U of A researchers test AI to measure risk of prescription opioids
The researchers looked at about three million opioid prescriptions a year from various medical professionals — doctors, nurse practitioners, dentists — to more than 600,000 patients in AlbertaStory continues below advertisement
“As a human, I can look at a couple of dozen variables and predict outcomes, but we’re finding that’s just not enough.” Eurich, who has been working on AI predictions for more than three years, said the system can “predict correctly four out of every five patients.” A patient identified as high-risk would have a higher chance of being hospitalized within the first 30 days of prescribing the drug, according to the machine.He added that AI-powered systems could also rapidly adapt to the changing environment — for instance, a sudden spike in opioid-related death during the pandemic.
Eurich said a “good portion” of poor outcomes related to opioids is not fuelled by street drugs, but by prescription use — particularly in the beginning.
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