Researchers at Children's Hospital Boston are touting their use of analytics to effectively predict potential adverse drug events.
Boston researchers use analytics to predict adverse drug events
According to a study that appeared online in Science Translational Medicine, members of the 396-bed hospital's informatics program created a mathematical model that relies on existing drug-safety data to make predictions about future instances of harm, including those that may take place years later.
"This approach allows us to make the important transition from detection to prediction," Ben Reis, head of the hospital informatics department's preventive medicine group and a co-author of the study, said in a news release. "We can potentially identify a dangerous drug side effect early on, instead of having to wait for sufficiently many patients to be affected by it in order to allow for detection."
Using only data available in 2005, the model successfully identified 42% of the drug-adverse event relationships that were later identified over the next five years, Children's Hospital Boston said in the release.
"Being able to predict a potential relationship that was not previously considered will improve the safety of drugs as they come to market, benefiting both drug companies and patients," Shannon Manzi, a pharmacist in the hospital’s emergency department and study co-author, said in the release.
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