As electronic health records systems and vendor tools have become more and more sophisticated, a myriad of metrics and KPIs are readily available to health systems with the click of a button. Some executive scorecards can have upwards of 20-30 metrics for ongoing reporting! A system’s denial rate is typically one of these metrics but is usually not one that is fully understood due to the complexity of denials data.
Since denials touch all aspects of the revenue cycle and clinical processes, your system’s denial rate (if accurate) can be an excellent indicator of the health of your overall operations. Often, hospital leaders have access to a denial rate but do not know what it actually measures. For example, incorrectly categorizing remit codes may understate denials if key denial codes are excluded inappropriately. Additionally, duplication in data or measuring all types of denials (secondary, tertiary, etc.) can result in overstating denials and obscure what problems really need to be solved.
A good denial metric can give insight into two areas:
- How much revenue leakage is actually occurring in your system
- How well you compare across the industry and if there are target areas you should focus on or shared learnings from other hospital systems
A denial rate allows you to have an excellent indicator of where you should drive process, technology, or payer relations changes to prevent denials and stop revenue loss. Furthermore, an accurate and well understood denial rate will allow you to see if denials are reducing. Baselining and subsequent tracking of this metric will provide the roadmap to financial success.
Creating the Numerator
The first step in building the denial rate is creating the numerator. While this can also be a volume measure, it is important to first define this in terms of gross charges denied. The following framework should be applied when analyzing denial data:
- Delineating which Claim Adjustment Reason Codes (CARCs) should be considered a denial – CARCs should be categorized into Contractual Allowances, Adjustments, Patient Responsibility, and Denials. This is the first fundamental step in ensuring that you are calculating the correct figures. Further, denials should also be classified by category (Authorization, Eligibility, Medical Necessity, Coding, Non-Covered, etc.) to drive trend identification.
- Considering primary vs. secondary or tertiary denials – in this case, it is vital to consider the goal of the metric. If the goal is to calculate the percentage of billed charges that are lost to denials, we should only bring in primary denials as secondary or tertiary will overstate how much revenue is lost. Further, a “total” denial rate can be built as a secondary metric to capture all denials as it is also important to capture rationale on why secondary payer denials may be happening.
- Considering initial vs. subsequent denials – the same reasoning as #2 applies here. Only initial denials should be considered for our main denial rate as subsequent denials will overstate the revenue leakage. Going further, picking the initial denial can be tricky if two denials come on the same day. HFMA guidelines recommend picking an arbitrary denial on the claim. However, if both denials detract from the revenue, then it would make sense to combine the amounts to set as the denial amount for that encounter.
Once the above factors are considered in the denials data, you are now able to arrive at the denied gross charges for a specified period (reporting should be done at least on a monthly basis.). There should be additional data analysis done to ensure that duplication does not exist in denials data.
For example, if you are seeing denied charges for an encounter that are greater than the total billed charges for the encounter, this should be a red flag to review further. There can be data cleaning and manipulation steps put in place to ensure that duplication is eliminated or minimized.
Additional complexity
If a dedicated team exists that can focus on continuously analyzing and reporting on denials data, there are more sophisticated measures you can take to hone in on the most problematic areas:
- Defining controllable vs. uncontrollable denials – splitting the rate into two parts allows you to judge what is internally impactable vs. what should be pursued in payer meetings/negotiations
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- Controllable – failure to follow revenue cycle policies or guidelines (for example, a pre-authorization was not obtained for a service that requires one.)
- Uncontrollable – certain payers require protocols that cannot be done prior to bill submission (for example, invoices or itemized bills required after patient visit that the payer does not allow during initial bill.)
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- Defining denial codes used by certain payers that do not actually lessen revenue
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- Since payers use CARCs non-uniformly, what might be considered a denial for one payer might be an informational code for another. With sufficient research, you can define certain CARC and payer combinations as informational instead of an actual denial. This is important as it refines what is actually detracting from your revenue.
- Additionally, some payers might use CARC/RARC (Remittance Advice Remark Code) combinations as informational vs. a denial. These can also be excluded after the necessary research has been done.
- A committee who performs quarterly reviews of the data to judge what should be a denial vs. not is an ideal approach to identify new groups that should not be denials. This is due to payer behavior on CARC usage changing periodically and without warning.
Creating the Denominator
Initial denied charges typically remit up to three months after the billed date. The recommended approach would be to average the last three months of total billed charges to act as the denominator. The formula would then be:
Denial rate = Current month denied gross charges (initial denial, primary payer only) / Average of most recent 3 months of billed charges
Summary
Once the denial rate is established, you now have the information available to start improvement plans. Best practice rates live in the 5% – 10% range, but rates across the industry have been increasing from “10.15% in 2020 to 11.99% by the end of Q3 2023” and being “even higher for inpatient care: 14.07% through Q3 2023” according to an HFMA analysis. If your system is having issues with inpatient denials, please check out this article by PinnacleHCA’s own Vickie Bridge on tactics to prevent inpatient denials.
Staying vigilant with denials research and improvement plans is necessary to get to best practice levels. The denial rate can be continuously refined as more analysis is completed and payer behavior is more understood. This measure should become one of your key metrics and the “North Star” of the health of your system’s operations.
Please reach out to Ehson Afshar at [email protected] if you would like more information and/or to have a discussion around challenges with your system’s denial rate or analytics.
