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Urine drug tests may spot overdose risk earlier, Johns Hopkins study finds

Jun. 16, 2026
By AI, Created 04:01 UTC, Jun 16, 2026, AGP -

A Johns Hopkins-led study with Millennium Health says urine drug testing data can flag regional shifts in fentanyl exposure before fatal overdose numbers fully catch up. The findings suggest near-real-time lab data could help public health officials respond faster to changes in the illicit opioid supply.

Why it matters: - Synthetic opioid overdoses accounted for more than 68% of all fatal drug overdoses in 2024. - Faster surveillance could help public health officials, clinicians and policymakers spot emerging hotspots sooner. - Urine drug testing data may reveal changes in drug potency and composition before mortality data is fully reported.

What happened: - Researchers led by Andrew Huhn, PhD, MBA, an associate professor of psychiatry and behavioral sciences at Johns Hopkins University School of Medicine, published new findings in Drug and Alcohol Dependence. - The study was co-authored by Millennium Health researchers. - The team analyzed more than 2.1 million urine drug testing specimens from over 575,000 patients collected between 2019 and 2025. - The analysis focused on fentanyl concentration and fentanyl detection rates in urine drug testing data. - The researchers compared those measures with synthetic opioid overdose death data across the Northeast, Midwest, South and West.

The details: - Fentanyl detection rates in urine testing rose 104%, and fentanyl concentrations rose 333% during the study period as fentanyl-related overdose deaths increased 94% nationally from 2019 to 2023. - In 2024, fentanyl detection rates fell 25% and concentrations fell 28% in urine testing. - Those declines mirrored reported drops in fentanyl purity from the Drug Enforcement Administration and falling fentanyl-related deaths. - Heroin detection in specimens that were positive for fentanyl increased across the U.S. while fentanyl concentrations declined. - The shift was most pronounced in the West, suggesting more adulteration of the illicit fentanyl supply with heroin to offset weaker fentanyl. - Strong regional differences appeared across the country. - The West showed the highest fentanyl concentrations and the strongest correlation between fentanyl concentration and overdose deaths. - The South, Midwest and Northeast showed stronger relationships between fentanyl detection rates and overdose deaths. - Forecasting models built from urine drug testing data closely tracked monthly fentanyl overdose deaths. - The study described urine drug testing as providing near-real-time insight into drug use and exposure trends.

Between the lines: - The study points to a surveillance gap in overdose response: mortality data can lag while the drug supply changes quickly. - Near-real-time lab testing could give authorities earlier warning when fentanyl becomes more or less potent, or when dealers change what is in the supply. - The regional differences suggest that overdose surveillance may need to be tailored, not treated as a single national pattern. - Angela Huskey, PharmD, CPE, Millennium Health’s chief clinical officer, said UDT data can help minimize the lag between overdose reporting and current trends, giving public health officials earlier visibility into changes. - Eric Dawson, PharmD, Millennium Health’s vice president of clinical affairs, said the findings highlight urine drug testing as a real-time surveillance tool for the illicit opioid supply.

What's next: - Public health agencies and clinicians could use urine drug testing trends to identify emerging hotspots and respond with targeted prevention and treatment efforts. - The study suggests forecasting models based on urine drug testing data may help monitor monthly overdose patterns as the drug supply continues to shift. - Millennium Health says its monitoring capabilities can alert clinicians, health agencies and others to real-time drug use changes to inform overdose prevention strategies.

Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.

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