The last few years have been hard for just about everyone involved in healthcare, and not just because the revenue cycle has grown more complex. According to data from the Bureau of Labor Statistics, people on average now hold 12.4 jobs from age 18 to 54—nearly half of which are held before the age of 25. And that equates to just as many changes in their insurance coverage. Providers in turn must struggle to keep up with their patients’ seemingly ever-changing eligibility status, along with the details of what coverage is offered per level for a variety of payer plans. All that means it’s more challenging than ever to manage just about every aspect of the revenue cycle, and denials are no exception.
A recent MGMA poll found 69% of respondents had seen a noticeable increase in denials in 2021. Among those respondents, the average increase in denials was about 17%. And while there are plenty of reasons to explain the increase, we took the opportunity with our upcoming white paper, “Supercharge eligibility + estimates with a better payer intelligence engine,” to assess how eligibility-related denials factor into the equation.
How eligibility issues stir up more denials
Some of the results produced while developing that white paper were striking. When benchmarking denials for two similarly sized health institutions (both with similar patient populations and payer mix) we discovered a sizable difference in denial rates, one that indicated the first provider had processed millions less in denials. Further analysis revealed this provider dealt with roughly 35% fewer denials, which ultimately helped contribute to an additional $3-4M in revenue.
Generally, we expect such a discrepancy to be explained by a handful of familiar factors: a low clean-claims rate, an abundance of late filing or an escalating number of appeals left unattended to—issues normally associated with back-office management. But in this case those common factors did not dominate the narrative. Instead, the following stood out as the top drivers and differences between the two:
- A $39M difference in denials for patients identified as “not eligible”
- A $34M difference in denials related to coordination of benefits
- A $4M difference related to benefit maximums being exceeded
When we began to examine those discrepancies more closely, it became clear that there really wasn’t a back-office problem at all. In fact, client processes were considered quite lean and operated with consistent accuracy. Instead, problems were being generated much earlier in the rev cycle. By the time registration, scheduling and services had been rendered, there had not been notable mitigation to denial risks that should’ve been flagged. And with ever growing payer payment adjudication cycles, it seemed a steadily increasing denial rate was inevitable.
Looking for a root cause
In a study of Waystar clients, we found more than 10% of all registrants selected the wrong plan, and up to 35% of accounts triggered some kind of eligibility alert that indicated a potential denial risk. In other words, a significant portion of denials are caused by eligibility issues, one that could have been identified well in advance of them becoming problems. Finding other payers on file, replacement plans, CHIP, dental-only coverage and many other risk categories were simply not captured or flagged, which would have allowed end users to remediate the risk before a patient had even arrived for their appointment.
But what makes identifying these risks such a challenge? Ultimately there’s more to the problem than administrative oversight. The electronic data interchange (EDI) that makes modern eligibility solutions possible often includes message segments, plan codes and other critical identifying data that needs to be normalized and extracted. But that’s not possible without the right tools. If your front-end solution is not effectively crawling eligibility responses for risks like these, it’s time to upgrade your toolset and update your strategy.
Eligibility related denials are not always caused by issues in the coverage detection process, either. When it comes to common, multi-payer scenarios, benefit levels and coordination regularly cause problems in the claims adjudication process and ultimately have a significant impact on denial rates.
Older EDI solutions do not fully comprehend payer logic and often have a hard time identifying levels of coverage across different services. It’s no longer possible to rely on something like a ‘single STC 30’ EDI call to yield the benefit it (literally) once did. Now these benefits must be presented in a manner that lets staff easily interpret coverage and realistically determine when to expect payment from the patient and payer.
Wrapping it up: developing a comprehensive approach
You could be missing your single largest opportunity to strengthen your revenue cycle without a comprehensive approach to patient access eligibility. And one of the most important aspects of a truly comprehensive approach is shoring up your front-end processes to reduce the number of issues a claim might encounter as it moves downstream through the revenue cycle. Not only does this enhance the patient experience, it steadies revenue flow as it cuts down on the sort of trouble that would otherwise further drain staff time and resources.
Keep an eye out for our upcoming white paper, “Supercharge eligibility + estimates with a better payer intelligence engine,” for a more comprehensive look at what we’ve covered here. In the meantime, if you’re ready to tackle the challenges afflicting your front office, check out Waystar’s Financial Clearance solutions, which offer a smarter, simpler way to streamline areas like eligibility verification and prior authorization.