While Watson certainly impressed the nation with its sweeping victory on the game show Jeopardy last week, the medical community -- which IBM hopes will be first to use the technology -- may eventually become even more impressed with its affordability.
After showcasing Watson's ability to ingest Jeopardy questions and spit out near real-time answers, IBM is now preparing the supercomputer for a full-time gig as a data analytics engine for the medical community.
IBM announced this week it is working with speech and imaging recognition software provider Nuance Communications to produce a system that can help physicians and other healthcare professionals cull through gigabytes or terabytes of patient healthcare information to determine how to best treat illnesses.
"Combining our analytics expertise with the experience and technology of Nuance, we can transform the way that healthcare professionals accomplish everyday tasks by enabling them to work smarter and more efficiently," said John E. Kelly III, senior vice president and director of IBM Research. "This initiative demonstrates how we plan to apply Watson's capabilities into new areas, such as healthcare with Nuance."
For example, a doctor treating a patient could use Watson's analytics technology, in conjunction with Nuance's voice and clinical language understanding software, to rapidly consider all the related texts, reference materials, prior cases, and latest knowledge in journals and medical literature. This could help medical professionals confidently determine the best options for diagnosis and treatment.
IBM is working with Dr. Eliot Siegel, professor and vice chairman of the University of Maryland School of Medicine's department of diagnostic radiology, to bring that Watson project to fruition in the healthcare industry.
Siegel told Computerworld that patient information tends to be written in free form by physicians, who use abbreviations and short-text explanations. So it could take well over 10 minutes to an hour for another physician, radiologist or specialist to understand the intricacies of a patient's malady.
Now multiply one person's medical record by the thousands that a hospital or medical group might have, and the difficulty in finding best practices from healthcare trends becomes even more daunting.
IBM hopes that in about two years, Watson can be tweaked and go commercial to help hospitals and physicians take data from electronic health records (EHRs) and churn it into predictive modeling to determine the most likely outcomes from various treatments.
While there are many hurdles to achieving that goal -- such as the continuing lack of widespread EHR deployment -- Watson could one day save untold dollars and lives, IBM hopes.
Cost shouldn't be a significant factor as Watson is relatively cheap compared to medical technology routinely purchased by healthcare organizations.
The Watson supercomputer that appeared on Jeopardy last week was made up of 90 IBM Power 750 Express servers powered by 8-core processors -- four in each machine for a total of 32 processors per machine. The servers are virtualized using a Kernel-based Virtual Machine (KVM) implementation, creating a server cluster with a total processing capacity of 80 teraflops. A teraflop is one trillion operations per second.
According to Tony Pearson, master inventor and senior consultant at IBM, a Power 750 server retails for $34,500. Thus the 90 that make up Watson would cost about $3 million.
"That's not bad. You're going to spend $3 million on an MRI machine," Pearson said. "If you look at how expensive hospital equipment is, cost is not the issue."
A hospital, or even physician's office, doesn't necessarily have to buy the full clustered Watson computer system. The original compute algorithm single threaded on a single core processor took two hours to scan memory and produce an answer to a question. IBM technologists just added 2,880 CPUs, which produced the ability to answer the Jeopardy questions in three-seconds.
If a hospital or physician is willing to wait 30 seconds for an answer, then you'd only need one-tenth of that compute power or nine machines.
"So you're in the $300,000 range," Pearson said. "It's quite possible [to wait two hours] if you run it on your Power 750 at home. I'd bet there are some people who'd say, 'heck, I can't even get my doctor to call me back in two hours.' I think it's reasonable that larger hospital systems will have the bigger machines and smaller hospitals might settle for waiting a little longer for an answer."
"Watson seems amazing, but I'm not sure how it can take all that unstructured data and process it," said Marc Probst, CIO of Intermountain Healthcare in Salt Lake City, which services close to half the population of Utah.
Probst said he's skeptical because Watson's structured database is very dissimilar to the unstructured data in an EHR format.
"I don't know how well Watson works with Nuance, but there's so much detailed data in healthcare," Probst said. "It's known that the human mind can process 7 to 9 data items and consistently. The average clinical decision application uses over 40 data items to make a decision. So, there's much more data involved."
Last week, Intermountain Healthcare opened a 10,000-square-foot informatics research center supported by two data centers. Intermountain's Homer Warner Center for Informatics Research staffs 65 physicians and PhDs charged with providing decision support functions to clinicians, as well as provide input on the best possible care options.
For example, several years ago the Journal of the American Medical Association (JAMA) published the findings of a study that showed a correlation between the number of babies that wind up on ventilators in neonatal intensive care units (NIC) and at what point physicians induced labor.
"Using the practices and technologies in place at the Homer-Warner Center, we were able to change behavior. It had a dramatic impact on the health of babies," he said. "We were at about 30% of births induced prior to 39 weeks." Now, he said, "about 3%" are induced that early.
Probst said reducing the number of babies in NIC units saves "millions and millions" of dollars per hospital in his system. "We've got hundreds of such examples," he said.
Lucas Mearian covers storage, disaster recovery and business continuity, financial services infrastructure and healthcare IT for Computerworld. Follow Lucas on Twitter at Twitter@lucasmearian.