Unpaid Claims Analysis

An Effective Tool For Identifying Missed Revenue Opportunities

by Andre Kemeny and Daniel Bergantz

In an era of continuous reform and growing consumerism in healthcare, it is becoming increasingly important for providers to find ways to increase efficiencies and cut costs while concurrently identifying opportunities to increase revenue.  Providers often consider adding new services to drive volume, overlooking the revenue cycle as a potential contributor to increasing revenue.

Since 2000, there has been $538 billion worth of care provided for which no payment has been received.[1] A significant portion of these unpaid claims results from not receiving payment from the insurer.  Providers must continuously focus on ensuring all claims are charged, coded, and properly prepared for billing so that denials, delays, and improper payment are avoided as much as possible.  As a result, an unpaid claims analysis should be performed on a regular basis to measure any revenue loss that may be occurring due to sub-optimal claims management processes.

The Purpose of the Unpaid Claims Analysis

A key element in identifying opportunities for accelerating collections and improving revenue is to identify and quantify denied, underpaid, and otherwise unpaid accounts.  The purpose of this task is to analyze and quantify the impact of unpaid accounts by payer, patient type, reason, etc. in order to further identify opportunities that may exist within a particular area of the revenue cycle.

Ultimately, the results of an unpaid claims analysis effectively help identify the primary issues underlying why an account did not get paid.  An effective analysis can help organizations determine process issues, payer problems, and site of service issues to help staff redesign processes, improve technology integration and increase revenue moving forward.  The meaningful unpaid claims analysis includes the following activities:

  1. Preparing the data
  2. Calculating and analyzing the opportunity
  3. Identifying root causes
  4. Formulating conclusions and developing action plans

Preparing the Data

A robust analysis starts with 12 months of patient account level data (typically, the last fiscal year) and will include the following fields (among others):  patient ID, patient type, financial class, primary Insurance, secondary Insurance, tertiary Insurance (if available), charges, and payments fields.  In order to ensure that accounts have had sufficient time for full adjudication, data sets should be pulled with a 6 month lag (i.e., 6 months after the fiscal year end).

Next, accounts that ought to be excluded from the analysis should be identified and removed.  These accounts include categories for which reimbursement is not expected, such as charity care, and accounts that are reimbursed through alternative methods such as capitation plans or clinical trials.

Finally, accounts that have no third party payments associated with them should be flagged as “unpaid.”  All other accounts should have payment associated with them and should be flagged as “paid.”  Note: Since self-pay accounts will not have third party payments associated with them, they should be analyzed separately in order to develop and implement strategies to improve self-pay collections.

The Value of Calculating And Analyzing The Opportunity

The ability to estimate a monetary opportunity from the unpaid claims analysis is extremely valuable and helps organizations understand both the magnitude and the nature of the revenue opportunity.

The opportunity is obtained by calculating financial class or even payer-specific realization rates, and applying these realization rates to the gross charges of the unpaid accounts for the same categories (see Figure 1).

Figure 1. Sample realization rate calculation

Patient  Type
Financial Class
Insurance Payment
    Total Charges  
    Realization Rate      
Ancill. Champus $ (18,190)
$ 122,632 14.8%
  Comm $ (1,242,953) $ 5,275,713 23.6%
  Employee $ - $ 524 0.0%
  Guar $ (176) $ 8,219
2.1%
  HMO $ (5,192,091) $ 15,160,017 34.2%
  Mcare $ (2,254,354) $ 12,604,167 17.9%
  Medicaid $ (1,261,363) $ 6,662,822 18.9%
  Medicaid HMO
$ (8,124,070) $ 39,160,987 20.7%
  Medicare B $ (3,963,294) $ 25,753,479 15.4%
  Medicare HMO $ (1,404,935) $ 8,781,522 16%
  NJBC $ (8,297,005) $ 29,677,568 28%
  No Fault
$ (104,533) $ 381,712 27.4%
  PMcd $ - $ 27,218 0%
  Self Pay
$ - $ 3,001,649 0%
  Unvalued $ - $ 4,940 0%
  Workers Com $ (177,489) $ 385,589 49.5%

This, in effect, approximates the portion of total charges the organization would have realized on a claim, had the claim been paid at the same realization rate for claims that were paid.

