How do you fix a problem that's beyond your area of expertise? As a veteran admin professional in U.S. healthcare information management, Jennifer has seen firsthand just how much data the industry generates. It was so much data, in fact, she knew that hospitals couldn't possibly unlock their full potential with the current analytic process.
Unfortunately, Jennifer didn't have the tech skills to solve this problem, and most courses she had come across offered a career change she didn't want. It seemed like her aspiration to make a difference would remain unrealized — that is until she was promoted to an analyst position. The promotion solidified her entry into the tech world.
She promptly enrolled in TripleTen's Data Analytics Bootcamp. And six months later, Jennifer is ready to start transforming US healthcare management from within.
We spoke to her about her journey and how data analytics can change healthcare for the better.
The Hidden Treasure
Over the last 15 years, Jennifer has analyzed how insurance companies paid her hospital for healthcare services. If insurance companies refused to cover a cost, Jennifer would sift through the data to determine the reason, and come up with the best course of action to ensure payment. She knew this common issue came with potentially detrimental results: either the doctor or patient could lose money. With the high cost of medical services in the U.S., many patients risked losing their homes.
Dealing with such sensitive data took real skill. So upon her promotion, Jennifer felt a fresh perspective would do her some good. She wanted to learn more about data analysis — getting some insights on creating dashboards and identifying trends in the data. However, this wasn't her sole motivation for returning to the classroom.
As an experienced healthcare administrator, Jennifer couldn't help but notice how much data was compiled in the system. And while plenty of vendors were providing automated data analytics for hospitals with software and AI, Jennifer saw they were missing what this data meant for real patients. It was coding for the sake of coding, and she wanted to change that.
"They don't really employ people who know what purposes the data has been collected for. [...] I wanted to do something different. I wanted to understand the trends in the data to create insights into what hospitals need to do differently, like what talks they need to have with the insurance companies. [...] The US healthcare system needs to know how to use the plethora of data to gain insight on what the future of the US healthcare system looks like. For example: how the poverty-stricken areas of the US impact diseases like Diabetes and Heart Failure."
Always passionate about tech, Jennifer had begun online web and software dev courses in the past, but either got stuck or lost the motivation to finish. Her promotion, combined with the pitfalls in U.S. healthcare, became the nudge she needed to finally tap in.
Jennifer joined a local meetup and started considering different bootcamps. This included Data Analytics by TripleTen. It had scholarship options, so Jennifer decided to take advantage of this opportunity. She submitted a convincing application and ended up winning! (Go, Jen!)
Harder Is Better
Most people shy away from discomfort. But not Jennifer — she knew that forcing her way through the curriculum would make her a better professional in the end. This didn't make the journey any easier, however, especially since she had no experience in software development and felt intimidated by math. Any resource she could access, she used: from Google, YouTube, to her tutors and peers.
"It was very complicated. A lot of business problems I did were tech-related, so I really had to analyze outside of what the curriculum was teaching me, think about putting myself in the shoes of a software developer. [...] I really wanted to succeed because being able to write code in Python, seeing beautiful dashboards and tables of data from these lines of code, was really exciting for me… The more projects I completed the easier it became."
Another challenge was balancing the course with her full-time job. Luckily, Jennifer had prior experience doing online learning, so she knew how to schedule and prioritize. Spreading the course load through nights and weekends, she'd study for about 15 to 20 hours a week for six months. Some of that time was spent re-reviewing the ideas she didn't understand and asking for help when she felt stuck.
Still, Jennifer thinks pushing her limits worked to her benefit.
It was a challenge, but because it was a challenge, I think I learned a lot more from it. Because I was forced to be in a situation where I had to really keep asking questions, keep figuring out how to solve a problem so the code worked.
Rolling Up Her Sleeves
True to her expectations, Jennifer really did learn a lot. She emphasizes the importance of soft skills, a key part of the program. When an analyst creates dashboards for a business — or for peers, in Jennifer's case — they've gotta know how to talk to their audience.
"Being able to ask specific questions of your employer, of what they want the data to tell, it's gonna be really helpful… [...] You can know the tech side and know how the program works, but if you can't communicate that to an audience that's not tech-focused, it's pointless."
Applying her hard skills, however, will take some time. Jennifer believes it's important to share her experience with people who may be in the same position, so she started a blog, MedicalCodingForMillennials. She aims to build a community of peers to show what the future of the US healthcare system needs:
"There are situations where people have COVID in low-income areas, and there's data related to that. And even though I'm dealing with the finance side, it's a lot bigger than that. That's why I'm trying to provide options for people to share my experience because it's important for people to understand that it's so much bigger than what they think."
Looking Towards the Future
Now, Jennifer is building a healthcare-focused portfolio, eventually planning to add it to her blog. She plans to start with cohort analysis: "It's easy to find cohorts in different patients' populations," she says. And there's plenty of publicly available data she can use. She also wants to experiment with Tableau dashboards and notebooks, but since most of her TripleTen projects were tech-specific, she'll need some time to wrap her mind around them.
We'll be looking forward to reading about your discoveries, Jennifer!
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