Updated on: June 22, 2012

The Data Manager: Unbilled Charges—An Effective Measure of Coder Productivity

By
Original story posted on: July 29, 2010

By: Carol Spencer, RHIA, CCS, CHDA and Jill Sell-Kruse, RHIA, CCS

 

 

carolSpencerED. NOTE: This is the third in a three-part series designed to compare and contrast the “coding-state” manager’s roles andjkruse100responsibilities of today with the “data-state” manager’s roles and responsibilities of tomorrow. The first article discussed integration of controls and safeguards. The second article presented information on quality measures for improper payment. This article proposes measuring productivity in relationship to unbilled charges. The formula for each measurement is defined and the benefits of measuring productivity by unbilled charges are explained. All efforts related to the data manager are geared toward reducing financial risk and increasing data integrity.


Primary Measurements
In evaluating coder productivity in the “coding state,” the primary measurement is the chart— the number coded per day, per week or per pay period. Charts per day are converted to the number of hours coded and divided by productive hours for a productivity percentage. The goal is 95 percent productivity.

 

In evaluating coder productivity in the “data-state,” the primary measurement is unbilled dollars—how many pending dollars on the unbilled report per day, per week or per pay period. Unbilled dollars coded per day are converted to hours coded and divided by productive hours for a productivity percentage. The goal is 95 percent productivity.

 

Coder Productivity Formula Measured by Charts Coded

 

There are variations to the formula used to determine coder productivity. The general one presented here uses two key components: charts and productive hours. Usually, a time period is defined as either a week or two weeks in order to allow enough charts to be coded and reduce variation that could occur on a daily basis. This example will demonstrate coder productivity for one week (40 hours).

 

Non-productive hours are subtracted daily based on 13 percent for personal, fatigue, and delay (PFD) time, which leaves seven hours of productive time daily. Personal time includes two 15-minute breaks. Thirty minutes for worker fatigue include personal downtime as well as computer delays, downtime, or other process delays. Productive hours for one week total 35, additional non-productive hours are subtracted. The denominator is always 35 hours to calculate weekly productivity unless meeting time, continuing education units (CEU) time, or additional allotted time for high-dollar charts is subtracted from 35 hours for the adjusted productive hours. To calculate the numerator, take the following steps.

 

Define your hospital’s minimum “meets requirements” coding standard. If the minimum is 22 records per day, then calculate the minimum standard “earned coder credit” or number of charts per hour. Divide 22 records by 7 (for a seven-hour productive day), which equals 3.14 earned coder credits or 3.14 charts per hour. (If a hospital’s minimum standard is 25 records per day, then divide by 7 (for a seven-hour productive day), which equals 3.57 earned coder credits.

 

Take the total number of charts coded for the week and divide by 3.14 (standard earned coding credit) and the answer is the numerator.

 

For example, let’s evaluate the productivity for Coder A and Coder B. Both coders had no additional non-productive hours, so each denominator is 35 hours. For the numerator, Coder A coded 100 charts for the week. Divide 100 by 3.14 to determine Coder A’s earned coder credit of 31.8 and divide it by 35 productive hours, which equals 90.9 percent productivity.

 

Coder B coded 112 charts for the week. Divide 112 by 3.14 to determine Coder B’s earned coder credit of 35.7 and divide it by 35 productive hours, which equals 102 percent productivity. Again, this is based on a minimum standard; therefore, nothing less than 100 percent is acceptable.


Coder Productivity Formula Measured by Unbilled Charges

 

Let’s take this same theory and transfer the formula to unbilled dollars. The first task for the coding manager is to find out (from the hospital’s finance department) the average charges for an inpatient discharge.

 

Let’s use $29,000 as the average charges for an inpatient discharge. The formula presented here to calculate coder productivity is based on unbilled charges (rather than charts) and productive hours. Again, the time period may be a week or two weeks to allow enough unbilled charges and avoid variation that could occur if productivity monitoring occurred on a daily basis.

 

This example will demonstrate coder productivity for one week (40 hours). Non-productive hours are subtracted daily based on a 13 percent deduction for personal, fatigue, and delay (PFD) time, which leaves seven hours of productive time daily. Personal time includes two 15-minute breaks. Thirty minutes for fatigue time includes personal downtime as well as computer delays, downtime, or other process delays. Productive hours for one week total 35, additional non-productive hours are subtracted for meeting time or CEU time. There is no need to subtract non-productive time for high-dollar charts since the unbilled charges are a key component of the productivity formula.

 



 

Using this formula encourages the coder to code high-dollar charts whereas in the productivity formula by chart discourages the coder to code high-dollar charts. The denominator is always 35 hours to calculate weekly productivity unless meeting time or CEU time is subtracted for the adjusted productivity hours.

