295125
Estimating the effect of emergency care on early survival after traffic crashes
Methods: Data from 2002-2003 were combined from the Fatality Analysis Reporting System (FARS) and an expanded version of the National Automotive Sampling System (NASS) Crashworthiness Data System (CDS). Weighted Cox and Weibull models for survival time (tSURV) were estimated, with time-varying covariates (TVC) having constant effects for specified time intervals following EMS arrival time (tEMS) and hospital arrival time (tHOS). The Weibull model was repeated with tSURV interval-censored to reflect uncertainty about the exact time of death, using an imputation method to accommodate interval censoring along with TVC.
Results: FARS contained records for 92,718 persons with fatal or incapacitating injuries, and NASS/CDS contained 5,517 (weighted population of 642,716) with incapacitating injuries. All models associated mortality with increasing age, male sex, belt nonuse, higher speeds, and vehicle rollover. The interval-censored model associated EMS intervention with a beneficial effect until tEMS + 30 minutes, but not thereafter; hospital intervention was associated with a strongly beneficial effect that increased with time. Rural location was associated with a higher baseline hazard; a 50% reduction in rural prehospital time would theoretically reduce 4-hour mortality by about 7%.
Conclusion: Rural/urban disparity in crash mortality is mostly independent of time delays and EMS effects. However, survival models with TVC support clinical intuition of a golden hour in EMS care, and the importance of timely transport to a hospital.
Learning Areas:
Biostatistics, economicsEpidemiology
Learning Objectives:
Explain why traffic crash mortality is higher in rural areas.
Demonstrate methods to analyze the effect of EMS and hospital intervention on early mortality.
Keyword(s): Emergency, Injury Control
Qualified on the content I am responsible for because: I have numerous publications about injury epidemiology and trauma systems, especially related to statistical models.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.