Project management terminology was first being used around me when I was working at a health insurance. They were doing a project where they were trying to merge insurance services from two regions. They got a project manager and made us all come to meetings. I started hearing new terminology I didn’t understand.
In public health and healthcare, we are taught a lot about data and statistics. Those of us doing health analytics invariably learn SAS, which is a tough program to master. So it’s not like we are stupid, or don’t know anything about data.
Yet, if we find ourselves on application development teams, sometimes the discussion flies over our heads. That’s the way I felt working at the health insurance. Luckily, I wasn’t afraid to stop everyone and ask them to define the project management terminology they were using and with which I was unfamiliar.
Often times, I would learn that they were using a term that was useful to me as a biostatistician and epidemiologist. For example, I found the terms front-end and back-end so useful that I talk about them in this video, and more extensively, in my LinkedIn Learning data curation foundations course.
Project Management Terminology Health Data Analysts Should Know
I delve into this issue more extensively in the Application Basics course, but one of the issues is that biostatisticians, healthcare clinicians, and others with health data knowledge have been branded “subject matter experts” (SMEs) in the land of application development.
While that sounds nice on paper – being called an “expert” – it is actually a subtle dig. Being called an SME is basically like being told the you don’t have the knowhow to serve as a material technological contributor to the health application the team is developing. Watch my video below, where I explain the different technical roles on an application development team.
I interviewed a lot of health data analysts and people with a public health background, and a lot of them complained that they could not get through the SME barrier. They could not serve as an actual back-end programmer or developer on a healthcare application development team – even if that team was making a public health application!
The reasons they gave boiled down to structural barriers. As I describe in this blog post, public health teams are very hierarchical. If you are on one, and you want to act more like a data scientist on a data science team, this type of a hierarchy will prevent you from crossing over.
But even if you have a really nice boss who says, “Sure! Go talk to the project manager and see if you can serve on the application development team!”, you will likely have problems fitting in. That’s because these teams are totally not hierarchical, as you will see in this video.
Watch this video to learn how application development teams are arranged, and how they operate.
The bottom line is that it is very hard for a health data analyst – even one with a lot of experience – to get themselves onto an application development team. It’s more than just learning the project management terminology – which is useful. It is the challenge of learning how to work on these non-hierarchical teams.
That’s why the Applications Basics course is a foundational course in my online mentoring program for health data scientists. I feel that in order to retool and rebrand yourself as a data scientist, not only do you have to talk the talk, but you have to practice walking the walk.
Updated June 12, 2023.
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Project management terminology is often used around epidemiologists, biostatisticians, and health data scientists, and it’s often hard for us to admit we aren’t familiar with some of the terms. Watch my videos and take my Applications Basics course to get up to speed with vocabulary from the health application development domain.
