Detection of Opioid over Prescription

Business Goals

Detect and prevent overprescription of opioids.

Challenge

• The usage of opioids is associated with severe risks. These risks include misuse, addiction, overdoses, and death.
• According to the US Centers for Disease Control and Prevention (CDC): ”The number of drug overdose deaths increased by nearly 5% from 2018 to 2019 and has quadrupled since 1999. Over 70% of the 70,630 deaths in 2019 involved an opioid.”
• Detect doctors that are overprescribing opioids.
• Detect patients that are taking addictive substances on demand rather than genuine need.

Results

The service detected 367 cases of opioid overprescription in the sample of nearly 500 care settings and 12 200 people under the study. The cases are under closer scrutiny now.

Implementation Details

• Years of medical prescriptions history and a stack of machine learning tools for anomaly detection were used to detect doctors that prescribed and patients that got excessive amounts of opioids.
• Then, the detected cases of opioid misuse were analyzed by a team of experts. Such factors as patient age, gender, route of administration, dosage form, location, etc. were taken into account. As a result, the system of post-filtering for the anomaly detection algorithm was designed.
• The anomaly detection model and guard rails bearing domain knowledge produced an effective tandem allowing reliable detecting and preventing cases of opioid misuse.