FREQUENTLY ASKED QUESTIONS

mEDICAID dRUG pRICING hEAT mAP

1) When I hover over a state, what exactly do the two lines represent?

The orange line is the total reimbursement by state/program reported by the state to CMS each quarter, divided by the total number of units reported.  We have grouped all drugs using "NDC Description," which can be found in CMS' NADAC database.  We like using NDC Description because it's the most clear and easy to understand drug naming convention we have come across in any public database. 

The blue line is the National Average Drug Acquisition Cost for the same NDC Description.  We have lag corrected these prices to the best of our abilities/knowledge (see question #4 for more on this). 

2) What is "NADAC"? 

NADAC is National Average Drug Acquisition Cost.  It is what the average pharmacy is invoiced for a drug, based on a monthly survey of (primarily) independent and chain pharmacies. 

3) Does NADAC include pharmacy rebates?

Based on CMS' reported methodology, it is highly unlikely that NADAC includes the rebates that some wholesalers will remit to pharmacies based on volume discounts. While these rebates are not guaranteed and not used by every wholesaler in the marketplace, the timing of how those rebates are collected would make it extremely hard to track in conjunction with these data, even if that rebate data was publicly available (which it isn't). Thus, we simply could not account for after-the-fact rebates on generic drugs that pharmacies may be getting from their wholesalers.  So, we think it's safe to assume that NADAC represents the average pharmacy's invoice price, not the average pharmacy's net price. 

4) Why did you "lag-effect" NADAC?  How did you do it?

Our goal is for the comparison between the two lines to be as meaningful as possible.  For generic drugs, based on CMS' survey methodology, we had to lag correct the prices reported each week to bring them back to the right "pricing month" before we merged them together with the state utilization data.  Brand drug prices are collected by CMS differently, so they do not have to be lag-corrected.

To lag-correct NADAC, we created a lookup table with every date when NADAC was updated ("As of Date") and assigned it a "pricing month."  NADAC is released every Wednesday to the public.  Based on our studies, if this Wednesday falls on or after the 17th of any month, it reflects the prior month's survey prices.  If it's before the 17th, it likely reflects pricing from two calendar months prior.  We used this logic to assign the pricing month to the weekly NADAC generic prices, before joining it with the state utilization data.   

4) Does the state utilization data include Medicaid program rebates? 

No, manufacturer rebates are not included in the state utilization data.  Having said that, rebates on generic drugs (which are classified as "non-innovator" drugs) are relatively small.  Statutory rebates are 13% of Average Manufacturer Price (AMP).  Rebates on brand name drugs could be much larger.  Please refer to Medicaid's website for more reading on the rebate program.

It's worth noting that AMP is published in CMS's Federal Upper Limit (FUL) database.  So, theoretically, we should be able rebate adjust the orange line.  However, as we have poked around in the FUL data, there was enough missing data to give us pause before doing this.  We felt it was safer to leave the orange line unadjusted until we had more time to assess the quality of the FUL database. 

While the lack of rebate data leaves net costs to the state incomplete, we can still use gross prices to compare states to one another (given that statutory rebates are fixed for each drug by the federal government), evaluate pricing trends that are egregiously different from NADAC, and compare managed care reimbursements to fee for service for the same drug (given that they will experience the same statutory rebates).   

5) Is the difference between the orange and blue lines the "spread" the PBM takes?    

No.  The difference is NOT what the industry refers to as "spread."  Spread is the difference between what the PBM charges a payer for a claim and what it pays the pharmacy for the same claim.  Data on what pharmacies receive for claims is not public. The only public (and free) pricing benchmark is NADAC, so that is what we are using for our comparison.

We call the difference between the two lines "markup."  It is the difference between what the state pays, and the invoice cost to the pharmacy.  In other words, the markup is shared in some form by the PBM and the pharmacy.  In the case of a full pass-through / cost-plus model (like most Fee for Service models) the markup is effectively the dispensing fee.  In a non-transparent "spread pricing" model, part of the markup goes to the PBM (the spread), and part goes to the pharmacy. Sometimes the pharmacy could get paid below the NADAC, meaning all of the mark-up is captured by the PBM and the pharmacy margin could be in the negative. While we are well aware of those instances, that data would not be reflected in these charts. The PBM decides how much goes to each party, but ultimately there is no tracking of how they slice the pie.

There is no other way that we know to calculate "spread" than by lining up state payments (i.e. "Encounter" data) with actual pharmacy reimbursements.  Feel free to contact us for more guidance on how to do this comparison.     

6) If this doesn't measure spread, what conclusions can I draw from it?

We published this data because we found two things very interesting:

1. Many of the expensive, new generic drugs didn't seem to be deflating as fast as they should when we looked at NADAC.  While we can't draw conclusions on if a snapshot markup is good or bad, the fact that it changed so much over time for the same drug was, in our view, very interesting (and worth sharing).
2. There is such a wide disparity between what different states are paying for the same drugs at the same time!  Based our experience, we were skeptical on whether states were communicating with each other to share best practices on program design.  We hoped that a visualization like this would lead to more interstate dialogue.