Michael Dietz started as a product owner at MMIT in September 2020, where he works mainly in the data services department. He works to automate data extraction, helping to smooth access to therapies for MMIT clients.
I manage an application that extracts, transforms and loads data for our data operations team. We access public sources and obtain publicly available data to create insights and make better decisions from it all.
I work very closely with MMIT’s data operations team, analyzing their needs, because ultimately that is the client that I work for. I’m taking back requests of what type of data they’re looking to obtain, creating methods to obtain the data efficiently and automate the collection of that data. This takes a lot of the manual work out of the equation and allows the technology to do that for everyone.
Traditionally, someone would access a public source, look up and collect coverage or restriction data, then import the data to our database. That process requires a lot of manual effort and takes a lot of work.
Where I come into the equation is to say, we’ve identified a repeatable process here, it has standard steps to collect data, so let’s build a program to do that for us.
There are times when we just can’t — the data could be updated infrequently, or it’s in a format that we can’t process. So there are certainly cases where automation is not the answer. In those cases, we have a team that can evaluate and bring that in for our data operations team to use.
I could not say it any better than our motto, which is that we smooth access to therapies. We’re trying to make it as easy as possible for our clients to access drug and coverage data, discover trends and derive insights. We strive to meet that goal every day.
The variety, hands down. We work with so many different talented people and there is never a dull moment in trying to solve some of these problems to the data that we want. Every day is a new opportunity and there’s always somebody new to work with.
Maintaining the vast amount of sources of data. Each of these sources updates individually and maintains their data in different ways. The challenge is in keeping on top of everything and ensuring that we consistently obtain the data and make it available to the data operations team.
One of the exciting things on the horizon for us is that we are starting to further utilize data science to make some of the decisions around pharmaceutical and health care product data. I can see where we are in five years: We will be able to predict when coverage changes occur, have the ability to notify our clients sooner and gain a better understanding of how that affects the overall health care industry. I believe the future for MMIT is becoming more intelligent with the way we obtain and process data.
I am married and have a 4-year-old son, so my family keeps me plenty busy. I also love to garden and to cook. We moved into a new house recently that was pretty much a blank slate. So I’m always planting new flower beds, new gardens, new trees, and enjoying our home.