How low can you go? Newly launched dashboard explores 340B’s deeply discounted drug prices

 

Come here, my little friend. Don't be afraid.

One of the challenges with drug affordability in the U.S. is that we cannot agree on what a drug’s price actually should be. The relatively simple question of “what should a drug cost?” is surprisingly nuanced in the United States due to a variety of drug reference prices (or pricing benchmarks), which our system relies upon to pay for drugs. Whether we recognize it or not, we experience this every time we go to the pharmacy.

What do we mean? We can almost assure you that the price you pay for a medication at a pharmacy is different from the price someone else will pay that same day, for the same medication, even though you both got the same drug, at the same pharmacy, on the same day. Which is pretty nuts when you consider that this is a stark contrast to other purchases we make as consumers. Can you imagine if you went to check out and your gallon of milk was 10x more expensive than the person in front of you? Even if it was blue milk, it’d still be a rip-off.

Source: Tulsa World

We have previously explored this drug pricing disparity phenomenon at 46brooklyn. In our first podcast series called Drug Pricing 101, we painstakingly reviewed no less than nine different drug pricing benchmarks (ASP, AMP, WAC, DP, AWP, AAC, NADAC, U&C, and MAC) to demonstrate that, perhaps, we have challenges affording drugs simply because we cannot agree, in a transparent way, as to what drugs should cost. Said differently, if you have nine different ways to quantify a drug’s price, you effectively have no real price at all.

Having said all that, Drug Pricing 101 was an introduction to U.S. drug pricing, and far from all-inclusive in addressing the litany of drug prices actually available in the U.S. We certainly covered the high points with AWP, NADAC, and MAC, but notably absent from the “poster children” of drug pricing distortions was 340B.

For those who are not full-bore drug pricing nerds, who have been along for the mildly entertaining 46brooklyn drug pricing research ride for any extended period of time, we understand at this juncture, you may be asking yourself, “ok, I’m interested in drug pricing and I do like all the Star Wars references, but I don’t think I can stomach another tiresome excursion into the sarlacc pit of another system nuance — especially one with both numbers and a letter in the name,” trust us when we say that we get it. So here’s another Star Wars reference to sweeten the deal:

With the long-anticipated release of the first episode of Obi-Wan Kenobi on Disney Plus this week, allow us the opportunity to use an old Jedi mind trick as a means of enticement to get you to plod your way through a necessary chapter in your hero’s journey. If you’ll recall from The Empire Strikes Back, Obi-Wan’s Force ghost beckoned a young Luke Skywalker to Dagobah to find Jedi Master Yoda in order to better learn the ways of the Force, much as we instruct you to continue your training here.

So, my young apprentice, you want put down your death sticks, rethink your life, and join us on a journey into the depths of the 340B program — the dark, sticky, off-world swamp of the U.S. drug pricing system.

Drug Pricing 102: An Introduction to the 340B Program

For the unfamiliar, the 340B program got its start with the Veterans Health Care Act of 1992 (i.e. 340B program). That law provides access to purchase drugs at reduced prices (i.e., 340B prices) for certain healthcare groups called Covered Entities. The law came about because Congress had two years earlier instituted the Medicaid Drug Rebate Program (MDRP). That program established obligations for drug manufacturers to provide rebates to Medicaid programs in exchange for Medicaid agreeing to pay for their drugs in the first place. MDRP rebates were, and still are, calculated via a formula which included a requirement that Medicaid get the “Best Price” for drugs that the manufacturer made generally available in the marketplace.

After the passage of MDRP, manufacturers pulled back from some of the discounts they offered existing healthcare groups, like hospitals, likely over concerns that their existing programs would run afoul of the newly enacted “best price” provision (if someone is getting the best, someone else, by default, has to get the worst). So Congress created the 340B program, which effectively gave the Covered Entities (the hospitals who were no longer getting the discounts they used to get) the same discount the government gave itself, via Medicaid. Make sense? If not, check out some of the 340B resources at HRSA, 340B Health, USC Schaeffer Center, or even a recent Weekly Checkup by the American Action Forum.