Figure 2. Opportunity matrix, representing payment the organization would have received had the claim been paid

Patient Type Ancillary Clinic ER IP SDS Grand Total
Champus $2,986 $1,391 $12,046 $34,337 $110 $50,870
Comm $344,287 $356,311 $783,044 $3,761,292 $224,583 $5,469,517
HMO $490,199 $146,495 $597,775 $1,520,789 $258,500 $3,013,759
Mcare $82,184 $43,344 $82,613 $747,716 $131,837 $1,087,693
Medicaid $94,131 $13,836 $250,544 $2,500,277 $44,000 $2,902,788
Medicaid HMO $736,550 $157,036 $1,002,411 $3,850,289 $819,491 $6,565,777
Medicare B $55,857 $80,430 $10,183 $9,591 $344,218 $500,278
Medicare HMO $166,662 $60,660 $111,627 $450,404 $610,424 $1,399,776
NJBC $539,595 $107,188 $544,418 $2,905,690 $385,593 $4,482,484
No Fault $20,204 $6,779 $934,856 $1,806,390 $51,157 $2,819,387
Workers Com $38,645 $28,284 $243,266 $458,259 $82,090 $850,545
Grand Total $2,571,458 $1,001,754 $4,572,783 $18,050,075 $2,952,002 $29,148,071

As illustrated in Figure 2, the opportunity matrix illustrates the value of unpaid claims categorized by patient type and financial class.  Totals are calculated for each patient type and each financial class category as a means to help identify potential areas of improvement at the macro level.

Identifying the Root Cause

Although the opportunity calculation helps to understand what the quantified opportunity might be across the organization, it does not provide the reasons that claims were not paid.  To identify the root causes of unpaid claims, it is necessary to investigate accounts and to research why payment was never received.

Since it is not practical to sample the entire dataset (potentially many thousands of accounts, depending on the size of the organization), a statistically significant sample size should be determined and can be investigated to appropriately represent the entire dataset.

Investigation of these accounts reveals the root causes for why claims were not paid.  Common reason categories include:

  1. Patient Access:  Registration-Data Quality, Eligibility - Insurance not Eligible, Coordination of Benefits, No Authorization/Precertification/Referral
  2. In House:  Medical Necessity, Coding-Data Quality
  3. Patient Financial Services (PFS):  Additional Information Requested from Insurance, Bill-Data Quality , Duplicate Claim, Exhausted Benefits, Experimental or Investigational, Lack of Timely Follow-up, Non-covered Service (for service changes after registration), Payer Contract Violation (e.g., readmission, 72 hr rule, etc.),  and Untimely Filing

Formulating Conclusions and Action Plans

With this valuable information in hand, leaders can subsequently make informed decisions regarding the improvements that could reduce future unpaid, underpaid, and delayed-payment claims volume.  The analysis results (sample summary of results shown in Figure 3) should be shared with appropriate departments and teams who are then tasked with developing action plans for improvement and held accountable to take action and drive results.

By sharing the results, teams and department staff will be empowered to make informed decisions based on real information.  Through the involvement of these same groups in the development and carrying out of action plans, accountability for improvement and results will be enhanced.

Figure 3. Summary of unpaid claims analysis illustrating root causes of unpaid claims and associated opportunity

Summary of Opportunities Low Mid High People Process Technology
Patient Access $3.7M $4.9M $6.1M   X
X
In House $2.6M $3.5M $4.4M   X X
Patient Financial Services
$11.2M $14.9M $18.6M X X X
Financial Impact
$17.5M $23.3 $29.1M      
Note: Results vary by organization and PNC cannot guarantee a particular level of results for your organization

Conclusion

An unpaid claims analysis is by no means a panacea that will uncover and resolve every revenue related challenge, but truly it is a tool of great worth that is generally underutilized.  By conducting an unpaid claims analysis, healthcare leaders can discover and measure the true nature of hidden challenges negatively affecting revenue.  By utilizing the valuable information that is developed through this exercise, leaders can reinforce accountability in their teams and instill a disciplined approach to performance improvement.

PNC Healthcare Advisory Services

PNC’s Healthcare Advisory Services team has extensive experience working with health systems and other healthcare providers throughout the nation to improve organizational effectiveness and financial performance.  Areas of consulting focus include: revenue cycle operations and strategy, project management, system implementation support, strategic planning, labor management, Lean/Six sigma process improvement, and strategic pricing.  The team frequently conducts unpaid claims analysis work as part of project assessments in order to determine the nature and magnitude of the revenue cycle-related opportunities facing the healthcare provider.  Although the nature and magnitude of the opportunities for every organization are different, the approach of the unpaid claims analysis is proven and effective.

Andre Kemeny
Vice President
PNC Healthcare Advisory Services

andre.kemeny@pnc.com
Read Full Bio »

Dan Bergantz
Vice President
PNC Healthcare Advisory Services

daniel.bergantz@pnc.com
Read Full Bio »


Receive the Healthcare Matters Newsletter

Subscribe Now »