Shifting Mindsets: Preventing Denials Before You Have to Appeal Them

By: ​Ashley Hunter, MBA, CHFP, and Briauna Driggers

​Rising denial rates and delays in claim payment are a major concern for every health organization’s revenue cycle in 2025. Denials ultimately cost organizations money and can potentially result in additional revenue loss. Dealing with write-offs for claims that cannot be appealed is an issue, but the larger and more concerning problem is the high volume of incoming denials. If an organization does not have the necessary staff resources to work the incoming denials, these account balances will remain in AR until they ultimately must be written off due to timely filing.

Many people focus on denied claims as they come through the door, spending their time and resources submitting appeals prioritized by dollar amount. This becomes difficult to keep up with at a high volume and requires a full mindset shift from appealing denials to preventing those denials from happening in the first place.

Root cause analysis is the primary tool that can be utilized in denial prevention. This type of review goes beyond pie charts and line graphs showing what the common denials are and instead allows for the identification of why claims are getting denied. Once a root cause can be found, processes and operations can be remedied to ensure future payment of claims is received on the first submission. 

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Understanding Denial Data Fields

​The data that is used to initially build reports for denial trending comes from responses payers are sending back within the Explanation of Benefits (EOB). Every charge line item within a claim will have a code from the payer to explain why they are paying or denying a claim. There is only one set of codes that all payers utilize. These data fields must be included in any types of reports you build to allow for enough details to properly analyze a denial’s root cause.

Denial Reason Code – A code the payer sends to communicate why they are denying payment for a claim

​Example Denial Reason Codes:
- CO-197 - Preauthorization/notification absent
- CO-16 - Claim lacks additional information needed for adjudication
- CO-4 - Inconsistent procedure code and modifier 

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​Every denial code will have a two-letter abbreviation in front of it. This provides additional details on the type of adjustment the payer is communicating. The most utilized code is CO, which indicates the adjustment relates to the contractual obligation between the provider and the insurance payer.

• CO – Contractual obligation
• PR – Patient responsibility
• PI – Payer-initiated reductions
• OA – Other adjustments

​In addition to a denial reason code, payers will send remark codes. For denial codes that are vague or do not provide detailed information as to why the claim is denied for that specific reason, remark codes will generally give some sort of guidance on the root cause.

Denial Remark Code – A second code given in addition to the denial reason code to provide further guidance on the reason a claim was denied
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Example Denial Remark Codes:
- MA51 - Missing or invalid CLIA certification number
- N205 - Information provided was illegible
- MA82 - Missing or incorrect billing information for a physician

Every healthcare organization utilizes denial categories to group together denial reason codes that share a root cause type. For example, denial reason codes 197, 198, and 284 are all related to authorizations, so they are grouped together as authorization denials. These categories typically vary from organization to organization. If your organization does not currently have any type of category or class mapping, this can be done by reviewing denial reason codes and assigning them to a category. Denial categories are typically the best place to start when analyzing denials for trend identification.

​Denial category – A grouping of denial reason codes that share similar root causes for trend identification

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Identifying Trends

​In order to analyze the root cause of an opportunity, trends must first be identified. The best data field to investigate patterns within data is the denial category. Trends can also be identified by fields like top denying payer, denial reason code, denied procedure code, and more. Typically, all of these trends will link back to a denial category. The primary question being asked should be “Why are claims being denied?”. 

The first step in answering that is identifying a category that provides some guidance into the why. Once a trend is identified, root cause analysis begins to answer the who, what, when, and more relating to the ultimate source of the denials.

A key tool for reviewing denials is reporting. Reports should be customized for each organization to ensure the data is relevant and beneficial to them specifically. When creating data visuals for denial reporting, the information should not be so high-level that further investigation is not possible, but also not so detailed that there is too much data to digest.

A basic visual to include within a denial report is denial category denial amount by month. This can provide a starting point for root cause analysis, as this begins at the highest level of detail. The goal of identifying trends is to identify a very high level, but impactful trend. In the graph pictured above, there is a strong trend showing authorization denials growing in dollar amount throughout the timeframe. Other beneficial measures or visuals include denial rate, open denial amount, top denied locations/offices, and denial by specialist or physician. 

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Root Cause Analysis

Now that the trends negatively impacting an organization financially are identified, it’s time to drill down into the root cause to pinpoint the exact action or process that is resulting in this unfavorable payer response.

The first step in root cause analysis is identifying a trend. To determine the exact cause, further exploration of the data is necessary, focusing on mid-level and precise details. After the initial discovery of a pattern within a denial category, the next step is to delve into these mid-level details. By adding more mid-level information, you can explore additional levels of detail.

Examples of Mid-Level Details:

• Denied CPT code
• Denying Payers
• Denial Reason Code
• Denied Provider

​Once the additional details have been explored, a report of actual denied claims with filters based on selected data points can be run to start analyzing examples. When examples are being reviewed, items outside of the claim and EOB should be considered. The root cause of a denial can sometimes be on a claim; however, it is essential to review all documentation and processes leading up to claim submission to understand the reasons behind the items listed on the claim.

Additional items to review for root cause analysis outside of a claim or EOB:
 - Registration notes
 - Authorization notes
 - Patient chart/ clinical documentation
 - Patient demographics

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What This Means for You

​Addressing the increasing rates of claim denials is crucial for the financial health of every healthcare organization. By shifting the focus from responding to denials to proactively preventing them, organizations can significantly enhance their revenue cycle management. Understanding denial data fields, categorizing denial reasons, and identifying trends are integral steps in developing a comprehensive strategy to minimize denials and understanding root cause analysis. By investing time and resources into preventive measures rather than reactive ones, healthcare organizations can safeguard their revenue, improve operational efficiency, and ultimately deliver better care to their patients. Emphasizing denial prevention not only leads to timely payments but also strengthens the overall financial foundation of healthcare providers, making it essential for every organization to embrace this proactive approach in 2025 and beyond.