Responding to the US opioid crisis: leveraging analytics to support decision making

Area of Science:

• Public Health
• Epidemiology
• Health Policy Analysis

Background:

• The United States faces a severe opioid epidemic, with over 80,000 overdose deaths in 2022.
• Opioid use disorder (OUD) significantly contributes to morbidity, economic losses, and social disruption.

Purpose of the Study:

• To highlight opportunities for using analytics to inform policy decisions for the opioid crisis.
• To outline modeling approaches for understanding OUD and evaluating interventions.

Main Methods:

• Descriptive and predictive modeling of OUD prevalence, incidence, and risk factors.
• Analysis of policy effectiveness for OUD prevention, treatment, and harm reduction.
• Evaluation of regulatory and criminal justice system reforms.

Main Results:

• Analytics can provide insights into geographic and demographic variations in OUD.
• Modeling can assess the impact of various policies on OUD rates and overdose deaths.
• Data-driven approaches can inform strategies for mitigating social determinants of OUD.

Conclusions:

• Leveraging analytics is crucial for developing effective, evidence-based policies to address the opioid epidemic.
• Comprehensive modeling can support targeted interventions and resource allocation.
• Analytics can guide reforms to reduce the burden of OUD on individuals and society.