Evani Dalal
Pronouns: she/her
Research Mentor(s): John Kloosterman
Co-Presenter: Gao, Oliver
Research Mentor School/College/Department: EECS – CSE / Engineering
Presentation Date: April 20
Presentation Type: Poster
Session: Session 3 – 1:40pm – 2:30 pm
Room: League Ballroom
Authors: Evani Dalal, Oliver Gao, John Kloosterman
Presenter: 49
Abstract
The opioid crisis in the United States began in the late 1990s as healthcare providers began prescribing opioid pain relievers at greater rates after pharmaceutical companies claimed that these pills were not addictive. Millions of people have since suffered from opioid overdose and substance use disorders. In this research project, we seek to make sense of a huge dataset detailing every shipment of opioid pills to US pharmacies from 2006 to 2014 in order to discover patterns associated with opioid pill distribution. The dataset used in this project was obtained by The Washington Post from the U.S. Drug Enforcement Administration. In order to get more insight on the impact of the opioid crisis, we created data visualizations in Python. We found an increase in the distribution of opioid pills from 2006 to 2012 in Michigan and examined the various patterns in the dataset that correlated with the increase in pill distribution, including individual pharmacy shipments, county populations, and different pill types. Our findings and data visualizations help advance our understanding of the opioid crisis as an issue connected to geography, demographics, and policy, impacting different regions of Michigan.
Engineering
