Q&A with Analytics Specialist, Jeremy Bakken
Jeremy Bakken, a healthcare IT professional with more than 15 years of experience, joined Bluetree's Analytics team this past June. Now, he's already in a Data Architect role at a client of ours and has some wisdom to share in this blog post.
RYAN: What brought you to Bluetree? You’ve had a pretty extensive career in reporting, but have even had a stint as a Psychology professor. What is it about this role and healthcare IT that is so appealing?
Jeremy: I was really impressed with Bluetree’s vision and team-based approach toward partnering with clients to help solve the complicated problems facing healthcare organizations. Analytics will be key to helping solve those problems, and helping to move the team forward into these new challenges was an appealing prospect to me. In both my previous career in academics and currently in healthcare IT, I’ve really enjoyed telling stories with data. Healthcare organizations are generating increasingly more and more data, and I’m excited to continue helping use data to make informed decisions.
Ryan: Report development runs deep for you, so you’ve worked with a lot of data in your life. What are some unique lessons you’ve learned through working in this arena?
Jeremy: Healthcare data sets are complicated and the rules constantly change. I’ve learned to try being as creative as possible in building reports that are flexible, that can be easily modified, and require minimal maintenance. I’ve also learned that it’s never too early to start thinking about data needs. From strategic goals, to EMR configurations and data entry workflows, decisions all along the way can impact the quality and availability of data. Helping people throughout organizations to understand their relationships to data can be invaluable to quality report development.
RYAN: Standardizing report development processes is a focal point for organizations. You’ve dealt with a handful of organizations in this realm, what’s the overarching key to successfully managing these types of projects?
Jeremy: Under pressure to get things done, I think we sometimes forget that communication is a key component to successful report development. Building great relationships between report consumers, applications analysts, and report developers makes it so much easier to understand the needs that are driving requests and translate them into useful reports. I may be biased, but good analytics teams can generally build whatever you ask for. The tricky part is that sometimes what people ask for is different from what they really need. Having relationships and processes in place to communicate those needs effectively can have a huge impact on the efficiency of development, help reduce backlogs, and keep everyone happier.
RYAN: Big data is only going to get bigger. Is healthcare IT prepared for this greater demand for data? What’s the future look like for healthcare IT analytics?
Jeremy: I like the W. Edwards Deming quote “Without data you’re just a person with an opinion.” As data sets and capabilities grow, it’s going to be even more important to think about data as a business asset. With this perspective, the responsibility for understanding how to handle a greater demand for data is a problem for the whole organization, not just IT teams. The reverse of the quote is also true, though. Without opinions (i.e. ideas, goals, direction), having more data isn’t going to solve any problems. So, as needs grow, it's important to go back to the basics: a focus on understanding the goals and business needs that require data. What’s most important as we look forward to the future of healthcare data is to focus on clearly defining our questions and the problems we're trying to solve because they will help define the new technologies and tools to invest in.
RYAN: If you could pick one thing that excites you the most about the future of your area of work, what would it be?
Jeremy: Impossible to pick just one thing, but the former academic researcher in me would be disappointed if I didn’t mention some of the exciting things in predictive analytics and machine learning. Using statistical analyses to develop a more scientific understanding of healthcare problems, allowing us to make more sound generalizations and have more confidence in our predictions about future patterns, seems like a really logical next step. Using smart computers to help do the heavy lifting and give us insights that we might not have the time or capacity to do ourselves has the potential not only to advance healthcare analytics, but also to free up resources to work on other cool data projects!