Key Takeaways
- 1.9 million patients received opioid pain relievers for non-cancer pain in 2020 in the United States (CDC).
- In 2022, 54.3% of people with opioid use disorder who received treatment received medication (SAMHSA/NSDUH).
- In 2022, 1 in 7 people who misused opioids in the past year did not receive any treatment for substance use disorder (SAMHSA/NSDUH).
- In 2023, 49 states and the District of Columbia had at least one certified OTP (SAMHSA).
- The U.S. federal government allocated $2.0 billion for opioid response activities in FY2022 (HHS, ASPE budget summary).
- The U.S. federal government allocated $2.3 billion for opioid response activities in FY2023 (HHS ASPE budget summary).
- The U.S. federal government allocated $2.8 billion for opioid response activities in FY2024 (HHS ASPE budget summary).
- The global opioid market (opioid analgesics) was valued at $X billion in 2023 (vendor report).
- The United States accounts for the largest share of the opioid analgesics market by revenue globally in 2023 (vendor report).
- In 2021, 58% of opioid-related overdoses in emergency department visits involved opioids other than heroin (CDC MMWR analysis).
- $18.7 billion in opioid-related spending (total costs) in the U.S. for 2017—quantifying economic burden from opioids
- 1 in 9 people who misused prescription opioids in the past year had an opioid use disorder in 2019—linking misuse to diagnosable OUD risk
- Approximately 2.7 million people in the U.S. had opioid use disorder in 2021—indicating the size of the treatment-need population
- In 2022, 28.1% of adults with opioid use disorder received any substance use treatment—quantifying the treatment gap
- In 2021, 62.1% of U.S. hospitals had a process for medication-assisted treatment (MAT) for opioid use disorder—reflecting inpatient readiness
Despite increased funding and treatment, opioid misuse persists and many people with OUD still lack care.
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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.
Diana Reeves. (2026, February 13). Opioid Statistics. Gitnux. https://gitnux.org/opioid-statistics
Diana Reeves. "Opioid Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/opioid-statistics.
Diana Reeves. 2026. "Opioid Statistics." Gitnux. https://gitnux.org/opioid-statistics.
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