Neha Patadia, a strategic national account executive for Premera Blue Cross, analyzes data sets to develop strategic health care proposals for Fortune 500 companies. As an instructor for the UW Certificate in Health Care Analytics, she teaches topics like predictive health analytics, data science for population health and consumerism.
In her spare time, Neha is a musician who plays five different instruments. Learn more about Neha, the certificate program and this rapidly growing field.
What is health care analytics and why is it important?
First off, health care is a massive $3.8 trillion industry. About one out of every three dollars spent in health care is wasted. Each year, 200,000 to 400,000 preventable deaths occur because of issues around health care. Although some issues are very difficult to solve, there are low-hanging fruits that we can address thanks to data.
Health care analytics is the process of looking at various data sets so that we can learn how to provide better access, costs and quality of care. The field covers a broad spectrum: it spans from people entering things into databases all the way to machine learning, predictive analytics and the use of neural networks.
Previously, you had to rely on phone calls and faxes to get health information, which made for a long and tedious process. These days, we can integrate information into databases. It’s easy to see how many labs or surgeries have been performed for a person because we can analyze their medical records. We can now do things like see if a patient had opioids prescribed to them by someone else in the state, in an effort to help cut back on opioid abuse and addiction. Companies have started leveraging algorithms and machine learning in fields such as imaging and radiology to predict if someone has cancer.
What is unique about the UW Certificate in Health Care Analytics?
The UW Certificate in Health Care Analytics is interdisciplinary, and by that I mean it covers a big breadth of topics. There are book-knowledge aspects to it, but there are also practical components, where you get to actually see and learn by playing around with real data sets. You get to explore the different types of technology that’s being leveraged and you can make your own hypothesis and assessments of data sets. Students get to explore what it’s like as health care analysts by working on their capstone projects with community organizations and businesses in the Seattle area. This practical aspect makes it very different from other courses.
Why do you love teaching health care analytics?
I’ve been teaching for three years at the University of Washington and around six years in general, and I love it. I love the feel of the community that we’re creating. I’m an East-coast transplant and have been in Seattle for three years. In Boston, there was a massive community of health care analysts, health care startups, health care entrepreneurships and formal education systems. When I came to Seattle, I felt like elements of that were missing. I wasn’t able to find that community very easily, and so by teaching, I can help foster that community.
Do you have advice for people interested in the program?
People are realizing the power of health care analytics and the power of data. Lots of companies, especially tech companies, are getting into it. I think funding has been increasing slowly in the last five years for startups and we are seeing a growth in the space.
Data can be challenging. Some datasets are super large and super messy. Leveraging that data to find meaning can take time. Just have patience. It’s all worth it. And lastly, data is just a tool. The story telling and the meaning behind what the data is telling is the real key so try to think about the complete picture and the story behind the datasets.
How does music and health care analytics intertwine?
I play five different instruments: piano, violin, guitar, flute and djembe, a Congolese drum. You use similar parts of the brain for both analytics and creativity. Like music, health care analytics has an element of math and an element of creativity. When you're actually playing music and when you're interpreting the composer's notes, you have to put your emotions and your thoughts into it to make sure that you're playing it the way that you want it to sound. Similarly, in analytics, you have to think about how to batch your data and the story you plan to tell with your data, because data is only as good as what you’re trying to portray and what you’re trying to tell.