With the rising costs of health care, and the growing demographics of baby boomers, health administrators are always looking for savings. A new and provocative study out of the Indiana University suggests that computer modelling can choose better and less-expensive treatments than the physicians alone, resulting in a 50% reduction in costs and 40% increase in patient outcomes.
By using a new framework that employs sequential decision-making, the previous single-decision research can be expanded into models that simulate numerous alternative treatment paths out into the future; maintain beliefs about patient health status over time even when measurements are unavailable or uncertain; and continually plan/re-plan as new information becomes available. In other words, it can “think like a doctor.”
Although Derrick Harris at Digacom states that nobody is suggesting we replace physicians with computers, he does point out other advances in this area:
IBM has been banging this drum loudly, most recently with two new commercial versions of its Watson system — one of which is designed to determine the best-possible course of treatment for lung cancer patient by analyzing their situations against a library of millions of pages of clinical evidence and medical research.
In July, I highlighted 10 ways that health care providers and startups are using big data to improve effectiveness and decrease treatment costs.
More recently, I explained how access to more — and better — data is critical to everything from rating doctors to, possibly, curing cancer.