About 85% of patients with opioid use disorder are described in clinical notes as being abusers, addicts, junkies, or with other stigmatizing terms, preliminary results of a new study suggest.
"No matter what type of specialty you're in, and no matter if you're a male or female clinician, you should choose your words carefully," study investigator Jyotishman Pathak, PhD, professor of psychiatry and of population health sciences, Weill Cornell Medicine, Cornell University, New York, toldIn physician-patient encounters, especially with patients of lower socioeconomic status or less education,"there's already a power dynamic going on," Pathak added.
About 85% of patients with OUD/SUD had stigmatized language terms in 111,422 notes. The most common negative terms included abuser, addict,Individuals in the SL group tended to be older, and there were more people in the SL group than in the No SL group in each age category from ages 33 to 80 years.
"Patients are already very vulnerable, and you would expect that the language being used would have more empathy," he said. The aim is to develop AI tools that help clinicians document clinical notes appropriately. This might involve an autocorrect feature that flags or corrects inappropriate language or prompts the user to change the wording, said Pathak.
Artificial Intelligence Deep Learning AI NPL Machine Learning ML Natural Language Processing Artificial Neural Networks Opioids Healthcare And Medical Technology Health And Medical Tech Health And Med Tech Health And Medical Technology Healthcare Technology Medical Technology Electronic Medical Record EMR Electronic Health Record EHR Computerized Medical Records Systems
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