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A Little Imms Admin Analysis Tool

Warning: I am introducing a quick-and-dirty little imms analysis tool.  Emphasis on dirty.  This might lead to more questions than answers.  Be forewarned.

As you can imagine, I do a lot of pediatric productivity analysis and find an endless number of angles at which to slice and dice the data.  Every new practice I work with teaches me something.

For example, I've always quickly eyeballed each practice's vaccine volume and administrative coding.  I finally sat down and spent 15min making a spreadsheet that will tell me if there's a "leak" somewhere.  Are there vaccines being given, but coded incorrectly?  Are there vaccines being given and not being coded at all?  Thanks to VFC and the 90471/2/3 set, this spreadsheet can't do a perfect job telling us everything we need to know, but it's a start.  It has helped me catch practices who aren't billing all of the possible component based admins.

This tool is somewhat like the RVU calculator.  You need to gather some data, drop it into the spreadsheet, and then it tells you something.  The data you need to gather is very simple: a list of your immunization-based CPT codes and their unit volume.  You can include all your CPTs in the data, the spreadsheet will do the work for you. 

Here are the step-by-steps:

  1.  Run a report in your PM to generate a list of CPT codes and units for any given time frame.  It might look like this:
    CPT-5 Units
    90460 6381
    90461 3403
    90471 2443
    90472 100
    90651 564
    90670 736
    90680 503
    90685 630
    90686 2543
    Note that you'll want to strip off any modifiers.  If there are non-imms codes in there, no big deal.
  2. Take this data and drop it into the spreadsheet in the tab named "Imms."
  3. Hop over to the Analysis tab and check it out.

What do the results tell us?  Columns G+H provide the analysis.

  • H2 is your total imms admins you recorded.
  • H3 is the total count of imms you've recorded.
  • H4 is where it gets interesting.  In theory, if you add up all of your 90460s and 90471/2/3s, the result should match your total number of vaccines given.  In other words, H4 should match H3. 
  • If H3 and H4 differ, you'll see the results in column I. 
  • In C2 and C3, you get the ratio of certain imms admin codes to each other.  This is a placeholder for some interesting future conversations.
  • It also calculates your oral/intranasal admins and vaccines (G7/8).

Here's an example of what it might look like:

imms_tool-3

Why would the numbers differ?  I've seen a number of reasons.

If the imms are greater than the expected admins:
  • You charged for vaccines for which you didn't record admins (oh no!).  This is the big thing I'm looking for.
  • You have a funky VFC coding requirement that doesn't use imms admins (which means you can go count VFC vaccines and confirm the difference).
If the expected admins are greater than the imms:
  • You didn't charge for vaccines that you gave.  This is the other big thing I'm looking for. 
  • You have a funky VFC coding requirement that doesn't use vaccine codes normally (which means you can go count VFC vaccines and confirm the difference).

It's not possible for the spreadsheet to make sure you have your 90460/90461 distribution correct, but you can make a quick estimate to see if you're far off.  It's not going to spot the one time you missed a 90461 on a Pentacel but if you are always missing one on your MMR, it might.  Let's see if I can describe this...First, most of the time, 90471s are used for flu shots.  Not always, of course, but if you quickly add your 90471 totals to your 90460 totals and pretend for a minute, you can compare the results in G9 and H9 to see if you're in the ballpark.  It's far from accurate or perfect, but I've used this trick to find some leaks - when this quick check doesn't work, I start digging and lo and behold!  The practice hasn't been billing TdaPs right or something.

Play with this.  See what you get.  Tell me where it's broken or how I can improve it.

The Quick And Dirty Imms Admin Anaylsis Tool, 2019.

 

Tags: immunization administration, immunizations

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