Predicting Drug Diversion: The Use of Data Analytics in Prescription Drug Monitoring
The Student Journal of Information Privacy Law: A virtual student-led publication at the University of Maine School of Law
15 Pages Posted: 4 Jan 2022
Date Written: November 15, 2021
The leading narrative driving policy is that the opioid epidemic was driven by overprescribing by clinicians, leading patients to become addicted. This has led to draconian laws that have harmed chronic pain patients and use of invasive prescription monitoring programs throughout the country. The black box algorithms mine data and have never been subjected to independent verification. Patients and prescribers alike are flagged. Although prescribing has dropped dramatically since the introduction of prescription monitoring, overdose deaths have risen dramatically to record highs, driven by the illicit fentanyl market. Despite this, law enforcement continues to focus on diversion of prescription medication, data mining and raising privacy concerns.
Patients seek healthcare and consent for treatment. There is no consent for their protected health information to be given to the Department of Justice. Using administrative powers, the DEA is able to search databases. Private entities are gaining more and more access to this data as companies merge. George Orwell was prescient.
Funding Information: None to declare.
Declaration of Interests: None to declare.
Keywords: data analytics, privacy, algorithm, prescribing, DEA
JEL Classification: K4
Suggested Citation: Suggested Citation