Within pharmacy, and U.S. drug pricing more generally, 340B is a big deal. According to analysis performed over at Drug Channels, the 340B program’s size (in terms of dollars) is at least equivalent, if not larger, than Medicaid’s own rebate program. According to Dr. Fein’s analysis, the 340B program reached $38 billion in 2020. According to Medicaid and CHIP Payment and Access Commission (MACPAC) data (Figure 1 - top line of Exhibit 28), the Medicaid program produced $39 billion in rebates in 2020. Those numbers look very equivalent to us, so we’re directionally inclined to agree with Dr. Fein’s assessment.

Figure 1
Source: MACSTATS, Exhibit 28

Now, before we make the mistake of judging the force of these programs by their size alone, perhaps more interesting than the near equal size is the fact that they’re more or less supposed to be mutually exclusive. According to the rules – and we have to believe everyone is following the law – manufacturers are protected from having to provide both a Medicaid rebate and a 340B price concession. This prohibition of duplicate discount makes sense in that the 340B price and the Medicaid rebate are essentially the same (minus supplemental Medicaid rebates or sub-ceiling 340B price concessions) and so manufacturers don’t have to give two separate parties the same price concession. In essence, we can interpret this to mean that (again, assuming the rules are being followed) the two programs combine for $77 billion in price concessions by the drug manufacturers with no overlap. This is out of an estimated $217 billion in 2020, or representative of 35% of all manufacturers’ gross-to-net reductions. Said differently, that’s no drug pricing moon. It’s a space station.

Ultimately, knowledge about 340B prices would provide several pieces of valuable information, not the least of which is greater price transparency regarding net prices for medications. If we had access to 340B prices, we’d have an idea of the net price of a drug in the Medicaid program, which would help us better evaluate formulary and coverage decisions within the Medicaid program. Can you imagine what a group like ICER could do in saying what a QALY for a drug is if they had greater insight into statutory rebates? Alternatively, if we had access to the 340B prices, we would also get a sense for the mark-up that Covered Entities earn off of the sale of 340B-acquired drugs at the existing average reimbursement rates. All topics we’ve previously expressed an interest in knowing about at 46brooklyn.

The problem, of course, is that 340B prices are expected to be secret, just like MDRP unit rebate amounts (URA).

Regardless of the supposed pitfalls or benefits of the 340B program (we have seen ample examples of both), given our general aversion to all forms of drug pricing arbitrage, the general opacity and complexity of the program has always been a source of discomfort for us.

So imagine our surprise when stumbling through Texas Medicaid data from their Vendor Drug Program, we discovered a file with the holy grail: reported 340B pricing in the public domain (Figure 2).

In our experience, there's no such thing as luck.

Digging a little deeper, we learned that the Centers for Medicare and Medicaid Services (CMS) approved a state plan amendment (SPA) for Texas Medicaid in June 2016, which allowed Texas to alter the way it paid for drugs, including that Texas Medicaid will reimburse “a 340B covered entity for a 340B covered outpatient drug purchased through the 340B program and dispensed to a patient of a 340B covered entity based on HHSC's estimate of the CMS 340B ceiling price“ (Figure 3).

Now, before we get too far ahead of ourselves let’s see what an estimate of 340B ceiling prices actually means. According to our deep dive, we strongly believe the methodology Texas is relying upon to get its 340B ceiling prices isn’t running afoul of disclosing proprietary, confidential, Death Star-style plans. Rather, they appear to be getting around this by publishing 340B prices as a discount to WAC. These can vary by drug class, including the state manually adjusting prices to meet its needs. However, CMS ultimately approved Texas’ SPA, meaning CMS agreed, for all practical purposes, that Texas’ methodology for calculating 340B ceiling prices was functionally equivalent to the 340B ceiling price — or at least, was good enough for government work. So, we’re going to take them at their word (more on that later) and believe that Texas’ published 340B price is representative of the drug’s acquisition price to Covered Entities. Alternatively, the difference between what Medicaid paid for the drug and the Texas Medicaid price is reflective of the net price Medicaid paid for the drug.

