MEDgle’s (as in “medical Google”) nifty analytics platform, now in beta, taps both personal health information and advanced statistics to help make clinical diagnoses.
“We have a supply-and-demand problem. We have an influx in the U.S. of 80 million baby boomers. But we also have about a 10% to 20% shortage of general practitioners. Worldwide, it’s a 30% to 50% shortage. At the same time, we’re collecting 100 times more data than ever before. The data itself is providing an opportunity.
There are numerous interactions between the patient and the care infrastructure. Maybe over the phone with a nurse practitioner, or at an emergency-care center, or with a physician. Each place where care is provided should be personalized. We see this trend toward hyperpersonalization, with Google, Amazon, and the rest. They deliver individualized experiences at scale.
The question for us: How do you scale a physician’s expertise? We’ve mined data from the CDC, the WHO, articles, and textbooks. We’ve presented them to physicians, who have spent 20,000 hours ensuring that the data are quality. And that’s how we developed the ‘doctor algorithm.’ It’s a graph of medicine that looks at how illnesses relate to age, lifestyle, or gender. For example, what is fever plus asthma, plus the patient is 32 years old? How do you combine these data into a meaningful diagnosis? That’s what the doctor algorithm is. It’s that synthesis that makes sense of the world’s health data.”
[Photo by Gabriela Hasbun]