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Even a top-notch specialist like Piet de Groen, a gastroenterologist at the Mayo Clinic in Rochester, MN, can’t know everything about every illness his patients may suffer. But on the rare occasions that he encounters an ailment he’s never seen before, chances are another physician at the hospital has. So de Groen is developing an electronic “data warehouse” that allows him to type in a patient’s symptoms and-within seconds-get a list of all similar Mayo patient records. By 2004, after initial data security and patient confidentiality issues have been resolved, de Groen and his colleagues will be able to use these histories to make more accurate diagnoses. In the long term, they could even access your genetic profile to help choose a course of treatment.

The Mayo system is being built with the collaboration of IBM Life Sciences in Rochester and in Yorktown Heights, NY. Started in the winter of 2002, the project has already produced a large database of medical records and software that can find groups of patients with similar conditions and treatments. While hospitals and HMOs are increasingly using electronic records to track patient histories, the Mayo system goes further. It automatically groups patients according to the factors they have in common, allowing doctors to search quickly for combinations of factors. It will be used first for medical research but ultimately to improve patient care. “The application of information technology and bioinformatics is moving toward medicine and patient care much more rapidly than anyone anticipated,” says Carol Kovac, general manager of IBM Life Sciences.

The Mayo’s data warehouse contains 4.4 million patient histories recorded over the past five years. Doctors can search these records by symptoms, age, patient’s home state, date of diagnosis, and other factors; in 2004, drug information will become available as well. Because the records are already clustered according to common characteristics, searches can zero in on the most likely matches, instead of poring through the entire database patient by patient. When a new patient’s information is entered, software automatically compares it with existing patterns and groups it accordingly. The result: the system could eventually operate fast enough to be used during a visit to the doctor’s office. So the doctor might, for example, check how older female patients with a specific set of symptoms respond to a particular drug.

But doctors and patients want more. They want to know why drug therapies work for some but not others; which people are more susceptible to cancer; and ultimately, what the best treatment is for each individual. For these kinds of queries, clinicians need access to genetic information, such as that gleaned from microarrays that provide snapshots of the activity levels of thousands of genes. “Using genomics to affect the way medicine is done, and making a secure repository of information that doctors can access-these avenues will converge,” says Gustavo Stolovitsky, a computational biologist at IBM.

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