A few years back, it was uncovered that Target, using data collected from their shoppers, was able to target (pun definitely intended) shoppers who might be pregnant—oh, and predict their due date too. Creepy, but completely and surprisingly legal.
Target assigns customer IDs to each shopper that associates collected data by email and credit card transactions in-store—sources that open the flood gates of Big Data for just one consumer. Andrew Pole, a statistician for Target, identified recent purchases like unscented soaps and lotions, cotton balls, wash clothes, and large purses, along with about 25 other products, that give shoppers a “pregnancy prediction” score. In turn, Target launches coupon campaigns featuring diapers, cribs, and baby shampoo galore to expecting moms—sometimes before they’ve even told their own parents, read about that story here. Target isn’t the only retail giant using Big Data and Business Intelligence strategies to better market to their consumer base.
Google seems to think they aren’t far behind in medical diagnosis either—with the launch of Google Now, and the constant push to connect Google with all aspects of life, it’s not too farfetched. Data from heart rate monitors, fitness/food journal apps, activity trackers, recent searches (like “what causes heart burn”), and other data sources in the hands of healthcare’s movers and shakers could be the change we want to see in U.S. healthcare.
Not to say progress in predictive analytics using EHR data isn’t happening—it is. However, the inclusion of data from social media, cell phone apps, and other sources could propel predictive analytics one-hundred-fold. That being said, the cost of time, resources, and capital, not to mention the flaming hoops of privacy and ethical concerns to jump through, would be astronomical.
In defense of both parties: Target and Google are product pushers, and their time and money is dedicated to increasing profits and selling more efficiently; healthcare providers are life savers, and their time and money is dedicated to improving the delivery of care. Their goals are the same, but their priorities are different. It may be quite some time before healthcare policy, technology, and funding catch up to the retail titans; however, the industry is picking up speed as we discover the benefits of life-saving predictive diagnosis from Big Data far outweighs the costs.