What’s next for big data?

While big data — the term for data sets that are large and complex — in the health care realm can probably sound scary to benefit brokers and advisers who may just be starting to consider data analysis for cost-savings with wellness programs and for self-funded clients, there’s a lot more to come. A June 5 perspective piece in the medical publication New England Journal of Medicine by Dr. Sebastian Schneeweiss outlines some potential developments for big data to better use this information for patients and doctors, and ultimately insurers and benefit brokers, alike.

See related: Importance of data analysis for brokers increasing

Schneeweiss says the two most important next steps for big data are “the generation of new knowledge about the effectiveness of treatments” and “the prediction of outcomes.” Right now, computers cannot execute either of these functions but if they were acquired, they could “directly influence patient care in the very systems that generated the data,” he writes.

The author goes on to list the necessary components of data analysis to get to these next steps. “All of these components of analytics have been developed, yet our health care system has not been able to systematically integrate them into its work to establish an ongoing learning-and-improvement process … why aren’t we closer to that goal,” he says, nodding to the agreement from all parties in the health care community that more data would be better for patients and health care costs.

The elements necessary to be infused together are, according to Schneeweiss:

  • Methods to “ensure” that patient comparison within big data are similar enough to each other
  • The analyses need to be automated  “without loss of validity”
  • Once automated, they need to be cued to “refresh” as much as every 24 hours
  • Big data interpretation software needs to be easy to use so that training is quick
  • Final data should be easy to read

Schneeweiss tells the health care community to remember the ultimate goal of big data — to help the patients receive better care. From that, all the other benefits like health cost reduction, error eradication will also stem, ultimately helping parties like insurers and benefit brokers, to boot.

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