Opioid use disorder (OUD) affects an estimated 16 million people worldwide. The diagnosis of OUD is commonly delayed or missed altogether.
Opioid addiction is characterized by a powerful, compulsive urge to use opioid drugs, even when they are no longer required medically. Opioids have a high potential for causing addiction in some people, even when the medications are prescribed appropriately and taken as directed.
In a new study, scientists aimed to test the utility of machine learning in creating a prediction model and algorithm for the early diagnosis of OUD.
To generate the model, scientists analyzed data gathered in a commercial claim database from January 1, 2006, to December 31, 2018, of 10 million medical insurance claims from 550 000 patient records. It relied on data such as demographics, chronic conditions, diagnoses and procedures, and medication prescriptions.
Journal Reference:
- Zvi Segal et al. Development of a machine learning algorithm for early detection of opioid use disorder. DOI: 10.1002/prp2.669