Healthcare // Electronic Health Records
06:08 PM
Paul Cerrato
Paul Cerrato
Connect Directly
Repost This

7 Big Data Solutions Try To Reshape Healthcare

Big data medicine is still largely unproven, but that's not stopping several medical centers and analytics vendors from jumping in with both feet.
7 of 8

During a recent Digital Health Conference sponsored by the New York eHealth Collaborative, Martin Kohn, M.D., chief medical scientist at IBM, and Pat Skarulis, CIO at Memorial Sloan-Kettering Cancer Center (MSKCC) in New York, outlined a joint venture to use the Watson supercomputer's big data capabilities to help oncologists provide better care for MSKCC patients.

Kohn pointed out that Watson isn't just a "search engine on steroids," or even a massive database. It relies on parallel probabilistic algorithms to analyze millions of pages of unstructured text in patient records and the medical literature to locate the most relevant answers to diagnostic and treatment-related questions.

Ninety percent of the world's data has been created in the last two years, and 80% of that data is unstructured. As any clinician with a pile of unread medical journals knows, that massive collection of information includes far too many papers for any one human to read.

Watson reads it for them at lightening fast speed.

With the help of natural language processing (NLP), the computer not only pulls out relevant terms to match the search terms in a clinician's query, but it also understands the idioms and other idiosyncratic expressions in the English language. And with the help of temporal, statistical paraphrasing and geospatial algorithms, it finds meaningful relationships between the clinician's question and its massive collection of medical facts and theories.

MSKCC decided to collaborate with IBM to "build an intelligence engine to provide specific diagnostic test and treatment recommendations," Skarulis said. The two organizations now are combining data from MSKCC's massive database, called Darwin, with all of Watson's NLP capabilities. IBM is using all of the medical center's structured patient data and its NLP tools to convert the medical center's free text consultation notes into usable data. Skarulis hopes to launch a pilot shortly that will allow the supercomputer to work on real medical cases.


Big Data Analytics: Where's The ROI?

Pediatric Cardiologists Turn to Clinical Analytics

13 Big Data Vendors To Watch In 2013

IBM Watson Finally Graduates Medical School

Healthcare Execs Must Prepare For Big Data

Think Small Data Before Big Data, Healthcare Gurus Argue

Pittsburgh Healthcare System Invests $100M In Big Data

7 of 8
Comment  | 
Print  | 
More Insights
Newest First  |  Oldest First  |  Threaded View
User Rank: Apprentice
1/3/2013 | 3:50:55 PM
re: 7 Big Data Solutions Try To Reshape Healthcare
During my interviews with Big Data vendors and medical centers, I did see some tangible results, but in some cases they were improvements in "intermediate endpoints," as medical researchers like to phrase it.

Improvements in blood glucose or serum cholesterol levels in patients whose data has been crunched is worthwhile, but it's not the same as documented evidence that the analysis reduced cardiac deaths or limb amputations. Those are the real endpoints we need to reach.
Paul Cerrato
InformationWeek Healthcare
Register for InformationWeek Newsletters
White Papers
Current Issue
Twitter Feed
Audio Interviews
Archived Audio Interviews
GE is a leader in combining connected devices and advanced analytics in pursuit of practical goals like less downtime, lower operating costs, and higher throughput. At GIO Power & Water, CIO Jim Fowler is part of the team exploring how to apply these techniques to some of the world's essential infrastructure, from power plants to water treatment systems. Join us, and bring your questions, as we talk about what's ahead.