"Fortunately, I survived that process long enough for them to come back with an answer in time. When you're talking about advanced cancer patients it's unacceptable for this to take months... even weeks can have deadly consequences," Dishman said.
Today's hospitals aren't set up to share electronic health data. While the federal government has required healthcare facilities to roll out electronic healthcare records, the technology to share data even within hospital groups is either non-existent or in the nascent stage. And, for oncology and other specialized medical care, sharing data is even more difficult, as it calls for specialists around the country to first find each other and then share data about specific cancer types.
The first human genome took 13 years and $3 billion to produce. Today, geneticists can generate the same information in hours and for under $1,000.
But genomic data is still massive in size -- a terabyte or more of information.
"With less than 2% of cancer patients in the world being sequenced, it's already an incredibly difficult prospect to actually share the data," Druker said.
The Collaborative Cancer Cloud works by allowing physicians to send out secure electronic queries to other healthcare facilities seeking patients with cancers and genomics similar to their own patients. Once a match is discovered, all electronic patient data is made anonymous before the data is analyzed.
"The moment an answer is given back through the secure container, the virtual machine disappears and all the data used to come up with an answer to the query disappears," Dishman said. "So it's not like the cancer center in Texas can peer into raw cancer data at OHSU."
OHSU has plans to go live in the first quarter of 2016 with two other cancer centers to pilot the Collaborative Cancer Cloud technology. If successful, the plan is to then wrangle more healthcare centers into the network to share the collaborative technology.
"We hope dozens, if not hundreds of cancer centers will use ours or use the open-sourced technology to make their own data sharing platforms," Dishman said. "At the end of the day, we want to at least remove barriers that are keeping precision healthcare from scaling."
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