how it got to a recommendation,” she acknowledged. “GenAI must show its work — and ours does.”

Attendees saw live examples of how AKASA’s solutions display direct quotes and evidence from the medical record to support each suggestion, making it easy for CDI teams and coders to review and quickly validate or reject.

Watch this video about why one mid-cycle leader thinks GenAI is the future of the industry.

Raymond also dispelled myths about implementation complexity. While some AI initiatives require major technology overhauls, AKASA’s solutions are designed to layer onto existing workflows and scale with each organization’s needs. And it’s not just fast in concept — it’s fast in practice. The GenAI can review more than 100 clinical documents in 90 seconds.

She also emphasized how GenAI can improve physician engagement by reducing unnecessary noise:

“The goal isn’t more queries — it’s better ones,” she said. “You want 70 meaningful queries, not 100 distractions. GenAI helps you focus where it matters most.”

Ultimately, her message was clear: GenAI isn’t just a new tool — it’s a paradigm shift. And the organizations that embrace its nuance and specificity will be the ones to unlock the most value, both financially and clinically.

One executive from Cleveland Clinic agreed:

“It’s not just about speed. It’s about consistency, accuracy, and scalability. This is technology we won’t want to live without in five years.”

Read more about the Cleveland Clinic-AKASA collaboration.

From Real Talk to Real Results: What the Tables Shared

Attendees broke into table groups to discuss current tools, wish-list capabilities, and success metrics. Here’s what emerged:

1. A disconnect between tools and needs

Many participants still rely on manual processes or computer-assisted coding (CAC) systems that have failed to meet expectations.

One attendee summed it up: “We tried a CAC, but coders ended up deleting all the suggestions. The false positives were just too high.”

Others cited the disconnect between inpatient and outpatient systems — noting that “patients don’t think in silos, and neither should our tools.”

2. CDI and coding must collaborate

Several groups emphasized the need for tighter integration between clinical documentation integrity (CDI) and coding teams. This isn’t just operational — it’s financial.

As one leader noted: “It’s time to stop blaming physicians for under-documenting and start giving mid-cycle teams tools that highlight what matters, when it matters.”

GenAI tools like AKASA’s help bridge this gap by identifying missed documentation and coding opportunities and allowing CDI and coding teams to work from a unified worklist. They can review cases together and exchange comments in the integrated platform for the other to review. Codes from query opportunities are added to the list for coders to review.

Raymond explained: “GenAI should show its work. That transparency builds trust — with coders, CDS, physicians, and compliance teams alike.”

3. Speed, ROI, and scalability are non-negotiable

When asked what matters most when evaluating new vendors, attendees were clear:

• Fast time-to-value
• Measurable ROI
• Seamless EHR integration
• Vendor trust and healthcare credibility

And they don’t want another “rip-and-replace” implementation. They want GenAI that layers onto existing systems and scales with them — not against them.

What Sets the AKASA Approach Apart

During the session, Raymond broke down how AKASA’s GenAI technology is different — and why it’s built to deliver results that matter:

• Tailored model per health system: Instead of a “one-size-fits-all” LLM, AKASA refines its foundation model with each client’s documentation, coding styles, and specialty lines.
• Trained on real healthcare data: 43M+ clinical documents and 2.4M+ encounters form the training base.
• Transparent outputs: Every suggestion is backed by citations from the clinical record — no “black box” decisions.
• Integrated workflow: Coders and CDI teams can collaborate in one shared interface.
• Expansive coverage: AKASA’s solutions review 100% of encounters and surface high-impact opportunities for review — reducing the need for manual audits and freeing up FTEs.

Looking Ahead: The GenAI-Enabled Revenue Cycle

As the session wrapped, Raymond offered this call to action: “GenAI is already changing the mid-cycle. Don’t wait to explore its potential.”

The days of fragmented tools and endless audits are fading. What’s emerging is a new standard — one where GenAI works with your teams to drive revenue, improve quality, and enhance compliance.

Perhaps most powerfully, as one participant put it, “This gives us back time — and confidence — to focus on care.”

Want to see this technology in action? Check out the AKASA suite of products built for the mid-cycle, including Coding Optimizer and CDI Optimizer.