Case Study: Leading pharmaceutical company unlocks insights from 3rd-party data previously unaccessible

Our client, a large Pharmaceutical company, needed to understand the procedures patients with Chronic Kidney Disease (CKD) patients went through, from diagnosis onwards.

Specifically, they wanted to answer questions such as, “At which point in their treatment journey are they prescribed a certain medication?”, and “For an average patient with CKD, what are the odds of being prescribed one medication versus another?”.

To answer these questions, the client had purchased large 3rd party healthcare data sets, such as patient claims data, from data vendors including Komodo and HealthVerity.

They knew what they needed to understand from the data, but the data was complex and hard to analyze, even for technical analysts. They realized that they needed data analytics engineering experts to properly transform this large and complex dataset in order to get the answers they needed. They turned to BigLittleRobots to implement that solution.

After assessing the data, we designed a modern architecture that would ultimately present mapped patient journeys, visualized through an interactive dashboard. This would empower the client with the ability to interact, compare, and analyze the information and easily spot trends and insights.

We began by connecting the data. Due to security protocols of data vendors, the source data could not be ingested to an external data storage warehouse and required adapting solutions to the constraints of their environment.

The data was cleaned then modeled, creating rules, groupings and connecting tables that would make it possible to not only answer the questions the clients had, but create the flexibility for them to be able to dive deeper, see more patterns and trends, and answer more questions.
We then created a visual layer, giving the client easy access to in-depth mapped patient journeys through an interactive dashboard.

As a result, questions that used to take several weeks of analysis to obtain answers to, were now available in near real-time, leading to high impact strategic decisions.

The creation of interactive patient journeys also led to an important discovery. The client identified that black patients had a much higher likelihood of presenting with the disease at a later stage in its progression when compared to white patients, which not only leads to poorer outcomes but also costs the healthcare system more to treat.

This has led to publications in the Life Sciences space, as well as numerous strategic initiatives to reduce racial discrepancy in healthcare which help reduce healthcare inequity and reduce costs in the system overall.