Challenge

Clinical documentation integrity, or CDI, is a field that gets more complex by the day. That’s something that Terri Meier, the Assistant Vice Chancellor Revenue Cycle at the University of Arkansas for Medical Sciences (UAMS), and her team have known for years.

Back in 2022, the CDI program at UAMS was already a point of pride for the Arkansas organization. But even with impressive statistics — boasting over 90% coverage of diagnosis-related groups (DRGs) and achieving 85th percentile in MedPAR —Meier knew that in the rapidly evolving landscape of patient care, coding, and billing, her team would need to adapt if they wanted to maintain their advantages.

That’s because as regulatory requirements expand case documentation becomes more complex. Previously, information was isolated to a few sections within a patient chart.

Now, details could be anywhere increasing the time to fully review a patient chart exponentially.

The team soon found they were hitting the limits of people’s capacity to review every data point and ensure complete capture for every chart.

So, you can try to have broad coverage across all charts, and then take a slice of charts and have expert driven deep dives, Meier explained. “But what happens to all the charts that don’t get that deep dive?”

Solution

Initially, Meier found an interim fix: implementing technology that could help the team prioritize which charts might need that deep dive. But it was a temporary solution. The number of important diagnoses that impact quality, mortality, readmission and SDOH only continues to grow, meaning that the number of missed opportunities — or, charts that needed a more thorough review but weren’t prioritized for one — would only grow.

Knowing that payers were heavily investing in AI, Meier’s gut told her that there must be an AI solution that could augment her team’s skills. But payers often employ five or more AI vendors to review cases for payment integrity, a level of tech stack that was out of UAMS’ reach.

“How do we compete with that?” Meier wondered. For her, the answer was to work smarter, not harder.

“If we can’t support multiple levels of technology, what is the best single solution for us that could help level the playing field?” she wanted to know.

That solution needed to be able to sift through all of the charts at UAMS and identify any opportunities to capture missed or inaccurate diagnoses. In an ideal world, Meier thought, AI would be able to handle the labor-intensive work required to do a deep review of every data point in a patient’s chart — a task that was becoming humanly impossible to perform — and then surface the cases that actually needed the clinical judgment that only UAMS CDI specialists could provide.

Oh, and if that solution could minimize the financial risks to the organization, the Vice Chancellor of Revenue Cycle would definitely be interested.

Results

With SmarterPrebill, the CDI team at UAMS now feels confident that 100% of the charts sent to payers are accurate. That’s translated to some tremendous financial success. $5.3M in total DRG revenue per year, to be exact.

On top of that, SmarterPrebill has had a tremendous impact on UAMS’ CDI team. The Sysiphian task of reviewing every data point within every chart is gone.

“AI is doing the heavy lifting on the front end, the deep review of every data point, which takes minutes or even hours of low-level administrative work out of their day,” explains Meier. “It’s a more productive, more satisfied team.”

And, UAMS has recently expanded its footprint in Arkansas — adding two new facilities in the last year. Both now use SmarterPrebill.

What's next

For both efficiency and revenue generation standpoint, the next thorn in the CDI team’s side is populating appeals letters. On average, each takes 60 minutes for the team to compile. Meier and the team are already looking to expand their collaboration with SmarterDx by using SmarterDenials, a clinical AI solution to populate appeals letters.