Is Big Data Hurting Healthcare?

By Katie Wike, contributing writer

When used correctly, Big Data can find correlations between EHRs, emergency room wait times, money saving practices in medical imaging, and more. However, as researchers point out in an article published by the American Journal of Managed Care, the same data can be misconstrued to show correlations that do not actually exist.

Fierce Health IT reports authors of the study give the example that, for every five million packages of x-ray contrast media distributed to healthcare facilities, about six people die from adverse effects. Big Data can be manipulated in a way that those deaths can be found to be highly correlated with things like electrical engineering doctorates awarded and per-capita mozzarella cheese consumption.

“Because we cannot conceive of a causal mechanism, it is obvious that these variables play no causal role in x-ray contrast media deaths. That such high correlations can be easily mined from big data is concerning nonetheless, because it is not always trivial to assess whether they are telling us something useful.

“The way forward requires careful selection of observational research designs coupled with rigorous testing for violations of key assumptions on which causal inference relies,” the report’s authors write.

Big Data can fall victim to falsifications, which aims to pinpoint false assumptions about a suspected causal variable and outcomes. “Although caution is warranted, we should not dismiss big data too quickly. The way forward requires careful selection of observational research designs coupled with rigorous testing for violations of key assumptions on which causal inference relies,” write the authors.