Comparative Analysis of Patient Distress in Opioid Treatment Programs using Natural Language Processing
Fatemeh Shah-Mohammadi1, Wanting Cui1, Keren Bachi1
1Icahn School of Medicine at Mount Sinai, New York, NY, U.S.A.
Abstract:
Psychiatric and medical disorders, social and family environment, and legal distress are important determinants of distress that impact the effectiveness of the treatment in opioid treatment program (OTP). This information is not routinely captured in electronic health record, but may be found in clinical notes. This study aims to explore the feasibility and effectiveness of natural language processing (NLP) strategy for identifying legal, social, mental and medical determinates of distress along with emotional pain rooted in family environment from clinical narratives of patients with opioid addiction, and then using this information to find its impact on OTP outcomes. Analysis in this study showed that mental and legal distress significantly impact the result of the treatment in OTP.
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