Analytics is a staple of most Canadian industries. But it has yet to make a serious dent in one sector that is overflowing with data: Medicine.
That could be about to change, a Toronto conference on data analytics in health care was told Tuesday.
“A lot of good work is going on,” Dr. Richard Irving, conference co-chair and associate professor of operations management and information systems at Toronto’s York University Schulich School of Business, said at the end of the first day of presentations. “There’s reason for hope.”
During the day attendees heard how
--Cancer Care Ontario, a provincial agency for chronic diseases, has set up a data analytics centre of excellence;
--a Calgary hospital uses analytics to guide doctors to use better practices for patients with diabetes;
--Toronto’s Mount Sinai Hospital has started to use analytics in patient surveys to improve trust with clinicians;
--a children’s hospital gathers 90 million of points of real-time data a day for analysis in a neonatal intensive care unit.
This last project, at Toronto’s Hospital for Sick Children, is truly an example of big data in action in health care. The Artemis project hopes to be able to predict when babies in distress are about to fall prey to infections.
In fact, there’s a cloud version that connects to several hospitals around the world gathering data on sick babies.
“When you think about how much computing has changed and how much the backbone of network infrastructures have changed, we really are at a point now where big data solutions for health care make sense,” Dr. Carolyn McGregor, Canada research chair in health informatics at the University of Ontario institute of technology and an Artemis project leader told the conference. “We have the capacity.”
The goal of analytics in health care is to help clinical teams improve patient outcomes, speakers said, because the way medicine has been practiced for years has to be improved.
The conference heard that variations of patient outcomes across cities, provinces (or across countries) can’t be explained away. Some doctors’ patients do better than others and health care providers have to find out why.