Open Health Data Comes of Age

0 Comments19 June 2014

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Two weeks ago, the Health Data Consortium put on what’s become a major annual event for Open Data aficionados: The Health Datapalooza, designed to encourage new applications of Open Data in healthcare. This is the fifth such event since they started in 2010, and the Health Datapalooza has grown from a brainstorming meeting of a few dozen people to a well-produced gathering that attracts about 2000 people each year.

I was also at last year’s Health Datapalooza and I found a significant shift in just a year’s time. While the Datapalooza has always been promoted as an event about open health data, it’s actually included many companies using data that is very closed indeed. A number of Datapalooza companies work to analyze hospital records or health insurance data in new ways. While that’s important work – both to reduce administrative costs and improve patient outcomes – it’s not really an Open Data use case.

This year, however, it’s clear that Open Data is playing a larger role in healthcare in the U.S. the UK. A major reason is that these governments are releasing more and more open health data for public use. At this year’s Datapalooza, the FDA announced the launch of Open FDA, a website that makes data on adverse drug effects easily available to the public. And the GovLab at NYU, where I serve as senior advisor, released a new study on the potential power of open data from the UK’s National Health Service.

Medicare has released more data in the last 5 years than the first 50.

The Centers for Medicare and Medicaid Services made headlines recently when they released records of Medicare billing that named the doctors involved, but that was only part of a larger program to make more and more of their data public. As one speaker noted on the Datapalooza’s first day, “Medicare has released more data in the last 5 years than they did in the first 50.” New data is leading to new insights and new opportunities. Todd Park, U.S. Chief Technology Officer and the man who launched the Health Datapaloozas, said that open health data can now help create “A fundamental shift in how we pay for health care focused on value, not on volume.”

To begin with, Open Data is helping us understand the current state of healthcare – and is showing that healthcare quality and cost are virtually unrelated today. Dr. Elliott Fisher, Director of the Dartmouth Institute for Health Policy & Clinical Practice, described how research is showing that there are more than twofold differences in per capita Medicare spending in different parts of the U.S., and no evidence that areas that spend more are delivering better care as measured by mortality rates. “There is no relationship between quality and spending,” he said simply. But with better data, used analytically, “There’s a huge opportunity to both reduce  costs and improve care.”

There is no relationship between quality and spending in healthcare.

In another keynote address, Dr. Atul Gawande – the multitalented surgeon, author, and director of Ariadne Labs – echoed the need to use data to bring care, costs, and quality in sync. “Understanding the sickest,” Gawande said,” is how we fix our healthcare system.” It’s often noted that the sickest people in the system, not surprisingly, add the most to the cost of healthcare. But Gawande offered insight into why that’s so. Much of the problem, he said, is that our healthcare system is not geared to treat people with chronic illness, and as a result they receive inefficient care and expensive care. One patient he described, for example, kept going to the ER for migraines, until a simple analysis of her patient records showed that she was on the wrong medication. With more healthcare data and analysis, he argued, it will be easier to find dysfunctional patterns of care and get the sickest patients the care they need.

Another keynoter, Vinod Khosla, went farther with a bold prediction: Over the next decade or two, he said, “Data science will do more for medicine than all the biological sciences combined.” But for that to happen, we’ll have to be willing to use data and data science in ways that will change the role of doctors. Khosla, who was the founding CEO of Sun Microsystems, has a challenging vision for medicine’s future.

The problem he hopes to help solve is undeniable: 210 thousand people die in the U.S. each year from preventable medical errors. “The error rate in medicine,” said Khosla, “is the same as if Google was allowed to have a driverless car that had one accident a week.” Human doctors are not computers, and Khosla argues that computer are better at avoiding not just obvious errors but more subtle ones: They’re better at analyzing data to predict the likely benefit that a particular procedure or treatment will have on the health of a specific patient with a specific medical history.

The error rate in medicine is the same as if a Google car was allowed to have one accident a week.

After 10 or 20 years of training by expert doctors, Khosla believes that computers will help us move from “the practice of medicine” to “the science of medicine.” The doctor’s role will shift from an analytic one to a more human, and humane, role of helping patients make choices and use the medical care that’s available to them.

While this vision is still in the future – and still debatable – a number of companies are now using open data to improve healthcare and individual health. I’ll cover them in my next post.

- Joel Gurin, Founder and Editor,

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