While a computer that could predict your future is tantalizing. Would you want a glimpse into your future, whether it be good or bad?
Until recently, most medical statistics have been bell curves created in hindsight. We know from studying the U.S. population that nearly 1 in 10 people have diabetes. We even know some factors that increase the likelihood of getting diabetes (such as being overweight or having a family history of the disease).
Predictive analytics utilizes data mining, artificial intelligence, statistics and modeling to make predictions. Imagine a computer that could look at your grocery store purchases, the size clothing you buy, your doctor visits, age, gender, marital status, career, employment status and more. A powerful enough computer could get most of that information from your Facebook page, credit card bill and your medical record. Then that computer could look at that same information over time to see trends and compare those trends to hundreds of thousands of other people. All of a sudden, that computer is a tool that can predict your chance of self-inflicted disease far more accurately than a doctor could during a 15 minute visit. If you had a 90 percent chance of developing diabetes would it motivate you to exercise more or eat a healthier diet? Maybe
We should be happy that the Affordable Care Act exists — the more powerful predictive analytics becomes, the easier it would be for insurance companies to deny us coverage for things we have no idea about.
Predictive analytics isn’t theoretical. And we should be happy that the Affordable Care Act exists — the more powerful predictive analytics becomes, the easier it would be for insurance companies to deny us coverage for things we have no idea about. And in all likelihood, things your insurance broker has no understanding of either.
Predictive analytics has the potential to make huge contributions to medicine. Hospitals are already using it to predict which patients have a high chance of needing an ICU admission, or will “bounce back” to the hospital after discharge, or have diabetic complications. And data mining is being used to detect fraud. Just recently a physician and fraudulent practice was discovered to be an illegal oxycontin pill distributor.
But predictive analytics isn’t perfect. Like all technology, it is up to the users to determine the ethics of the situation.
Dr. Salvatore Iaquinta is a head and neck surgeon at Kaiser Permanente San Rafael and the author of “The Year They Tried To Kill Me.” He takes you on the Highway To Health every fourth Monday.