Big Data Tackles Rising Healthcare Costs

Escalating healthcare costs are driving companies to collect and analyze “big data” on their employees in an effort to predict who may be at risk of expensive health complications and encourage those employees to alter their behavior to make healthier life choices – such as diet, activity level, etc. Perhaps an individual’s online activity, purchasing habits, and voting record (yes, companies are looking at employee’s voting record) can indicate their long term health – and more importantly, the long term cost of providing health insurance.

But beyond the privacy concerns – which are significant – in order for this concept to work, the algorithms that process such data to indicate future healthcare costs have to be developed, tested, and refined.

Now much of this can be done through simulation and data analytics, however, in doing so, there are bound to be a large number of false positives and false negatives as these algorithms are applied to real live people in our diverse, complex world. That isn’t to say the desired outcome isn’t achievable or worth the effort, it likely is on both counts.

It will just take time and a certain amount of patience.

It could be that in the short term there are errors in this analysis that lead companies to encourage the wrong set of employees to do activities that aren’t well suited for them, and lead, overall to increases in healthcare expense rather than decreases. These kind of growing pains will just have to be tolerated while the overall practice is being developed.

Indeed, the privacy and Big Brother concerns, raised here in the WSJ, will have to be tolerated as well.