Opioid Data Lab

At the Opioid Data Lab we create tools to advance drug safety science. Our mission is to create open source epidemiology tools to automate tedious data processing. Our studies encompass Theory, Practice and Lived Experience. We use modern health surveillance and causal inference methods to evaluate opioid analgesics and heroin, with a focus on abuse deterrent formulations (ADFs). Housed at the University of North Carolina at Chapel Hill, the University of Kentucky in Lexington and the University of Florida, we collaborate with pain patients and people who use drugs to answer questions with real life implications. Every day, our scientists analyze datasets representing the experience of tens of millions of individuals. We study pain management practices, harm reduction, addiction treatment, and overdose prevention.

We show our work to share our work. Each study in at the Opioid Data LabĀ  publishes lab notebooks that clearly identify funders, hypotheses, methods, results and data visualizations.

Notebooks
We use Jupyter Notebooks to show each step of the discovery process. From raw data to conclusions, these notebooks allow others to replicate or extend our work. Viewable from a web browser, you do not need to run statistical software to follow along.

Code
We post code on GitHub repositories in 4 programming languages: SAS, Stata, Python and R. Data scientists can edit, add to, or fork our code to create new research tools and data visualizations.

Open Science and Licenses
We invite anyone with an interest in reducing the harm from prescription opioids and heroin to use our tools and improve upon them. Each project is accompanied by a license and open science badge to make sharing and reuse rules explicit.

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