Reporting and benchmarking are critical components in managing any pathology practice or clinical laboratory. Gone are the days of waiting to review a month-end reporting packet. Real-time feedback on operational and financial performance is becoming increasingly necessary as the healthcare industry demands more work for less reimbursement and laboratories are required to adapt leaner, more efficient processes.
While benchmarking is a somewhat rudimentary method for managing the financial performance of a pathology practice, the information that core indicators provide helps to identify whether the organization is performing on par with, better than, or not as well as similar pathology practices within the market. In addition, monitoring benchmarks can provide early indications of process or staff training issues that should be remediated.
Using a large pathology and clinical laboratory claims database, current claims data and trends were analyzed and key performance indicators (KPIs) developed to help pathology labs benchmark operational and financial performance and better understand the quality of current revenue cycle management (RCM) processes. Top KPIs identified for anatomic pathology include:
- net collections (%)
- bad debt (%)
- days in Accounts Receivable (AR) (#)
- denials (%).
Net collections rate
The net collections rate is calculated by dividing net charges (gross charges – contractual adjustments) by net collections (gross payments – refunds). The national rate average for net collections is 88 percent to 92 percent, based on payor mix and patient demographics. A below-average performance on net collections rate may indicate that claims aren’t being followed-up on in a timely manner. An above-average performance on net collections rate may mean RCM processes are being managed and collected exceptionally well, or it could also indicate that the billing department is taking what should be bad debt adjustments as contractual adjustments, which erroneously inflates net collections statistics.
Bad debt rate
The bad debt rate is calculated by dividing the total amount written off as bad debt by the total amount that was eligible to collect. In this explanation, the specific reference is to bad debt associated with patient and third-party transactions.
Bad debt rate can be challenging to benchmark due to differences in how labs and billing service providers choose to classify contractual adjustments and denials. For example, timely filing is considered a bad debt by some practices, but others consider it a contractual adjustment. The basic rule is that anything that isn’t a formal contractual adjustment (the difference between what is billed and the contracted reimbursement rate or total allowable for that service) should be written off as bad debt. However, there may be exceptions.
When bad debt write-offs are classified accurately, a bad debt benchmark of 10 percent to 12 percent is considered average or good for most pathology practices. While bad debt write-off benchmarks were lower in previous years, the increase in patient responsibility due to growing high deductible health plans has resulted in most pathology groups trending slightly higher bad debt percentages than historical averages.
In instances where bad debt performance is better than average (less than 10 percent), it’s likely that patient demographics (for example, propensity to pay) and follow-up policies are resulting in higher collections and, subsequently, fewer bad debt write-offs. That said, it could also indicate that non-contractual denials are being written off as contractual adjustments instead of bad debt. In addition to auditing write-off policies, it is also worth reviewing days in AR to ensure that there isn’t a large volume of claims older than 90 days sitting in receivables. There may be balances that have not yet been adjusted or accounted for as a potential bad debt accrual.
Below average performance (more than 12 percent) on bad debt may indicate claims are not followed-up on in a timely or appropriate fashion, and/or claims are being written off too quickly, resulting in missed opportunities to appeal denials, missed filing deadlines, or writing off patient balances without proper follow-up or engagement in order to increase likelihood of payment.
Days in Accounts Receivable
To calculate days in AR, compute average daily charges (for example, total charges for six months divided by the number of days in the last six months) and divide the total accounts receivable by the average daily charges.
Although days in AR seems to be a straightforward calculation, the benchmark can vary based on the type of work performed by the laboratory and the timing of adjustments. Overall, a benchmark of 35 to 50 days is fairly standard. If days in AR exceed 50 days, that warrants additional investigation.
Below-average performance on days in AR (less than 35 days) may be the result of a terrific payor mix that pays quickly. On the other hand, it may also mean that adjustments are being made or claims are being written off too quickly, resulting in missed opportunities to collect on cases that are payable. It is a good practice to review bad debt write-offs by category to determine if there are any unusual outliers (such as how quickly patients are rolled over to collections).
Above-average performance on days in AR (above 50 days) may be related to the type of work a laboratory performs. Groups that work with capitated plans and IPAs, bill out-of-network plans, or perform molecular testing that may require appeals will have above-average days in AR without there being an issue. A good way to analyze AR is to benchmark the top 10 payors (which likely make up close to 80 percent to 90 percent of revenue) and determine if there are any clear outliers. If the laboratory performs complex testing with a high likelihood of denials, also review days in AR by CPT code to see which tests have the longest turnaround (and success/failure rates) on payment.
Denial rate is calculated by dividing the total dollars billed for denied claims by the total dollars billed on all submitted claims for each processed remittance. The goal is to maintain a denial percentage of less than 10 percent.
Depending on the revenue cycle management system in use, and the granularity of data provided by the billing software or service provider on denial types and gross and net revenue, a pathology practice may or may not have insight into its denial percentage. Yet a practice’s denial rate is one of the most critical performance measures of AR, as it is an important indicator of how well RCM processes are working, and reflects payor-specific trends that can impact the practice and its patients.
Pathology labs can only improve what they measure. A sound technology infrastructure that supports optimized business processes and delivers the right financial and operational benchmarks and KPIs is essential to success.