Key Takeaways
- 97% of adolescents who receive treatment for substance use disorders in specialty programs begin with an intake assessment that evaluates substance use severity and related risk factors
- 1.2% of adults reported using methamphetamine in the past year in 2023 (NSDUH)
- 2.1 million naloxone kits were dispensed via community programs in 2021 (kits dispensed)
- 10.1% of respondents in a national survey reported receiving naloxone in the past year (2019-2022 combined estimate)
- 81,806 drug overdose deaths occurred in the United States in 2020
- 1 in 10 U.S. adults reported past-month alcohol misuse in 2022
- 1.5% of U.S. adults had a past-year stimulant use disorder in 2022
- $46.2 billion in 2022 was the estimated cost of drug overdoses in the U.S. (healthcare and lost productivity)
- $14.6 billion in 2019 federal spending was associated with substance use disorder treatment and prevention programs (US federal estimate)
- $1.0 billion estimated cost of opioid use disorder-related ER visits in 2017 (US estimate)
- 1.7 million opioid prescriptions were dispensed per day on average in 2019 (prescribing volume metric)
- 2.5x higher odds of receiving MOUD among patients who accessed PDMP-linked care coordination programs (study estimate)
- 1.7 million people misused prescription opioids for the first time in 2022 (NSDUH incident estimate)
- 92% of U.S. public opioid treatment programs use medication-assisted treatment (MAT) as part of routine care models (program adoption estimate)
- 2,916 opioid treatment programs were certified to dispense methadone in the U.S. in 2023
U.S. overdose and substance use burdens remain high, highlighting rapid access to assessment and medication, plus naloxone.
Related reading
Treatment Demand
Treatment Demand Interpretation
Prevention & Harm Reduction
Prevention & Harm Reduction Interpretation
Mortality & Morbidity
Mortality & Morbidity Interpretation
Economic Impact
Economic Impact Interpretation
Prescription & Monitoring
Prescription & Monitoring Interpretation
Program Capacity
Program Capacity Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Rachel Svensson. (2026, February 13). National Center For Drug Abuse Statistics. Gitnux. https://gitnux.org/national-center-for-drug-abuse-statistics
Rachel Svensson. "National Center For Drug Abuse Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/national-center-for-drug-abuse-statistics.
Rachel Svensson. 2026. "National Center For Drug Abuse Statistics." Gitnux. https://gitnux.org/national-center-for-drug-abuse-statistics.
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