And if you’re still wondering what exactly Texas has posted, let’s allow their website to do the talking, where their Formulary Drug File Layout explicitly states that their “Drug_340B” field “Identifies the current 340B price of the drug.” Seems pretty plain to us scruffy looking nerf herders.

It was at this point that we freaked out a little. Upon downloading the files, we felt a great disturbance in the Force, as if millions of voices of those who desperately want drug pricing secrets to remain hidden suddenly cried out in terror and were suddenly silenced.

By Darth Vader’s breathing apparatus, WE HAVE 340B PRICING INFORMATION…

At least, to the degree that it is good enough for government work.

So what did we do? This is 46brooklyn folks — we must do what we think is right, of course: give it away! So we immediately began building a new visualization: the 46brooklyn 340B Drug Pricing Dashboard. (Figure 4)

Understanding the new 46brooklyn 340B Drug Pricing Dashboard

We took the information that Texas supplied regarding 340B prices and made a tool such that anyone could compare either the net price of a drug in Medicaid in 2021 (the difference between what Medicaid paid for the prescription and the 340B price of that same prescription according to Texas) OR the estimated mark-up to the 340B price that Covered Entities are taking (by comparing the difference between the actual acquisition price of the drug within retail pharmacies according to Texas and the 340B price, again according to Texas). We modeled the 340B Drug Pricing Dashboard off our old Medicaid Heat Maps, using CMS state drug utilization data (SDUD) to identify the average number of units (i.e., pills, milliliters, or grams) of the medication dispensed and giving state-specific insights into the prices. By either metric, this visualization provides arguably the greatest transparency into granular net drug prices in the U.S. that anyone has ever been able to offer publicly.

To demonstrate, we compared the aggregate rebates in Medicaid in 2020 to the MACPAC figure regarding rebate amounts per state. If 340B ceiling prices and Medicaid net price are nearly the same, we would expect that the results would be fairly equal (recognizing that some variability will result from Medicaid supplemental rebates and 340B providers dispensing Medicaid claims [which Medicaid can’t get a rebate on]). In Figure 5, we compare the amount of rebates we think Medicaid got as a portion of Medicaid drug spend in 2020 based upon the Texas Medicaid 340B value weighted across all the units dispensed to the percentage derived from MACPAC Exhibit 28. Ultimately, we found that the results were pretty close in most state-to-state comparisons (Figure 5) and in the aggregate.

Figure 5
Source: 46brooklyn Research

Overall, Exhibit 28 on MACPAC tells us that state Medicaid programs recognized a 54% rebate off their gross spending ($39.2 billion in rebates off of $71.8 billion in gross spending). The Texas 340B data, weighted based upon the expenditures available within SDUD for 2020 (which should exclude 340B), would estimate that the total Medicaid program got a 45% rebate in 2020. A difference of just 9% — which considering that we don’t know supplemental rebates, and cannot factor in the lag states have in recognizing rebates — we feel pretty confident we’re getting it mostly right.

But as a wise man once said, “Your eyes can deceive you; don't trust them.” While we wanted to believe it was good enough for government work, we couldn’t stop ourselves from checking. That was partly why we made the state-to-state comparisons as way of further checking the accuracy. Consider the range of accuracy values state-to-state in Figure 5. A range of -14% to 51% doesn’t seem great, we’ll admit. But when we go state-by-state, our 340B estimates for net Medicaid costs are within plus or minus 5% for 39% of all Medicaid lives. That increases to 79% of all Medicaid lives at a 15% error range, and basically covers everyone at a 25% error range (Figure 6). So outside of really a single state or two, we’re fairly close by the standards of government work.

