The Use of Big Data and Analytics at Glooko

Many members of my family suffer from type 2 diabetes (T2D). The disease took my grandfather’s eyesight before it took his life. My dad has been suffering with diabetes for quite some time, and having a parent with T2D greatly increases my risk for getting diabetes myself.

There are some lifestyle changes that people can make to decrease the likelihood of developing diabetes, but previously there was not a single portable tool in the market to keep track of everything. Monitoring blood glucose (BG) data is especially important because BG levels may go too low due to a high insulin dose, a change in diet, or increased exercise. This happened to my uncle once while he was traveling by bike to his office and it almost ended in disaster. Fortunately, he is fine today but things could have been much worse.  After this incident, I wondered if there is a product that could help people with diabetes. Then I found Glooko.

As a person impacted by diabetes in a personal way, I wanted to work for a company that leverages my data skill-set to help improve the lives of people with diabetes. I learned about Glooko from a Facebook group and was extremely excited when I learned more about the company. I immediately pursued what I considered my “dream role.”

A big-data revolution is under way in healthcare. Healthcare companies have been aggregating years of R&D data into medical databases, payers and providers have digitized patient records. Even the U.S. government opened the doors to its healthcare knowledge data, which includes information from clinical trials and patients covered under public insurance programs.

Glooko uses data analytics and reporting platforms to identify trends and create reports to simplify diabetes management for people with diabetes, providers, and coaches. But, the application of data has much more potential. By using predictive algorithms, we can predict if someone is going to experience hyper or hypoglycemia  or the amount of exercise that should be completed to get the best outcome or the number of calories that should be consumed in order to control a specific person’s BG.

This data can also help with diabetes prevention and in slowing down the progression of the disease in people already diagnosed. Researchers are understanding variations in the disease to develop predictive models and identify risk factors for the onset and progression of T2D. The researchers claim that the model identifies new risk factors for T2D and is better at predicting disease onset than current models.1

We are going through a digital and data revolution. And I believe that data will help improve quality of life and make the world a better place. I am happy to be a part of Glooko and contribute to breakthrough work to help people with diabetes.

1 ″How To Cure Diabetes With Precision Medicine -.” Healthcare Big Data Analytics, Turnkey Data – John Snow Labs. DATAOPS, 15 Feb. 2017. Web. 13 Apr. 2017.

Ramakrishnan Kumar

Ramakrishnan is data enthusiast who is passionate about Data analytics and technology. He loves music, exploring nature’s beauty, and cooking.