What is the First Pass Resolution Rate (FPRR)?

The efficiency of a billing process distinguishes a smooth revenue cycle from a disrupted one. Since the medical billing process is complex, practices must ensure each step is optimized. 

But the question is, how do billing professionals measure billing efficiency? One important metric is the First Pass Resolution Rate (FPRR).

FPRR is an essential key performance indicator (KPI) in healthcare revenue cycle management (RCM). It measures the percentage of claims successfully processed and paid on the first submission. Simply put, it calculates the total percentage of claims that do not need:

• Correction
• Resubmission
• Rework

First Pass Resolution Rate is an indicator of operational efficiency within a practice or billing department. If a practice has a high FPRR, it indicates that claims are successfully resolved without additional intervention after submission.

Conversely, a low rate may indicate issues in areas such as:

• Patient registration
• Eligibility verification
• Medical coding
• Documentation
• Payer-related processes

All of these problems create avoidable claim failures, which bottleneck the revenue cycle. 

Importance of First Pass Resolution Rate in Medical Billing

FPRR is an accurate metric because it measures the result of the first attempt claim. Other metrics, such as the number of claims sent and the efficiency of edits, do not fully represent the billing team’s efficiency.

On the other hand, First Pass Resolution Rate indicates the percentage of claims successfully resolved during the initial submission cycle. Each time a claim fails the first pass, it creates compounding costs for the practice:

• According to 2023 statistics by the Kaiser Family Foundation (KFF), less than 1% of denied claims were ever appealed. Thus, a failed first pass may increase the risk of delayed payment or potential revenue loss.
• Delayed payments increase the gap between care services and generated revenue.
• Failed first passes may contribute to higher AR aging and increased AR days.
• Additional time, cost, and resources are required to identify, rectify, and resubmit claims.

Moreover, practices with a consistently low FPRR likely have a systematic problem in their billing system. Therefore, it’s crucial to track the rate weekly by:

• Payer
• Service line
• Provider 

This tracking can reveal problematic areas, allowing targeted fixes rather than trying to reset the billing cycle completely. 

How to Calculate First Pass Resolution Rate (FPRR)?

Practices can calculate the FPRR for any time period, i.e., weekly, monthly, or quarterly. This can be done using a straightforward formula mentioned below:

First Pass Resolution Rate  =   (Claims Resolved on First Submission  ÷  Total Claims Submitted)  ×  100

Consider the case where a practice submits a total of 1,000 claims. Out of these 1,000 claims, 800 are resolved successfully on the first submission. In this scenario, the First Pass Resolution Rate can be calculated as:

(800 claims paid first pass  ÷  1,000 total submitted)  × 100  =  80% FPRR

First Pass Yield vs. Clean Claim Rate

Billing professionals often use first pass yield and clean claim rate. So, are they the same? Although they are used widely in RCM discussions, they measure different things. 

If practices fail to understand the difference, they may assume good billing performance, while their practice suffers operationally and financially. The following table explains the differences between first pass yield and clean claim rate. 

	First Pass Yield	Clean Claim Rate
Definition	The percentage of claims successfully processed without correction, resubmission, or additional intervention after initial submission.	The percentage of claims that meet all payer and internal billing requirements. They pass claim edits before submission.
What it measures	Measures the effectiveness of first-attempt claim resolution performance of the revenue cycle. Shows how often claims generate payment on the first attempt.	Measures the accuracy and efficiency of the claim preparation process before payer submission.
Revenue impact	Closely associated with revenue performance. Reflects claim conversion into payments.	Indirectly related to revenue because it focuses only on claim accuracy and submission.
Impact of claim rejections	Any claim rejected by the payer or clearinghouse and requiring resubmission negatively affects the FPRR.	A rejected claim that is corrected before submission may still be counted as a clean claim.
Impact of claim denials	Claims initially paid but later denied or adjusted are generally tracked separately from FPRR.	Clean claim rate does not indicate post-submission issues.
Common benchmark	90% or higher.	95% or higher.
Best used for	Evaluating overall revenue cycle effectiveness and payer performance. Also determines the payment collection ability without additional work.	Evaluates front-end billing processes and claim preparation accuracy. Reveals opportunities to reduce submission errors.

Note: Common target ranges vary based on specialty, payer mix, and organizational processes 

The Critical Difference

To summarize the table above, the clean claim rate measures the accuracy of claims before submission. This evaluates whether a claim passed all edits before submission. 

On the other hand, the first pass yield or resolution rate measures the claim outcome after submission. Therefore, it evaluates whether the claim was resolved and paid on the first submission.

Common Reasons Why Claims Fail on the First Try

Claims may fail on the first attempt due to small recurring errors that practices must identify and address. Identifying which reason applies to your practice is the first step to a streamlined revenue cycle. Your claims may fail on the first attempt because of:

Front-End Registration Errors

Front-desk errors can often trigger automatic payer rejections even before it is submitted for adjudication. Errors in eligibility verification may include:

• Mismatches in the date of birth and the insurance ID numbers
• Missing subscriber information
• Inaccurate patient demographics

Such errors should be reviewed on each patient visit to ensure all patient information is complete and up-to-date.

Specificity and Coding Errors

The most common coding-related first submission failures vary by practice and may result in claim denials or audits. They often indicate coder training gaps and may include:

• Missing required modifiers
• Non-specific ICD-10 codes  
• Incorrect CPT codes

Coverage Verification Failure

Inexperienced front-desk staff might only verify patient information during registration and not on the date of service. 

However, practices should note that patient eligibility may change between scheduling and the date of service. Checking eligibility on the day of service can help identify:

• Coverage terminations
• Limitations or exclusions
• Changes in the coordination of benefits 
• Deductible status changes

No Prior Authorization for Applicable Services

Missing authorizations are a leading cause of claim denials. Therefore, billing teams must receive prior approvals for new medications, specialized treatments, and other procedures. If authorization is obtained after services are rendered, the claim may be denied depending on the payer’s policy.

Best Practices to Optimize First Pass Resolution Rate

First Pass Resolution Rate is a clear indicator of a smooth billing process. If a practice has a poor FPRR, it will likely face financial challenges. Here are some best practices to ensure a high rate:

• Invest in specialty-specific coder training and update processes with each Medicare Physician Fee Schedule (MPFS) cycle to reduce coding errors affecting FPRR.
• Set a claims submission target within 48 hours of service to reduce delays and maintain a smooth revenue cycle.
• Verify benefits and eligibility on the date of service, not just during patient scheduling. This detects invalid insurance and prevents denied payments. 
• Segment FPRR by payer, service line, and denial reason code weekly to track and analyze the process.
• Build prior authorization verification into the scheduling workflow to obtain approvals for applicable services.
• Track denial reason codes on every failed first-submission claim to identify underlying operational errors.

Optimize FPRR with MediBillMD’s Medical Billing Services

An 80-85% First Pass Resolution Rate may appear acceptable, but it indicates room for improvement. MediBillMD’s services guarantee a 97% FPRR in medical billing. Every claim that fails the first submission can increase administrative workload and delay reimbursement.

Choose our medical billing services, designed to ensure that claims are processed and paid on the first try. We catch errors before they become write-offs.

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