 

To calculate the numerator, use the following formula. Define your hospital’s minimum “meets requirements” coding standard. If your minimum is 22 records per day then multiply that by $29,000 (average inpatient unbilled charges), then calculate the minimum unbilled standard “earned coder unbilled credit” or unbilled charges per hour.

 

The formula is $638,000 unbilled charges divided by a seven-hour productive day, which equals 91,143 earned coder unbilled credit or 91,143 unbilled charges per hour. Take the total number of unbilled charges coded (dropped) for the week and then divide it by 91,143 (standard earned unbilled coding credit), and the answer is the numerator.

 

For example, let’s evaluate the coder productivity for Coder A and Coder B. Both coders had no additional non-productive hours, so each coder’s denominator is 35 hours. For the numerator, Coder A coded $2,900,000 of unbilled charges for the week. Divide $2,900,000 by $91,143 earned coder unbilled credit, which equals 31.8; now divide that by 35 productive hours, which equals 90.9 percent productivity.

 

Coder B coded $3,248,000 of unbilled charges for the week. Divide $3,248,000 by $91,143 earned coder unbilled credit, which equals 35.6 divided by 35 productive hours, which equals 102 percent productivity. Again, this standard is based on a minimum standard; therefore, nothing less than 100 percent is acceptable.

 

Benefits of Measuring Productivity

 

The benefits of measuring productivity by unbilled charges include the following:

 

  • Better position to negotiate costs for contract coding services. For example, the expectation is that a contract coder would exceed the average level of productivity and that he or she would drop $3,625,000 by the end of the week. This is more meaningful to the chief financial officer (CFO) and the contract coding vendor in the negotiation than saying contract coders need to drop 125 charts by the end of the week. In addition, the coding manager can more effectively manage the unbilled.
  • Coders begin to see a direct correlation between their coding productivity and the unbilled dollars. The number of unbilled dollars is a number that coders are measured against daily, so now they can understand how their contribution of “dropping” bills impacts the overall unbilled. For a coder to say they dropped $4,000,000 in charges this week is much more meaningful than saying they dropped 125 charts this week.
  • Coding managers can effectively manage accounts on the unbilled (for example: $950,000 holding in queries, $300,000 in admission orders, $400,000 holding in discharge disposition, $2,000,000 holding in missing dictation).
  • Coding managers are better able to determine the number of staff needed when they have a coder call off sick for one day, which will back up the unbilled by $638,000. A coder calling off sick for three days becomes $2 million. By seeing these numbers, a CFO may be more likely to allow additional staffing to prevent unbilled creep.
  • Health information management (HIM) directors can talk dollars and “sense” to their CFOs during discussions surrounding coder productivity; staffing; unbilled management; and building key relationships with the medical staff, case management, clinical documentation improvement (CDI) and all departments directly related to the timely, accurate, consistent, and complete documentation of the medical record and their impact on revenue and data integrity.

 

As always, productivity is balanced with quality; therefore, at no time is quality sacrificed for the sake of productivity.

 

Take the “data manager” challenge today!

 



 

This concludes the third part series that compared and contrasted the “coding-state” manager’s roles and responsibilities of today with the “data-state” manager’s roles and responsibilities of tomorrow. To receive all three articles go to:

 

http://racmonitor.com/news/33-top-stories/393-the-data-manager-controls-and-safeguards-for-revenue-and-data-integrity-part-1.html

 

http://racmonitor.com/news/33-top-stories/394-the-data-manager-reporting-coding-quality-measures-for-improper-payment-part-2-.html?start=1

 

http://racmonitor.com/news/33-top-stories/395-the-data-manager-unbilled-chargesan-effective-measure-of-coder-productivity-.html

 

About the Authors

 

Carol Spencer, RHIA, CCS, CHDA is a senior healthcare consultant with Medical Learning, Inc. (MedLearn®) in St. Paul, Minn. MedLearn is a nationally recognized expert in healthcare compliance and reimbursement. Founded in 1991, MedLearn delivers actionable answers that equip healthcare organizations with coding, chargemaster, reimbursement management and RAC solutions.

 

Jill Sell-Kruse, RHIA, CCS, is currently the coding manager at Memorial Health System in Colorado Springs, Colorado. She has over 30 years of experience in Health Information Management, 20 of which involved coding, coding education, coding compliance, and coding management.  Jill received her Bachelor's in Health Records Administration from the University of Pittsburgh.


Contact the Authors

 

cspencer@medlearn.com

 

sell-kruse@memorialhealthsystem.com

 

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