Source: NYTimes, Dec 2012
Just how special is Dr. Dhaliwal’s talent? More to the point, what can he do that a computer cannot? Will a computer ever successfully stand in for a skill that is based not simply on a vast fund of knowledge but also on more intangible factors like intuition?
I.B.M., on the heels of its triumph last year with Watson, the Jeopardy-playing computer, is working on Watson for Healthcare.
In some ways, Dr. Dhaliwal’s diagnostic method is similar to that of another I.B.M. project: the Deep Blue chess program, which in 1996 trounced Garry Kasparov, the world’s best player at the time, to claim an unambiguous victory in the computer’s relentless march into the human domain.
Although lacking consciousness and a human’s intuition, Deep Blue had millions of moves memorized and could analyze as many each second. Dr. Dhaliwal does the diagnostic equivalent, though at human speed.
While computers are good at crunching numbers, people are naturally good at matching patterns. To make a decision, physicians must combine logic and knowledge with their pattern-matching instincts.
Thousands of diseases are known, and many are rare. “Low-frequency events are hard to put on the brain’s palette, and that’s part of Isabel’s strength,” Mr. Maude said. “It’s impossible for any one person to remember how each of those diseases presents, because each presents with a different pattern.”
He added that Isabel was aimed not so much at the Dr. Dhaliwals of the world, but at more typical physicians.
Dr. David J. Brailer, chief executive of Health Evolution Partners, which invests in health care companies, agreed. “If everyone was a diagnostic genius, we wouldn’t need these decision support tools,” he said.
Diagnostic mistakes account for about 15 percent of errors that result in harm to patients, according to the Institute of Medicine. Yet diagnostic software has been slow to make its way into clinical settings, and Dr. Dhaliwal, who uses Isabel as a “second check,” said he could understand why.
Not only is it hard to integrate software into an already busy daily work flow, he said, but “most of us don’t think we need help at diagnosis, especially with routine cases, which account for the majority of our work.”
Dr. Henry Lowe, an internist at Stanford University and director of its Center for Clinical Informatics, doubts that a computer could ever replace a diagnostic wizard like Dr. Dhaliwal, or even a competent clinician.
“Designing computer systems that work well with incomplete or imprecise information is challenging,” Dr. Lowe said. “Particularly in medicine, where the consequences of defective decision-making may be catastrophic.”
Mimicking Human Analysis
I.B.M.’s Watson for Healthcare has yet to focus directly on diagnosis. The company is working with Memorial Sloan-Kettering Cancer Center to teach Watson to interpret clinical information and, eventually, help determine treatment. I.B.M. also recently began a collaboration with Cleveland Clinic to broaden Watson’s analytical capabilities into the area of medicine.
Dr. Martin Kohn, chief medical scientist for I.B.M. Research, is careful to point out that Watson for Healthcare is intended to be “neither omniscient nor omnipotent.” Yet, Dr. Kohn noted, most physicians set aside five hours or less each month to read medical literature, while Watson can analyze the equivalent of thousands of textbooks every second. The program relies heavily on natural language processing. It can understand the nature of a question and review large amounts of information, such as a patient’s electronic medical record, textbooks and journal articles, then offer a list of suggestions with a confidence level assigned to each.
For physicians, Dr. Kohn said, one problem is what he calls “the law of availability.”
“You aren’t going to put anything on a list that you don’t think is relevant, or didn’t know to think of,” he said. “And that could limit your chances of getting a correct diagnosis.”
Dr. Dhaliwal agreed, citing the recent outbreak of hantavirus at Yosemite. Ten people contracted the virus, and three died. “It’s a febrile illness that looks like the flu,” he said. “It’s so rare, the last time you might have seen it was your medical school classroom.”
Had Isabel or a similar program been used, the deaths might have been prevented, Dr. Dhaliwal said. “You might think you’re in familiar territory, but the computer is here to remind you there are other things.”