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New Algorithm Uses Patient Data To Predict Future Health Conditions

Researchers have developed a new algorithm that uses patient data to make  predictions about an individual’s future health conditions, according to a paper published in the Annals of Applied  Statistics, Popular Science reports.

How It Works

Massachusetts Institute of Technology and Columbia University researchers  took data from a multiyear clinical drug trial involving tens of thousands of  patients age 40 and older. Patient information includes gender, ethnicity,  medical histories and prescriptions (Boyle, Popular Science, 6/5).

They then used the Hierarchical Association Rule Model to predict future  medical conditions based on combined data on various conditions from the larger  patient pool.

Tyler McCormick — assistant professor of statistics and sociology at the  University of Washington — said the statistical model “provides physicians with  insights on what might be coming next for a patient, based on experiences of  other patients.” For example, patients who already have dyspepsia and epigastric  pain could be more likely to develop heartburn, according to McCormick.

Access to Tool

McCormick said he intends to make the tool available to both doctors and  patients. He said, “We hope that this model will provide a more patient-centered  approach to medical care and to improve patient experiences” (Hall, FierceHealthIT, 6/6).

Source: iHealthBeat

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