Category Archive Start-Ups

Predicting monthly collections of a Practice in Healthcare

Predicting Collections for a Physician Practice:

First Step :

Take Practice’s Charges per Month over the past year and multiply by your “Weighted Average Practice Yield” (WAPD).

WAPD: Allowable for a CPT / Charged per CPT, for ex: if the fee charged /transmitted per CPT is $100 and allowable is $50, yield is 50% ($50/$100) generally whatever times Medicare rate/ Medicare allowable 

Estimate of Yield for a Specific Payer

– Complication is because of Various Payer Contracts for a Practice and the yield varies by CPT (E&M Vs Proc), Procedures can have higher yield than E&M’s.

– To get a Close estimate of Yield for a Specific Payer

          * Take Top 20 CPT’s, calculate Yield for each code

          * Calculate weighted average for the overall yield upon frequency of each of CPT’s

– Repeat the above process for each payer or atleast 80% of payment volume.

– Get overall Yield for practice by creating a weighted average based on charge volume (not payment volume)

For Capturing Month–to-Month variations

          (This works as long as payer and procedure mix are stable)

– To Capture Month–to-Month variations, distribution of average monthly payments by date of service, do the below:

In other words, which month’s patient encounters generated this month’s collections? Once you know this you can apply your practice’s average weighted yield to the portion of each preceding month’s charges that will impact the current month’s collections. This is easiest to see with an example:

Let’s assume your weighted average practice yield is 30% and your collection distribution is:

15% of this month’s collections come from this month’s dates of service (month N);

40% of this month’s collections come from last month’s date of service (month N-1);

25% of this month’s collections come from dates of service from two months ago (month N-2);

10% of this month’s collections come from dates of service from three months ago (month N-3);

10% of this month’s collections come from dates of service of 4+ months ago (month N-4+).

With this information in hand (which a good billing system or billing provider should be able to provide) you are ready to build a predictive collections model. If you use excel then you can build the model so that on one row your enter the practice’s charges by month and then directly below you calculate the collections for the month. If we take the data from above, the calculation for each month would be (where n equals the current month):

Final Formula :

 ((month N charges x 0.3 x 0.15) + (month N-1 charges x 0.3 x 0.4) + (month N-2 charges x 0.3 x 0.25) + (month N-3 charges x 0.3 x 0.1))/0.9  = Month N expected collections.

Few Pointers to remember :

  • The faster your collections the more the current month’s collections are dependent on the current month’s charges.
  • To simplify the calculation, it is helpful to limit the calculation to the current month and the three previous months. This is what I did above and it is the reason that I divided the answer by 0.9. The current month and the preceding 3 months account for 90% of the current month’s collections. When I divide the answer by 0.9 (90%), I take this 90% answer and extrapolate it to 100%.
  • Once you have constructed an excel spreadsheet with the formula’s outlines above you can quite accurately predict your month-to-month collections and account for the impact of seasonal and vacation driven changes in your charge volume. In addition, with the collection prediction in place your can quickly spot billing issues before they have a chance to propagate.