Fighting the Opioid Crisis Through Artificial Intelligence and Machine Learning

In the United States, an average of 135 people die per day as a result of opioid-induced overdose, according to the National Institute on Drug Abuse. A November 2017 report issued by the Council of Economic Advisers estimates that the total economic cost of the opioid crisis was $504 billion in 2015. This likely underestimates the total cost, given the difficulty of quantifying social impact on people suffering from opioid use disorder, as well as the financial hardships of family members and communities affected by addiction and fatal overdose. The opioid epidemic is a national health crisis that requires intervention by state, local, and national policymakers. To reduce the prevalence of opioid-induced mortality, stakeholders need access to more opportune data that will drive evidence-based policy recommendations and patient-centric treatment pathways.