For the first time in our existence, CMS has released drug pricing data that overlaps with the date of our launch. As we ripped open the data and examined CMS’ gift, we found some major changes in the way that the state of Ohio reported their data – and it has revealed some eye-opening information about PBM and pharmacy margins on prescription drugs. Given all the drug pricing noise out of Ohio, and the federal heat on PBM “spread pricing,” we decided to do a deep dive into what’s happening in Ohio, and how its new data provides incredible clues to determine where the money flows within the drug supply chain.
Recently, CMS updated their State Utilization databases, which provides quarterly drug pricing data that shows what state Medicaid programs are spending on prescription drugs. This most recent data update ended up filling in most of the Q2 2018 potholes and extended the 2018 data to include large portions of the third quarter. We have updated all of our dashboards that rely on this dataset, rolling all of them forward to Q3 2018, and there are some insightful takeaways. This update is a really big deal for us at 46brooklyn, because it is the first time that a dataset’s timing will overlap with our existence as an organization. With our launch in August 2018, this meant that CMS’ latest utilization data update for Q3 2018 would be the first real quarter of data that could have been theoretically impacted by our work and Ohio’s work to bring transparency to drug pricing in state Medicaid programs and beyond. After analyzing the data, the results are nothing short of amazing, and a clear indication that this system is in the midst of change. Here’s our insights.
A few months ago, we released our Medicaid Markup Universe that collects all generic drugs dispensed within different state Medicaid programs and displays each as a bubble. The larger the bubble, the greater the cost the state is paying for that drug relative to its acquisition cost (i.e. “markup”). While that dashboard provides a good qualitative feel for individual drug pricing distortions, it doesn’t help quantify the distortions. To better identify those distortions in each Medicaid program, we designed a new visualization that drills down to three different groups (or celestially-speaking, “galaxies”) within the universe. We call them the High-Cost, In-Range, and Low-Cost galaxies. Our newest dashboard, the Medicaid Markup Galaxies, shows which drugs state Medicaid programs may be underpaying for, and perhaps more importantly, which drugs they may be overpaying for.
Over the past couple weeks, we’ve been reflecting more on how neat Bloomberg’s Ohio Medicaid markup bubble chart was in their recent article, “The Secret Drug Pricing System Middlemen use to Rake in Millions.” We’re kicking ourselves now that we neglected to delve deeper into this in our report, “Bloomberg Puts Drug Pricing ‘Markups’ on the Map”. But like fine wine, good visualizations only get better with time, so it took us a few weeks to fully realize the possibilities that such data analysis could open up. Bloomberg’s excellent visualization does, however, leave a few open questions. What do other state Medicaid managed care programs look like? How do they compare to state fee-for-service programs? What do all states look like? To answer these questions, we set out to build a new visualization dashboard to compare drug markups between state Medicaid programs. We call our creation the “Medicaid Markup Universe” (because it looks very celestial). In this new visualization tool, we found a disturbingly large difference in drug markups across generic drugs in state Medicaid managed care programs, resulting in a slew of warped incentives that pressure supply chain members to value certain medications over others, and thus, certain patients over others.
Earlier this week, Bloomberg reporters published their results of a fascinating deep dive into Medicaid generic drug prices. The piece did an excellent job explaining the ins and outs of the hidden pricing spreads that exist on generic drugs, and it featured some intuitive visualizations that helped educate readers who may not have been familiar with these little-known drug price tactics. The analysis conducted by Bloomberg also integrated the results of a recent report from the state of Ohio's Auditor, which found that in a one-year span, PBMs pocketed more than $224 million dollars in spread pricing. Armed with this data, we set out to discover if we could deduce what pharmacy margins were over that same time period in an effort to peel back new layers of the onion and provide better information on where the money is going. Check out our newest drug pricing report to learn more about hidden prescription drug markups.