American Journal of Medicine, internal medicine, medicine, health, healthy lifestyles, cancer, heart disease, drugs

The Big Health Data–Intelligent Machine Paradox

CLEF = Cross Language Evaluation Forum; CNN = convolutional neural network; LSTM = long short-term memory unit; METEOR = Metric for Evaluation of Translation with Explicit Ordering; MS COCO = Microsoft Coco framework; RNN = recurrent neural network.

What Happens When an Unstoppable Force Meets an Immovable Object?

This paradox plays out in many high-stakes global arenas—geopolitics, climate change, and financial markets, to name a few. Artificial intelligence thrives on massive disparate data sets, so it is not surprising that these data-dense megatrends are being shaped by artificial intelligence1 Although most humans do not face election, live near receding glaciers, or trade in cryptocurrencies, we are all learning that when manmade forces and intelligent machines collide, the costs and consequences can be real.

So it is with human health data.

Humans share 1 inherent right and bear 1 attendant risk—good health. In an inexorably older and progressively sicker world,2 another potential cataclysm confronts patients and physicians—the silent explosion of health data. The uses and fates of these health data, which will have grown from an estimated 153 exabytes in 2013 to 2314 exabytes by 2020 in the United States alone, are already being influenced by artificial intelligence.3 Medical students and trainees learn humanistic principles based on the Hippocratic precept, Primum non nocere (‘First do no harm’). Will humans use intelligent machines wisely, using big data responsibly for health care and medical training? Or will their power and immensity paradoxically produce unintended harms?

The expanding digital health data universe is the unstoppable force saturating the Cloud with big data droplets.

Individual personal health information resides in and fluxes through 2 types of data repositories. Administrative health care databases are operated by entities responsible for resourcing care and managing costs in socialized and quasi-market health insurance systems. Administrative health care databases are massive multigenerational payloads of demographic and utilization data (ie, pharmacy, physician, ambulatory, and hospital services)4 linked to multiple electronic medical records (EMRs) and increasingly homed in Cloud platforms compliant with the Health Insurance Portability and Accountability Act. Despite informatician and analyst expertise, their complexity and the density of their data defy standard statistical methods, limiting their applications to health care process and utilization management.

The EMR is the immovable object of health careit’s not going anywhere.

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-D. Douglas Miller, MD, CM, MBA

This article originally appeared in the November issue of The American Journal of Medicine.

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