The New York Times reports on the issue of data mining electronic medical records and the privacy issues that can arise:
Over the past decade, nudged by new federal regulations, hospitals and medical offices around the country have been converting scribbled doctors’ notes to electronic records. Although the chief goal has been to improve efficiency and cut costs, a disappointing report published last week by the RAND Corp. found that electronic health records actually may be raising the nation’s medical bills.
But the report neglected one powerful incentive for the switch to electronic records: the resulting databases of clinical information are gold mines for medical research. The monitoring and analysis of electronic medical records, some scientists say, have the potential to make every patient a participant in a vast, ongoing clinical trial, pinpointing treatments and side effects that would be hard to discern from anecdotal case reports or expensive clinical trials. [...]
But the challenges posed by this sort of research are significant. The information entered into a medical record may be wrong, and diagnostic codes are notoriously unreliable, according to [Nicholas Tatonetti, assistant professor of biomedical informatics at Columbia,] partly because they are also used for billing. And doctors don’t think like researchers. [...]
Perhaps the most pressing issue is patient privacy. Electronic health records must be “de-identified” before they can be used for research. That requires more than simply removing a name. Any information that might identify the patient must be excised. At the same time, researchers have to be able to tell when they’re looking at records from the same patient, which may be stored in several databases.
“One patient may be in as many as 20 different databases,” said Dr. William S. Dalton, founding director of the Personalized Medicine Institute at Moffitt Cancer Center, which is currently tracking more than 90,000 patients at 18 different sites around the country. Moffitt combines information from the electronic medical record with data from X-rays and other imaging studies, tumor tissue cultures and even genetic profiles.
“There’s an immense amount of information and different databases, all using different data dictionaries,” Dr. Dalton said. “And they don’t all agree.”
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