Using big data analytics to save the lives of newborns
There are a range of diseases and syndromes in newborns that, if undetected and untreated, can be fatal or debilitating. For example, phenylketonuria (PKU), an amino-acid metabolic disorder, can lead to severe developmental issues. PKU was one of the first diseases regularly tested for by physicians. And, when detected early enough, children with PKU can manage their diet and can lead normal lives (indeed, I heard of one example of a child that was top throughout school and is now a physician).
Recently, I attended a function by the Newborn Foundation to commemorate the work of newborn screening advocates. It was interesting to meet this group, all folks passionate for the welfare of newborns. I was also given an inside view of how hard it is to change health policy, to add one new screening protocol to the list (the ramifications are huge).
But the most interesting thing to me was how data-driven these folks were. They knew that they needed the hard numbers to show why a new test was necessary. They used data to inform policy. For example, they needed to show the cost of testing versus the cost of not testing, such as emergency visits or reduced quality of life and potential increased care of diseased children. One person was comparing the price of annual screening to the cost of providing Lipitor. Another said, “little test, big bargain.”
Also attending the event was Dr Carolyn McGregor, from the University of Ontario Institute of Technology. Dr. McGregor built a system at Toronto’s SickKids hospital to monitor newborns and predict dangerous infections 24 hours earlier than traditional visual methods (watch this great video about her work).
The Newborn Foundation recently added one more screening to the list: for Complex Congenital Heart Defects. And, with data being at the center of the Newborn Foundation’s efforts, then it should not be a surprise that the interest in Dr. McGregor’s work was high. Folks asked her how her system could be used for screening of heart defects, using an algorithm to predict heart function or circulatory issues. They also asked how perhaps her system could be used in developing countries, where screening could have an even greater impact.
Use that data
Dr. McGregor said it best when she said that “the babies give this data to us freely,” so we should use it to make their lives better.
Which got me thinking: Organizations that don’t understand that the future of healthcare is data-driven will fail to provide the best care they can possibly give.
We must do our best to make use of this valuable data these babies, and all our patients, so freely give us to make them healthier and happier and to be productive members of society.
Do you feel that you’re data-centric? Do you think healthcare will be more data-centric? How do you use data in your organization? Do you have stories of how better use of data led to better outcomes?
Let us know!
View this short presentation for an overview of the University of Ontario case study: