The math is brutal: The US spends nearly three times more on health care, per capita, compared to any other developed nation.
Yet, for all the money spent, we don’t seem to be getting any healthier. The US ranks 33rd in overall life expectancy. Obesity is rampant. Diabetes is epidemic. Asthma and other auto-immune diseases are on the rise.
The cost of health care should concern companies and consumers alike. Private businesses have been bearing the brunt of employee health costs for decades. Warren Buffet once called General Motors “a health and benefits company with an auto company attached.” That assessment is fair. GM, along with other American car companies, pays more than $1,500 in health care costs for every car they make. Japanese car-maker, Honda, pays only $150.
So, how can we bring costs down across the system while still improving the quality of care? One answer depends on leveraging big data in two areas: identifying highly qualified physicians and providing cost transparency.
When a person chooses a doctor, it’s hard to distinguish a top tier physician from an average one. This is especially true with primary care physicians. That’s because, up until recently, there hasn’t been a way to track who diagnosed and cured you in just one visit – and whom you had to see three times.
Then, there is the issue of cost – or more precisely, the lack of a fixed cost. A colonoscopy isn’t like a car with a set sticker price. It can cost $800 for the procedure in a doctor’s office, but up to $2,500 when performed at a hospital. Yet, both have nearly identical outcomes.
Vitals collects big data from decentralized sources like medical boards, association sites, government sources, publications, as well as patient-reported sources. In all, we aggregate and normalize more than 100,000 disparate sources of physician quality data. We then pair our database with centralized health plan systems. They’re the keeper of thousands of procedure codes, not to mention the details of various employee and individual plans.
Together, we weave a cohesive view of quality vs. cost for both members and plans. For consumers, this liberation of data –making it transparent — changes how they interact with their health insurance company. How powerful? Consider FedEx. Before the advent of the Internet, the company employed entire call centers to answer the question “Where is my package?” By allowing consumers to access their internal tracking system, FedEx saved millions by actually liberating data and delegating the task of tracking to the consumer – all while providing a better customer experience!
In the same way, we are empowering members to make better choices about how and where they spend their health care money. In the end, they end up with a better patient experience and less out-of-pocket costs.
As well, health plans not only save money from members choosing better doctors and lower-cost services, but they actually have the data necessary to sculpt their provider pool in order to build the most effective and economical network.
We may never buy a medical procedure in the same way we buy a car. But it is time to start leveraging big data in order to understand basic quality metrics such as “How good,” and “How much,” if we are to drive change in our health care system.