Just Launched: A Prescription for Healthcare Data
Spending on prescription drugs amounts to more than $400 billion in the United States alone, approximately 20% of U.S. healthcare spend. While prescription drugs are an increasing facet of daily life – often meaningfully improving many people’s lives – few understand or have access to the incredible amount of data generated in the conception, development, and regulation of any prescription drug.
What activities take place before a drug makes its way into a patient’s hands?
The Power of Data in Aggregate
At Enigma, we believe that data accessibility begets discovery. Our newest Enigma Labs project,
A Prescription for Healthcare Data, highlights the development life cycles for more than 80 commonly-prescribed drugs through a series of nearly 1,000,000 data points brought together from 9 different government portals in the U.S. and E.U.
While all of the datasets presented in this site are technically available to the public, they are often disjointed, messy, and not user-friendly. As such, rarely (if ever) have these datasets been joined and contextualized to provide meaningful, accessible information to the population at large.
By linking these healthcare datasets, we built a more complete narrative around drug development, from patents and clinical trials to adverse events and Medicare spend. Our goal is to facilitate a deeper understanding of the many events that pertain to (and the decisions that influence) the life cycle of a pharmaceutical drug.
Building a Drug Life Cycle
While traditional health-focused public agencies such as the Food and Drug Administration (FDA) or the Center for Medicare & Medicaid Services (CMS) may capture key statistics on drug approval activity or drug utilization/spend, analyzing this data on its own offers only a singular view into a specific part of a drug’s life cycle. By connecting these datasets, plus a number of alternative datasets, such as U.S. patent filings, we were able to build a comprehensive timeline of key events making up a drug’s development and usage. Here are some of the things you’ll be able to learn about the lifecycle of each drug:
Cost: Medicare spending, cost per unit, annual out-of-pocket cost per patient, price increase/decrease from 2010-2015, average spend for drugs treating similar conditions
Usage: how many people utilize the drug, which drugs are commonly prescribed under medicare
Patents: filings, including first discovery and researcher, patent expiration, competitors (or lack thereof)
FDA applications: applicant name (manufacturer), type of application, application by manufacturer, how different application types may protect exclusivity, effectiveness of current policies to inspire competition
Clinical trials: age, gender, number of patients, length of trials
FDA approvals: processes and timelines, market exclusivity strategies for drugs
Adverse events: number of events, patient, gender, type of side effect, outcomes
Since a drug is often represented many different ways in the market (e.g. re-brandings, re-formulations, or generic entrants) we chose to focus our visualization on a single molecule to provide a more holistic view of each medication. This enables you to see pre-market events as well as information regarding both brand-name and generic formulations of the same drug. Additionally, it enables you to quickly compare the shape of one drug’s development to that of other drugs treating similar conditions.
Note: we’ve included an entire section about our methodology on the site if you’re interested in the details.
Big Picture Exploration
We’ve sifted through dozens of tables and millions of rows of data to create a streamlined view of each of the 80+ drugs. With this data connected, you can easily see not only the granular details about a specific drug but also a more comprehensive picture of how drug development has changed over time.
Beyond the major milestones, there are any number of paths to follow and questions to explore throughout the site. We hope you’ll let your curiosity lead the way. If you’re in need of inspiration, here are a few ideas to get you started:
What’s the average length of a clinical trial?
How much time lapses between for approval of drug and creation of the first generic?
Does Medicare see meaningful prices fluctuations or decreases post-approval of a generic?
Have generics entrants led to reductions in price?
In the coming weeks, we’ll be publishing a series of follow up investigations and deep dives here on the blog, so be on the lookout. In the meantime, happy exploring!