Estimate of mortality reduction with implementation of advanced automatic collision notification. (29th May 2017)

• Record Type: Journal Article
• Authors: Lee, Ellen; Wu, Jingshu; Kang, Thomas; Craig, Matthew
• Is Part Of: Traffic injury prevention. Volume 18(2017)Supplement 1
• Page Start: S24
• Page End: S30
• Publication Date: 2017-05-29
• Subjects: Telematics -- injury prediction -- crash notification -- postcrash -- triage -- prehospital care; Traffic safety -- Periodicals; Traffic accidents -- Periodicals; Wounds and injuries -- Prevention -- Periodicals; 363.125
• DOI: 10.1080/15389588.2017.1317090
• Languages: English
• ISSNs: 1538-9588

Abstract

ABSTRACT: Objective : Advanced Automatic Collision Notification (AACN) is a system on a motor vehicle that notifies a public safety answering point (PSAP), either directly or through a third party, that the vehicle has had a crash. AACN systems enable earlier notification of a motor vehicle crash and provide an injury prediction that can help dispatchers and first responders make better decisions about how and where to transport the patient, thus getting the patient to definitive care sooner. The purposes of the current research are to identify the target population that could benefit from AACN, and to develop a reasonable estimate range of potential lives saved with implementation of AACN within the vehicle fleet. Methods : Data from the Fatality Analysis Reporting System (FARS) years 2009–2015 and National Automotive Sampling System–Crashworthiness Data System (NASS-CDS) years 2000–2015 were obtained. FARS data were used to determine absolute estimates of the target population who may receive benefit from AACN. These estimates accounted for a number of factors, such as whether a fatal occupant had nearby access to a trauma center and also was correctly identified by the injury severity prediction algorithm as having a "high probability of severe injury." NASS-CDS data were used to provide relative comparisons among subsets of the population. Specifically, relative survival rate ratios between occupants treated at trauma centers versus at non-trauma centers were determined using the nonparametric Kaplan–Meier estimator. Finally, the fatality reduction rate associated with trauma center care was combined with the previously published fatality reduction rate for faster notification time to develop a range for possible lives saved. Results : Two relevant target populations were identified. A larger subset of 6893 fatalities can benefit only from earlier notification associated with AACN. A smaller subgroup of between 1495 and 2330 fatalities can benefit from both earlier notification and change in treatment destination (i.e., non-trauma center to trauma center). A Kaplan–Meier life curve and a multiple proportional hazard model were used to predict the benefits associated with transport to a trauma center. The resulting range for potential lives saved annually was 360 to 721. Conclusions : This analysis provides the estimates of lives that could potentially be saved with full implementation of AACN and universal cell coverage availability. This represents a fatality reduction of approximately 1.6% to 3.3% per year, and more than double the lives saved by earlier notification alone. In conclusion, AACN is a postcrash technology with a promising potential for safety benefit. AACN is therefore a key component of integrated safety systems that aim to protect occupants across the entire crash spectrum.