In summary, comprehensive and charge-invariant billing metrics, such as PARBX, are more informative and objective than col

Useful metrics must be comprehensive and simple. They must combine both complete end-to-end processes and their individual components. Metrics must be used consistently over time and compared to standards.

1. Days in Accounts Receivable (DAR)

   A growing number of days in accounts receivable are symptomatic of a faulty billing process. One way to determine DAR is to count days from the date of service to the date of payment for every claim and then average across all claims. A simpler way to compute average number of days in accounts receivable by taking a ratio of accounts receivable to average daily charges, or

   DAR = (Accounts Receivable / Average Charge) x 365

   The main downside is this metric is its sensitivity to provider as it counts the lag time of unsubmitted claims for services already delivered.

   One obvious advantage of DAR metric is its independence of charges. The averaging feature of this metric eliminates sensitivity to specific day or CPT code but also hides the behavior shape of the accounts receivable curve.

   Note that national average of DAR hovers around 73 days. Advanced billing service providers leveraging powerful Vericle technologies often drive average DAR as low as 15 days.

2. Percent of Accounts Receivable Beyond 60, 90, and 120 Days (PARB60, PARB90, and PARB120)

   PARBX resolves the sensitivity issue of DAR metric and offers simple and charge-invariant metric of billing process. Its graphic representation has a skewed bell shape. Its steepness represents billing process quality: a steep curve and thin tail means healthy billing process, while a flat bell and a fat tail means billing problems.

   According to the MGMA survey, 25.35 percent of the average family practice's accounts receivables were more than 120 days old in 1997. This number has improved down to 17.7% in 2004.

   PARBX metric is especially helpful to identify patterns of problem claims containing specific payer or CPT code. Advanced billing service providers leveraging powerful Vericle technologies often drive average PARB120 as low as 5%, significantly below the national average of 17.7%.

   Further, PARB120 has been used to develop rule-based Billing Performance Index, which helps the development of billing industry standards. Chiropractors can use the index to benchmark their billing performance and to guide its improvement over time. Rule-based index definition allows for automated inclusion and exclusion of payers in the index based on payer attributes, such as numbers of processed claims, accounts receivable distribution, certain mix of CPT codes, or patient demographics.

3. First-Pass Pay (FPP Rate) and Denial Rate

   FPP is the percentage of claims paid in full the first time upon submission (subject to federal or state timely payment regulations: 15 days for electronic submission and 30 days - for paper).

   Denial rate is the complementary metric to FPP rate. It counts the percent of claims that require followup and therefore cost more to process. Followup may take the form of a phone call to payer to discover a lost claim or to receive interpretation of denial message, correction of earlier submitted data, resubmission of the original claim, consultation with the provider and medical notes, or denial appeal.

   Both FPP and Denial rates are very important metrics often used for billing process improvement. The upside of FPP/Denial metric is that it is charge-invariant but its downside is that it hides the differences between process imperfections on the claim submission and claim payment sides. To identify patterns of problem CPT codes or payers, FPP/Denial metric needs to be computed and compared across all pairs of payer-CPT code, which is a standard feature for modern billing technologies.

4. Patient Liability Rate

   Percent of Patient Liability is the ratio of patient responsibility to total billed charges and it roughly reflects patient deductibles. This measure is important in measuring front office function as it has little to do with clean claim submission or effective followup.

5. Collection Ratios

   Gross and net collection ratios metrics used to be popular metrics in the early day of digital computing. They compare (often arbitrary) charges to (allowed) payments. Net collection rate is defined as a ratio of Total Collections and Total Charges less Adjustments. Gross collection rate is defined as a ratio of Total Collections to Total Charges only. The main drawback of Collection Ratios metrics is the use of charges in defining gross and net collections, which precludes productive discovery of process improvement opportunities.

In summary, comprehensive and charge-invariant billing metrics, such as PARBX, are more informative and objective than coll

DAR = (Accounts Receivable / Average Charge) x 365

The main downside is this metric is its sensitivity to provider as it counts the lag time of unsubmitted claims for services already delivered.

One obvious advantage of DAR metric is its independence of charges. The averaging feature of this metric eliminates sensitivity to specific day or CPT code but also hides the behavior shape of the accounts receivable curve.

Note that national average of DAR hovers around 73 days. Advanced billing service providers leveraging powerful Vericle technologies often drive average DAR as low as 15 days.

In summary, comprehensive and charge-invariant billing metrics, such as PARBX, are more informative and objective than col

According to the MGMA survey, 25.35 percent of the average family practice's accounts receivables were more than 120 days old in 1997. This number has improved down to 17.7% in 2004.

PARBX metric is especially helpful to identify patterns of problem claims containing specific payer or CPT code. Advanced billing service providers leveraging powerful Vericle technologies often drive average PARB120 as low as 5%, significantly below the national average of 17.7%.

Further, PARB120 has been used to develop rule-based Billing Performance Index, which helps the development of billing industry standards. Chiropractors can use the index to benchmark their billing performance and to guide its improvement over time. Rule-based index definition allows for automated inclusion and exclusion of payers in the index based on payer attributes, such as numbers of processed claims, accounts receivable distribution, certain mix of CPT codes, or patient demographics.

In summary, comprehensive and charge-invariant billing metrics, such as PARBX, are more informative and objective than col

FPP is the percentage of claims paid in full the first time upon submission (subject to federal or state timely payment regulations: 15 days for electronic submission and 30 days - for paper).

Denial rate is the complementary metric to FPP rate. It counts the percent of claims that require followup and therefore cost more to process. Followup may take the form of a phone call to payer to discover a lost claim or to receive interpretation of denial message, correction of earlier submitted data, resubmission of the original claim, consultation with the provider and medical notes, or denial appeal.

Both FPP and Denial rates are very important metrics often used for billing process improvement. The upside of FPP/Denial metric is that it is charge-invariant but its downside is that it hides the differences between process imperfections on the claim submission and claim payment sides. To identify patterns of problem CPT codes or payers, FPP/Denial metric needs to be computed and compared across all pairs of payer-CPT code, which is a standard feature for modern billing technologies.

In summary, comprehensive and charge-invariant billing metrics, such as PARBX, are more informative and objective than col

In summary, comprehensive and charge-invariant billing metrics, such as PARBX, are more informative and objective than collection ratios. Modern Vericle-like technology using such metrics helps identifying billing bottlenecks as it allows interactive review of multiple metrics along different aggregation dimensions.