For Digital Healthcare, Too Much Data, Not Enough Context


Delivering quality care digitally means having the platforms and tools that can sift through enormous volumes of data to rapidly identify issues.

Digital healthcare is undergoing a revolution. And it has a problem many other industries only wish they had. The issue can be summarized by the following:

Doctor to patient: “I see the problem. You’re generating too much data.”

That funny-but-true line was delivered by Dr. Daniel Kraft, founder of the Exponential Medicine Conference and a professor at Singularity University, in a recent discussion with CXOTalk’s Michael Krigsman.  The challenge, Kraft points out, is there is no shortage of data available to healthcare practitioners, but not enough context. The ideal digital healthcare platform, he says, should “learn from the clinician experience around the world, and synthesize the data into its actionable components,” he explains. “No one wants to see the raw EKG data, blood pressure, or other elements. What does it mean in context and even normalized to that individual? There are lots of layers to it. We’re starting to see the dots connect.”

See also: DataOps: The Future for Healthcare Automation

Kraft was joined by Dr. John Halamka, president of Mayo Clinic Platform, who pointed to the need to align health systems and data in real time to deliver the best outcomes. He pointed to radiation oncology or radiotherapy, in which therapy needs to aligned with a linear accelerator “that needs to be programmed by a physicist and an expert radiation oncologist. It takes six-plus hours of human time to review the films of the tumor and then program the linear accelerator.”

With real-time systems and data alignment, much of this delay could be eliminated, Halamka continued. “What if one developed a cloud-hosted mechanism to ingest images of tumors, AI algorithms that would be able to review those and, in literally near real-time, recommended the safest, lowest dose, most effective mechanism of delivering the radiation therapy to the patient and then auto-programmed a linear accelerator thousands of miles away without a radiation oncologist or a physicist nearby?”

Work is underway on that problem, introducing platforms that are “connecting incoming data and algorithms, delivering something of value back and, ultimately, improving patient care,” Halamka continues. “Broadly, platforms are connecting producers and consumers and building value.”

AI helps enable digital healthcare

Artificial intelligence will pave the way to effective and rapid delivery of healthcare services — but there are still issues to be dealt with, the doctors agree. Physicians “don’t understand what’s underneath [AI’s] black box,” Kraft says. “We don’t even understand, often, what the machine learning is pulling from. As we get more data and sometimes there are magical insights, almost like the picture of the retina from DeepMind that can predict heart attack and stroke. But how do we address the challenge of medical education and using that in smart ways when it’s often a bit murky about where it comes from?”

Extracting data from patients also needs to be simpler, and there is progress in this area as well, Kraft adds. For example, with voice technologies such as Amazon Alexa, “you don’t need to train your 80-year-old mom. Just say, ‘Hey, did I take my meds?’ or; Help. I’ve fallen and I can’t get up,’ or let Wi-Fi seamlessly pick up behaviors and even sleep patterns and vital signs.”

Such capabilities mean an “ambient-sensing world without wearables,” Kraft continued. To any privacy issues, he advocates the idea of an automated “health traffic controller” that can evaluate situations in real-time and notify clinicians.

Delivering quality care digitally means having the platforms and tools that can sift through enormous volumes of data to rapidly identify issues. These technologies also offer opportunities for predictive capabilities as well. “Imagine you’re a primary care doc with 2,000 patients,” says Kraft. “You don’t have that reactive mindset where you wait for them to show up in the ER with a heart attack, stroke, or late-stage cancer. You’re seeing a dashboard that might indicate from their sleep data that their resting heart rate went from 50s to 70s and something is going on; you might need to call them. Or their blood pressures are out of range based on where you dialed them in. It’s complex, but I think we’re starting to get to that realm.”

The challenge, both doctors agree, is bringing together and integrating countless proprietary and siloed systems into an integrated network — a process that’s going to take time. “We have thousands of healthcare systems in the United States, let alone the world, so it’s not a one-size-fits-all,” says Kraft.

“You ask yourself, ‘How do you make this stuff generalizable?” says Halamka. “Airbnb is a pretty sophisticated technology platform connecting producers and consumers but available to all at low cost with great utility. We need to get digital health products to any website or any phone. Then it wouldn’t be a huge barrier to distribute a lot of these things.”


About Joe McKendrick

Joe McKendrick is RTInsights Industry Editor and industry analyst focusing on artificial intelligence, digital, cloud and Big Data topics. His work also appears in Forbes an Harvard Business Review. Over the last three years, he served as co-chair for the AI Summit in New York, as well as on the organizing committee for IEEE's International Conferences on Edge Computing. (full bio). Follow him on Twitter @joemckendrick.

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