Why You Need To Rethink Your Revenue Cycle Priorities

If there’s one thing I’ve learned in my 20+ years in revenue cycle, it’s that we tend to focus too much on the wrong things.

I get it. Denials, auths, claims follow-ups, and collections are loud, urgent problems. Payers make the process more painful every year, and health systems are constantly fighting for every dollar they’ve earned. I’ve been in those meetings, scrambling to improve denial rates, examining tightened margins, chasing down missing authorizations, and debating how much to invest in back-end automation.

But here’s the hard truth: you’re missing your biggest opportunity for quick wins.

The mid-cycle — specifically clinical documentation improvement (CDI) and coding — is where you can see the fastest and most efficient path to margin improvement.

And with the rise of generative AI (GenAI), there’s never been a better time to shift your internal focus.

A stronger mid-cycle means stronger margins

The problem with front-end and back-end revenue cycle fixes is that they still rely on payers. No matter how good your denial management is, you’re still at the mercy of an unmotivated payer. You submit a claim, you wait, you follow up, you appeal — it’s a constant uphill battle.

Mid-cycle optimization, on the other hand, is largely within your control. Unlike with prior auths or denials, there’s no need to deal with frustrating and time-consuming payer follow-ups, appeals, or complex processes for the mid-cycle. Proper coding, with verified clinical indicators and supporting documentation, before billing means faster payments and no A/R delays. Get everything right from the start.

Often overlooked, the mid-cycle is leaking millions in patient revenue that could be billed for today. The data speaks for itself:

68% of healthcare leaders say DRG optimization is still a problem, according to a HIMSS survey.

Traditional solutions — manual audits and rules-based technology — can’t keep up. Despite investing in multiple technologies and services to help, hospitals and health systems still leave 0.20–0.30% of net revenue on the table.

Based on our work with health systems, we developed a calculator to show how much revenue you could be leaving behind due to missed codes and poor technology. Try it out now.

Why generative AI should start in the mid-cycle

We’ve all seen the buzz around AI in healthcare, but not all AI is created equal. Many revenue cycle tools still rely on rules-based automation, which is static, limited in scope, and requires constant updates.

Are you still seeing “sepsis” in your coding when the documentation says “not sepsis”? Then you’re not using GenAI.

GenAI is different.

It enables software to rapidly and accurately understand complex clinical documents (such as chart records) that were previously opaque to computers, comprehend the clinical context, extract information from documents at scale, and use the data in meaningful ways.

At AKASA, we start with a foundation model trained on healthcare and refine it on a health system’s real clinical and financial data.

That’s game-changing for mid-cycle processes and teams because it enables:

• Comprehensiveness
• Speed
• Accuracy
• Transparency

This means analyzing 100% of encounters, reading all documentation, understanding context, capturing every quality indicator to reflect the true complexity of care, and providing evidence-backed justifications. That’s what a GenAI solution should bring you.

Hospitals already know coding and CDI are the backbone of accurate reimbursement. But now we have technology that can eliminate revenue gaps and optimize quality outcomes.

Gebrette Pritchett, a vice president at Stanford Health Care, recently gave a talk at HFMA Western Region Symposium with AKASA. As she told the audience:

“Generative AI is already here. If you’re not already incorporating AI tools into your workflows and revenue cycle, you’re behind.”

Want to know more about this technology? Here are 10 things healthcare leaders need to know about LLMs and GenAI.

Why AKASA is your best partner for GenAI in the mid-cycle

We’ve heard the noise in the market. We’ve heard your challenges with legacy technology that just doesn’t work the way you want it to. That your frustrations with margins are spiraling.

We understand the challenges in the end-to-end rev cycle. The ones keeping you (and us!) up at night. We’ve heard from our clients in patient access that they’ve got their prior auth right, but still aren’t getting the revenue they deserve. We’ve heard from the business office that denials are increasing despite the tools and process improvements that they’ve put in place.

We’ve taken all of our experience, from the front and back-end, and are focusing our efforts now on the mid-cycle.

Based on our work with leading health systems and academic medical centers, our mid-cycle approach is the most effective and efficient way to pilot GenAI technology and boost your margins.

We built Coding Optimizer™, a GenAI-powered mid-cycle solution, because we saw firsthand how much revenue was being lost due to coding inefficiencies.

Our approach is different. With Coding Optimizer, we:

• Tailor our AI to your health system, learning from your unique data and processes
• Examine every encounter from every service line — not just a sample — ensuring nothing slips through the cracks
• Uncover missed codes by reviewing all relevant clinical data, including documents, labs, vitals, and meds
• Autonomously recode every encounter from scratch, compares our findings to what was previously coded, prioritizes and presents the top opportunities for fast coder review
• Provide evidence-based justifications and quotes, providing recommendations you can trust and verify
• Offer an intuitive workflow, designed by our mid-cycle experts, that streamlines review time, making things more efficient for your team
• Showcase a dashboard that prioritizes high-impact, high-confidence opportunities
• Reduces reliance on outsourced vendors and audits
• Promise high accuracy across all major disease categories (MDCs)
• Deliver results quickly, with minimal lift

And we’re so confident in our ability to improve your mid-cycle performance that we go at-risk with our clients. If we don’t deliver results, we don’t get paid.

So here’s my challenge to you: stop chasing payer-dependent problems and start focusing on the revenue that’s within your control.

Rethinking your revenue cycle priorities starts now. Let’s make mid-cycle the foundation of your financial strategy. AKASA is ready to help.