One of the areas where “Big Data” will have the most impact is in health care. Applying analytics to medical research and treatment will extend human lives and improve the quality of life for, well, pretty much everyone. Recently, health insurer WellPoint announced that it will be the first commercial customer for IBM’s Jeopardy-winning Watson system.
A Watson system optimized for health care would have the ability to understand patient symptoms and conditions and then scan every medical textbook, journal, study, and clinical trial to suggest possible courses of action.
The system won’t be making decisions; it will be more like the Data character on Star Trek: The Next Generation. Imagine a system that can quickly and accurately produce a list of potential conditions, suggest tests that will winnow the list down, and then offer up advice on the treatment that offers the highest probability of success while taking into account the unique characteristics of each patient.
The payoff will be substantial. It should radically decrease the number of times doctors misdiagnose a condition, and it will ensure that they are using the best treatments available. It will also eliminate much of the wasteful testing and “defensive medicine” that pushes up health care costs while adding little value for patients.
It always surprises me how individual doctors will treat the same conditions in quite different ways. They have the power to use leeches or lasers. How any doctor approaches a condition is based on his/her experience and, to a large extent, the latest research they’ve heard about.
Most of the time this is OK, but in some cases it can result in the wrong treatment and bad outcomes. With analytic-based assistance, doctors will see which tests are necessary and which won’t add any value saving time, money, and patient distress.
Analytics will also help researchers figure out which treatments produce the best outcomes. The head of a very large medical organization once told me that if he could give researchers a simple database that contained millions of records covering diagnosis, treatment, outcome, and patient history (no names), they would be able to radically improve treatments for every condition.
Unfortunately, we’re a long way from analytics aiding research as I’ve outlined above. It’s not a technical problem; it’s a set of cultural, political and economic hurdles that have frozen the existing system in place.
Medical vendors (particularly ISVs) are loath to change their proprietary coding schemes. Patients don’t want to give access to their health records to anyone for fear it could be used against them. Insurers (and the government too) want access to the records for their own reasons which is a scary prospect for many of us.
But progress is being made on all of these fronts, and analytics-led medicine is becoming a reality. In the next five years we should see an explosion of systems, software, and even new treatments that have come about because of this new focus on analyzing data.
Dan Olds is CEO of Gabriel Consulting Group and Chief Editor of inside-BigData.