Michael Koppenheffer, Executive Director
I spent Wednesday roaming around the Advisory Board's Amplify Technology Summit, but I couldn't walk more than a few steps without tripping over an example of how data-driven initiatives are improving health care.
Dozens of Advisory Board members presented case studies of how they used data and analytics to improve clinical quality, manage population health, and lower cost. Policymakers and industry experts took turns on the main stage, sharing their insights too.
But one presenter stood out as the most passionate advocate for data-driven health care transformation: DJ Patil, the White House's chief data scientist. In a Q&A session with attendees, Patil articulated his vision of how data science can lead to what he calls "compassionate products."
Referring to moderator Piper Su's Fitbit wearable monitor, Patil opined that today's monitoring technologies still have several stages of evolution left until they realize their potential.
A more assertive wearable
It's one thing for a wearable monitor to alert you that you didn't sleep enough last night, said Patil. But he argued that an ideal monitor would go one step further and actively warn, "You should sleep in today—you didn't sleep well for a few nights in a row, and last time you did this, you got sick."
"That device in your hand needs to tell you what to do with your day," he said.
Patil called this vision of health care's technological future "compassionate technology."
By way of analogy, he talked about phone-based map applications. In Patil's way of thinking, a merely "sympathetic" product would be a map that showed the traffic on your route. An "empathetic" product—better—would show other drivers stuck in traffic as well.
But a "compassionate" product would propose an alternative route—or if there was no alternative, would propose a podcast playlist to make the time go by faster.
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I was struck by Patil's technology evolution framework, in part because it parallels our firm's own experience with the application of technology to solve health care problems. Across the past decade, we saw the value of our technology products grow as we enhanced the products' analyses to include sophisticated comparisons between organizations or between clinicians—what Patil might term an "empathetic" technology approach.
But over the past few years, the Advisory Board (and others in the health care industry, to be fair) have been endeavoring to embed data-driven insights directly into administrative and clinical workflows, through specific products as well as by optimizing existing systems—to create "compassionate" products, in Patil's nomenclature.
Patil seems to believe that making health care technology more proactive and interventional is the right direction for the industry—but also that the industry has a long way to go to realize any of that potential.
The democratizing power of data
Still, Patil is optimistic that broader access to data and analytic tools will create new areas of value without enormous new investment. And he spoke from some experience: As the former data science head for social network LinkedIn, Patil explained that the service's popular People You May Know feature was the brainchild of a single data scientist's exploration of customer data, which the data scientist pursued even though the LinkedIn development team decided they couldn't afford to allocated resources to the idea.
In the case of LinkedIn's People You May Know, "a single person with data was a force multiplier." Patil said. "That's what we need to be able to enable in health care."
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