Estimate of mortality reduction with implementation of advanced automatic collision notification

Area of Science:

• Road Safety
• Automotive Technology
• Public Health

Background:

• Advanced Automatic Collision Notification (AACN) systems notify public safety answering points (PSAPs) of vehicle crashes.
• AACN provides injury prediction to aid dispatchers and first responders in critical decision-making.
• The goal is to expedite patient transport to definitive care, improving survival rates.

Purpose of the Study:

• Identify target populations benefiting from AACN.
• Estimate the potential number of lives saved by AACN implementation in the vehicle fleet.
• Quantify the safety benefits of earlier notification and optimized treatment destination.

Main Methods:

• Utilized Fatality Analysis Reporting System (FARS) and National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) data (2000-2015).
• Estimated target population benefits based on trauma center access and injury prediction accuracy.
• Calculated survival rate ratios using Kaplan-Meier estimator and proportional hazard models.

Main Results:

• Identified two key populations: 6893 fatalities benefit from earlier notification alone.
• 1495-2330 fatalities benefit from both earlier notification and transport to a trauma center.
• Estimated annual lives saved range from 360 to 721.

Conclusions:

• Full AACN implementation could save 360-721 lives annually, a 1.6%-3.3% fatality reduction.
• AACN doubles the lives saved compared to earlier notification alone.
• AACN is a vital postcrash safety technology for integrated vehicle safety systems.