The Atlantic, October 10, 2017
Olga Khazan

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[...] Experienced doctors use Human Dx for their most difficult cases, and newer providers use it to hone their skills. Johns Hopkins Hospital and other teaching hospitals are now using it to train medical residents. Georgia Lewis, a nurse practitioner who works with Nundy, used Human Dx when, two months into her stint at Mary’s Center, all the other providers went on vacation. Rashes can be confounding, so she’ll upload them to Human Dx along with a photo.

“We thought we can really help our communities because we have challenges getting specialty care.”

The contributors to the project are vetted based on how accurately they’ve solved past cases. Human Dx uses machine learning, which means that eventually the algorithms powering the diagnosis suggestions will become “smarter” based on the input of the doctors using it. The hope is that, over time, Human Dx can help reduce misdiagnoses, which according to studies happen up to 20 percent of the time.

Human Dx hopes to soon roll out to all 1,300 safety-net clinics in the United States. Ron Yee, the chief medical officer of the National Association of Community Health Centers, is helping clinics like Mary’s Center start using the platform. “We thought we can really help our communities because we have challenges getting specialty care,” he said.

Yee and his colleagues are still figuring out how to fit Human Dx into so many primary-care doctors’ workflows. They’re also puzzling through that eternal health-care question: how to get paid for it. “Does insurance accept this?” Yee said. “I don’t know what it looks like.” [...]

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