When it comes to hacking through the hype of big data, there are two types of analytics projects: those boundary-pushing advancements that, where they do exist, are mainly the product of big hospitals and academic medical centers, and humbler, more doable – but sometimes just as valuable – insights that can be gleaned by smaller providers.
“That demarcation between what’s practicable and what’s ‘Star Wars’ is a good one,” says John Hoyt, executive vice president of HIMSS Analytics. “When we do our Stage 7 validations, we do not ask for ‘Star Wars,'” he says, referring to the seven-step HIMSS Analytics EMR Adoption Model.
Clearly, some hospitals are better prepared than others to make big strides with big data. HIMSS Analytics figures show that 51.03 percent of hospitals are automated with financial business intelligence tools, while 45.8 aren’t – and don’t immediately plan to be. The numbers are roughly similar for data warehousing/mining technology (52.53 and 44.02 percent, respectively).
For clinical BI, the numbers are less encouraging: 29.04 percent have it, but 64.14 don’t. More hospitals are making use of clinical data mining tools (42.71 percent) but still more than half (53.69 percent) aren’t availing themselves of technology that could help make sense of the patient data they have.
The ‘Star Wars’ stuff exists – genomics, proteomics, metabolomics, for instance – and some clinicians are making big advances in the way treatment is delivered by drilling down into those billions of tiny data points.