BI Insights

Should Big Data Pick Your Next Doctor?

14 December, 2016

Should Big Data Pick Your Next Doctor?

This past spring, Owen Tripp, 37, was living the Silicon Valley dream. His latest company, Grand Rounds, had raised $100 million at a valuation said to be about $1 billion. He and his wife had a new baby, their third child. Sure, the noise from the kids–all of them under 6–meant he slept with earplugs, but so what? Life was great.

Then he woke up one morning convinced he’d left an earplug in his right ear. He checked. No plug. But he couldn’t hear anything in that ear. His doctor twice said it was just clogged before recommending an ear, nose and throat specialist. When he pulled up the specialist’s Web page, something didn’t feel right: Her expertise was in swallowing, not hearing. “I’m not feeling super-comfortable with the way this is being looked at,” he remembers thinking. “Why am I being referred to somebody who seems to be more versed in swallowing?”

Most people would just go to that doctor anyway. Or they’d call friends in the hope that someone would know a specialist. But Tripp is not most people: He is the cofounder of Grand Rounds, which is focused on matching patients with the right doctors. The company uses a database of some 700,000 physicians, 96% of the U.S. total, and merges it with insurance-claims data and biographical information to grade doctors based on the quality of their work. The idea is to help people find a physician who will give them the right diagnosis the first time around and link patients with experts who can give second opinions. For individuals, it costs $600 to get a doctor recommendation and $7,500 to get a second opinion.

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