The Remaining 20%: The Critical Role Denials Play in Lost Revenue (Part 1)

This blog post is part one of the series. View Part Two. View Part Three.

In revenue cycle management we’ve always been of the mindset that 60-80% of billing is clean when the order is received and relatively simple to do well; however, it is how the remaining percentage is tackled that will determine whether your efforts are truly successful. That could never be truer than with the climate we are in today. In addition to the compression of reimbursement across most segments of our industry, we’re faced with a taxing payor policy environment that lends itself to troublesomely dynamic, high volume failure points. To successfully acquire what would otherwise be lost revenue, we first need to understand our areas of greatest vulnerability.

In this three-part blog series, we will cover trends in denials and appeals, prior authorization, and payor policies that drive — or prohibit — proper revenue recognition. In Part 1, we’ll discuss the related trends in denials and appeals.

The most common denials types are:

However, the way in which these denials are categorized by the payors and the strategy behind successful appeals varies between payors and each segment of the industry. Routine pathology denials are not flagged in the same manner as NGS denials, which differ from clinical denials. To understand those variances, XiFin performed an analysis by leveraging recent transactional volume contained in our extensive data warehouse.

Each year, XiFin’s RCM platform processes more than 120 million laboratory and pathology accessions, exceeding $40 billion in gross billings. For this study, we assessed more than 34 million transactions, by payor group, denial reason, appeal type, and revenue generated.*

Data was aggregated by in-network and out-of-network payors, then subdivided into categories based on segment (Pathology, Molecular, Hospital, Clinical) and by Payor Group (BCBS, Commercial, Medicaid, Medicare, etc.). For purposes of XiFin’s data study, it’s worth noting that many of our Molecular customers perform proprietary, high dollar testing, of which the data outputs for this segment generally do not include routine molecular and pathology testing.

The above represents percentage of claims denied by industry segment. With exception of Medicare, denials in pathology and molecular contribute to no less than 10% of claims submitted, and in some cases as high as 20-45%. This is a substantial amount of revenue potentially lost if not addressed within a timely manner. In addition:

Nearly 60% of the claims denied by Medicaid for molecular customers in 2019 were for the CO197, or Prior Authorization, the largest denial type in the molecular segment. 

​Contributors to Medicare Advantage (MA) denials range from rudimentary billing errors, including filing a patient to the wrong Medicare plan, to more complex trends in how Medicare Advantage Organizations (MAOs) managed their benefit plans and claims processes. While MA plans should follow Medicare guidelines, in practice that is not always the case. It is not uncommon to experience a higher volume of denials, particularly for coverage, from MA plans as compared to Medicare.¹ Understanding Medicare guidelines is critical in systematically determining when an MA plan has not followed the overarching rules, thus allowing laboratories to realize an opportunity to successfully overturn the denial through strategic and efficient appeal processes.

CO97 (denied service or procedure was included in the allowance or payment for another procedure or service) accounts for 50% of the Blue Cross/Blue Shield (BCBS) denials and 31% of commercial payor denials in 2019.

CO97 denials are based on NCCI edits, further emphasizing the adoption of CMS guidelines into commercial payor policies. A payor analysis based on denial trends shows us the impact those edits have on back-end denials and subsequently augments our RCM workflow, such as building robust front-end edits to catch specific denial scenarios proactively.

The average for in-network denials is about 15% of claims; however, that number doubles to 30% or higher, for out of network (OON) claims, depending on segment and payor.

• BCBS is the most prevalent culprit of OON denials; their largest OON denials being PR96, or Non-Covered denials, which accounts for more than 30% of all OON blue denials.
• OON commercial denials are largely driven by PR242, or Services Not Provided by Network or Primary Care Provider. PR242 accounts for 42% of non-contracted commercial plan denials, as compared to only 12% for BCBS.

PR242 and PR96 denials serve the same purpose, however, each payor has communicated that purpose by utilizing completely different reason codes. Payors using different denial codes to deny for the same thing is not unusual, and yet is another reason it’s critical to have transparency into your trends and your data so you can establish efficient and effective workflows to address these subtle nuances of payor behaviors.

In summary, denials drive lost revenue. Proactive, front-end edits and automated workflows to resolve errors on the back end are necessary components of RCM workflow, but appeals are also becoming a critical component of revenue recognition.

As denials have evolved, so have our means of overturning them. In part two of this blog series we will substantiate trends in successful appeals. Using meaningful data, we studied which payors experience higher appeal success rates, what second and third level appeals contribute to success, and what percentage of revenue appeals drive across our business. 

*XiFin routinely performs trend assessments by aggregating data across all customers in order to understand industry trends and productivity bottlenecks. In addition to sharing insightful content with customers, this information drives continuous development of new functionality and automation within our billing platform.

Sources:

¹HHS OIG Medicare Advantage Appeal Outcomes and Audit Findings Raise Concerns About Service and Payment Denials. https://oig.hhs.gov/oei/reports/oei-09-16-00410.pdf

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