arcos (R) and arcospy (Python): twin software packages to access the DEA ARCOS database from 2006 to 2014

The ongoing Opioid Crisis in the United States poses serious public health issues. Understanding how the United States arrived at the present crisis is crucial to avoid future crises. One powerful tool for understanding trends in prescription opioid distribution is the Drug Enforcement Administration's (DEA) Automation of Reports and Consolidated Orders System (ARCOS). Recent litigation efforts by The Washington Post and HD Media have allowed for a substantial anonymized portion of the ARCOS database to be made available for public use. However, in raw format the available portion of the ARCOS database is more than 150 gigabytes and includes several hundred columns. Thus, the software arcos (in R) and arcospy (in Python) are meant to simplify access to the available data so researchers and interested citizens can rapidly gather relevant measures of prescription opioid distribution. The data available in arcos and arcospy spans the years 2006 to 2014. These are the years leading up to the now widely recognized Opioid Crisis. The data has been featured in a series of investigative reporting articles by both national and regional newspapers. There are numerous potential applications of this data to the study of health sciences, criminology, medical sociology, and more.

An article submitted to The Journal of Open Source Software (JOSS) explaining this software is available here. Useful vignettes demonstrating the software's functionality are available in both R and Python.