Statistical adjustment for misclassification of seat belt and alcohol use in the analysis of motor vehicle accident data.
The use of seat belts and alcohol is often mis-reported in police motor vehicle accident reports for a number of reasons. To avoid penalties, occupants often over report seat belt use and under report alcohol use. Police officers sometimes fail to account for evidence such as presence of belt burn, condition of belts, odor of alcohol, crash patterns, etc. Biased conclusions result when using misclassified accident data to estimate the effectiveness of seat belts in preventing injuries and reducing medical costs. We investigated the effects of misclassification of seat belt and alcohol use on the odds ratio of injury as well as medical costs. A statistical method and a SAS program were developed to adjust odds ratios of injury and medical cost estimates to account for misclassification of seat belts and alcohol use. The method allowed for incorporation of variables that could affect misclassification of seat belt and alcohol use. We conducted a Monte Carlo simulation and found that when there were large differences between the misclassification rates for major and minor injury, the unadjusted odds ratio could have up to a 90% bias while our adjusted odds ratio was effectively unbiased. To illustrate the method, we estimated the misclassification rates of seat belt and alcohol use by comparing merged police and hospital reports from Nebraska motor vehicle accident data sets (1996-1997) and then evaluated the bias of the odds ratio of injury and medical costs estimates due to misclassification. Our results showed that the bias of the odds ratio of injury and medical costs due to misclassification of seat belts and alcohol use depended both on the amount of misclassification and the reported frequencies. Misclassification about seat belt and alcohol use only slightly biased the unadjusted odds ratio estimates and mean hospital charge, while misclassification resulted in approximately a 69% underestimate of the total medical costs savings due to seatbelts. However, due to the small size of the merged Nebraska police and hospital data set used to estimate misclassification rates, these results are likely somewhat imprecise.
Guo
Haifeng
H
Minneapolis Medical Research Foundation, 914 South 8th Street, Suite S-206, Minneapolis, MN 55404, USA.
Eskridge
Kent M
KM
Christensen
Daniel
D
Qu
Ming
M
Safranek
Thomas
T
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000428:Alcohol Drinking / Q000009:adverse effects / Q000453:epidemiology*; D001334:Automobile Driving / Q000523:psychology / Q000706:statistics & numerical data*; D008192:Deception; D006801:Humans; D015233:Models, Statistical; D016017:Odds Ratio; D012309:Risk-Taking; D012449:Safety / Q000706:statistics & numerical data; D012622:Seat Belts / Q000706:statistics & numerical data*; D015983:Selection Bias; D014481:United States / Q000453:epidemiology; D014947:Wounds and Injuries / Q000453:epidemiology* / Q000209:etiology / Q000517:prevention & control