Figure 6
Source: 46brooklyn Research

We realize that you may note that a few states had some weird stuff going on in 2020 in regards to MACPAC rebates, but that’s your uncle talking; we don’t think a few small states should distract us from the bigger picture of what we have here. While we’ll likely never get the answer 100% right, we feel the math speaks for itself in that we’re potentially closer than we’ve ever been to solid numbers that reflect 340B discounted prices.

As way of final comparison, we made a few individual drug analyses. We started with insulin, mostly because of the number of insulin price investigations — particularly by Congress — have provided a great deal of insight into drug prices net of rebates. For example, we know through the Grassley-Wyden Insulin Report that in 2019, the drug manufacturer for Lantus offered OptumRx rebates up to 79.75% for preferred formulary placement of their product. We previously used this information to estimate the net price of insulin around $70 per prescription. Our 340B Drug Pricing Dashboard is estimating a net price in Medicaid of approximately $200 to $250. The differences between these two net prices for insulin can explain some of the error we’re observing in the aggregate numbers above.

But even with the limitation of maybe not getting some drugs exactly right, we can still see the value of what our tool can help us understand. One of the growing trends in pharmacy benefit design has been to prefer expensive brand name medications over their cheaper generic alternatives. On its surface, this phenomenon can be difficult to understand when comparing traditional pharmacy pricing benchmarks like AWP, WAC, or NADAC where brands universally seem more expensive. However, thanks to our tool, we can start to understand why plans may prefer certain brand name medications over their generic counterparts due to rebates.

Take Truvada, another medication we’ve previously written about on 46brooklyn, and compare its estimated net price in Medicaid for the brand and generic versions (Figure 4 previously).

In comparing their prices you can see it’s possible for the brand (estimated net cost $576 in Managed Care) to be cheaper than the generic (estimated net cost $624 in Managed Care) in Medicaid given the MDRP / 340B pricing paradigm. For the nearly 100,000 prescriptions dispensed in Managed Medicaid in 2021, this difference amounts to nearly $5 million in cost showing just how important getting the cost correct can be.

You have taken your first step into a larger world.

To say we’re a bit overwhelmed by what we stumbled upon is a bit of an understatement. To borrow from Emperor Palpatine, this data set is a pathway to many drug pricing analyses some may consider to be unnatural. Want an idea of the amount of money drug manufacturers are offering the system (via rebates) for their drug in the (generally speaking) most extreme circumstances? This data and new dashboard may offer you a path to doing that. Are you a plan sponsor looking to compare the amount of rebates your claims may have produced relative to the amount of rebate money your PBM actually gave you? This data and new dashboard can help with that. Curious how much cheaper your copayment / coinsurance would be if the plan sponsor would simply share those rebate dollars with you? This data and new dashboard might offer an idea into what that all means. Want to make a judgement call on formulary coverage based upon net costs of the drug? This data and new dashboard could help you make those assessments. In all these instances, so long as your are willing to work within the methods Texas uses to pay its own Medicaid claims, then you likely have the proverbial high-ground to perform these analyses.

Again, this dataset is not a panacea. We have already identified some limitations of the data in regards to Texas’ methodology for getting at 340B pricing, but that shouldn’t stop us from asking difficult questions based upon the public data made available under a CMS-approved SPA. Ultimately, in the information age, the data is what gives us power. It's an energy field created by all living things. It surrounds us and penetrates us. It binds the galaxy together. Data is the most important aspect of any program. Maybe, just maybe, this level of uncomfortable transparency into how much value is really out there in the middle of the drug pricing galaxy far, far away might help us finally boil the ocean that is drug pricing arbitrage.

If you made it this far, congratulations on following us on this damn-fool idealistic crusade. Give us your feedback and comments — your poking and prodding will help better inform our insights and analyses as we comb through and integrate this data into our ongoing research and reporting. We all pay a lot for prescription drugs. It’s time to add this line-item to the receipt.

 
Ben Link340B, MDRP, Rebates, Medicaid, Texas, Insulin, Lantus, Truvada