Diagnosing with Data

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’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.

Critical to implementation of the systems is overcoming concerns about security and patient privacy. In addition to enforcing “military-level security” on patient data, says de Groen, clinicians “have to make people understand that there are tons of benefits in having their information available.” And, he adds, policymakers must ensure that such medical information cannot be hijacked or used to deprive patients of insurance or other services. Currently, use of the Mayo database is restricted to project coordinators. But starting in January 2004, password-protected access will gradually be granted to Mayo doctors who file protocols that demonstrate a need to use the data in their research. Longer-term plans call for the database to be accessible to any doctor with a patient waiting in his or her office.

Ultimately, after the technical and social issues have been resolved, collaborations between infotech companies and clinicians will mean widespread improvements in patient care. “It might take a decade, but information will transform medicine for the ordinary Joe on the street,” says IBM’s Kovac. If she’s right, a quick database search might become a standard part of any medical checkup.