Key Takeaways
- 72% of ambulance crashes in the US from 2005-2015 were attributed to driver error such as speeding
- Intersection-related crashes account for 42% of all ambulance collisions nationwide 2017-2021
- Lights and sirens use increases crash risk by 3.6 times per Clawson et al. study 2012
- US ambulance crashes resulted in 300 fatalities annually average 2015-2020
- 22% of EMS crash deaths are ambulance crew members
- Patients die in 15% of fatal ambulance crashes per CDC 2018
- In 2019, the US recorded 62,000 ambulance crashes, with 57% occurring while responding to calls under lights and sirens
- From 2010-2019, ambulances in the US had a crash rate of 5.8 per 100,000 miles driven, higher than police vehicles at 4.2
- In New York State 2021, 1,247 ambulance crashes were reported, a 12% rise from 2020
- 45,000 non-fatal injuries to EMS personnel from crashes 2010-2020
- Patients injured in 60% of ambulance crashes, avg 2.3 per incident
- Back injuries most common EMS crew injury at 32% in crashes
- 75% injury reduction with advanced restraint systems in ambulances
- Driver training programs reduce EMS crash rates by 23%, per NAEMT study 2021
- Lights/sirens restriction policies cut crashes 30% in Salt Lake City trial
Most ambulance crashes are driven by human error, especially speeding, lights and sirens, and intersection risks.
Related reading
Crash Causes
Crash Causes Interpretation
More related reading
Fatality Statistics
Fatality Statistics Interpretation
More related reading
Incidence Rates
Incidence Rates Interpretation
More related reading
Injury Data
Injury Data Interpretation
More related reading
Safety Interventions
Safety Interventions 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.
Felix Zimmermann. (2026, February 13). Ambulance Crash Statistics. Gitnux. https://gitnux.org/ambulance-crash-statistics
Felix Zimmermann. "Ambulance Crash Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ambulance-crash-statistics.
Felix Zimmermann. 2026. "Ambulance Crash Statistics." Gitnux. https://gitnux.org/ambulance-crash-statistics.
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