INJURIES, DEATHS AND COSTS RELATED TO MOTOR VEHICLE CRASHES IN WHICH ALCOHOL WAS A FACTOR, WISCONSIN, 2013
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1 Crash Outcome Data Evaluation System INJURIES, DEATHS AND COSTS RELATED TO MOTOR VEHICLE CRASHES IN WHICH ALCOHOL WAS A FACTOR, WISCONSIN, 2013 Wayne Bigelow Center for Health Systems Research and Analysis University of Wisconsin Madison February, 2015 To contact the author: (608) wayne@chsra.wisc.edu
2 2 SUMMARY We evaluated motor vehicle crashes (MVCs) on public roads in Wisconsin for 2013 in which a police officer reported that alcohol consumption was a factor in the crash. In total, 10,379 persons were victims in alcohol related MVCs. Of those, 4,983 of those were not the responsible party. Highlights of our findings: Victims of alcohol related MVCs only made up 3.6% of all MVC victims. BUT: Victims of alcohol related MVCs made up 17% of all hospitalizations Victims of alcohol related MVCs Have average costs which are 6 times higher and make up 23% of all MVC related costs. Alcohol related MVCs cost Wisconsin $903 million in persons (36% of all MVC fatalities), comprising 6,756 years of life lost, were victims of alcohol related MVCs. For non-responsible victims of alcohol related crahes: 547 (11%) visited an emergency room 144 victims (2.9%) were hospitalized three times the rate for non-alcohol related crashes 41 victims (.8%) were killed eight times the rate for non-alcohol related crashes 1,454 years of expected life were lost. For children (under 19 years): 18 were hospitalized and 4 died Drinking and driving continues to remain a problem with tragic consequences in Wisconsin. BACKGROUND Perhaps no safety issue in transportation is more tragic than motor vehicle crashes related to alcohol consumption. Unlike motorcyclists who don t wear helmets and vehicle occupants who do not wear seat belts the consequences of which fall largely on the individual drinking and driving often involve innocent (ie. not responsible) persons. In Wisconsin, during 2013, there were 4,975 persons involved in alcohol related MVCs who were simply passengers (not driving and drinking) 48% of all persons involved in alcohol related crashes. NHTSA reports that in 2005 there were 16,885 fatalities in alcohol related crashes, one every half hour (Traffic Safety Facts 2005 Data). NHTSA also estimated that 254,000 persons were injured in alcohol related crashes, one every 2 minutes. Given the pervasiveness of the this problem and it s potential impact on transportation safety for communities and the state as a whole, we ve developed some basic information on alcohol related crashes costs and health events using the Wisconsin CODES data system for
3 METHODS 3 Data Sources The data used in this analysis is from the Wisconsin Crash Outcomes and Data Evaluation System (CODES) database. The Wisconsin CODES project is funded through grants from NHTSA and the Bureau of Traffic Safety within the Wisconsin Department of Transportation. The CODES data is comprised of two sets of records.. The first is the Wisconsin motor vehicle crash records data. The 2013 crash data was obtained through the Wisconsin Department of Transportation (WisDOT). This crash data contains information on all reportable crashes (with at least one injury or fatality, or at least $1000 in property damage. The data are collected by police officers at the crash scene, and include detailed information on the time, location and characteristics of the crash, as well as on the vehicle(s) and occupant(s) involved. The 2013 hospital discharge and Emergency Department (ED) data is obtained from the Wisconsin Hospital Association. State law mandates that all Wisconsin licensed hospitals report all inpatient discharges. This data combines detailed information on patient demographics, up to nine ICD-9 and five procedure codes, an external cause of injury code (E-Code), charges, length of stay and admission and discharge information. Data Merging The CODES analysis database was created by using a technique called probabilistic linkage (10) from By utilizing common information in both data sets, probabilistic linkage iteratively estimates a set of log odds weights used to determine the probability that specific records apply to the same person. The information used to link Wisconsin s CODES data included sex, age, date of birth, zip code of residence, county of crash, E-code derived type of injury and dates of hospitalization and of the crash. Starting in 2013, the quality of the data had improved to the point where exact linkage was used to merge crash and health related data. The data linkage for 2013 was performed by staff within the Department of Health and Family Services. Software Statistical Analysis System (SAS) software (SAS Institute,Inc., Cary, NC) was used for all statistical analysis and data merging. Case Definitions For our analysis we defined as alcohol related all cases for which WisDOT s crash data system revealed that alcohol was indicated as a factor in the crash by the reporting police officer. This particular data element is labeled ALCFLAGA in the accident record component of the crash data, and its values are either Y or N. All other cases were defined as non-alcohol related. To determine whether a particular individual was a responsible party among persons in alcohol related crashes we utilized a special flag indicating the person for which the reporting police officer thought had been drinking (there may be more than one per accident). This data element is labeled ALCFLAG in the occupant record component of the crash data, and its values are also either Y or N. By definition, no vehicle passenger could be the responsible party only vehicular drivers, cycle/moped operators, bicycle operators and pedestrians. We then excluded all crashes which occurred in a parking lot or on private property. The data elements included in the analysis are shown in Figure 1 (next page). 3
4 4 Figure 1. Variables Used in the Analysis Alcohol Use: Age ER Visit Hospitalization Death Medical Costs Other Costs Quality of Life Costs Combines police officer report of whether or not they believe that alcohol was a factor in the crash. < 19, 19-25, 26-35, 36-55, 55-64, 65 years or older and Missing Crash record was linked to an emergency department record. Crash record was linked to a hospital inpatient discharge record. Defined using K in the KABC0 scale in (WisDOT s crash data), and using hospital and ER discharge codes indicating death. Calculated from abbreviated injury scores and body part or region. Calculated from abbreviated injury scores and body part or region. Calculated from abbreviated injury scores and body part or region. A presentation on estimating these costs can be obtained from author upon request.. When all three of these costs are combined they comprise Comprehensive crash costs as defined by the National Safety Council (NSC). If only Medical and Other costs are combined, the estimates comprise Human Capital model costs as used by both the NSC and NHTSA. All cost estimates are adjusted for inflation and a Wisconsin specific cost of living adjustment. Years of Life Lost For deaths, equal to life expectancy (75) minus age at death. 4
5 Table 1 shows the number of persons for whom police reported that their consumption of alcohol was a factor in causing the motor vehicle crash, as well as the number of persons who received a citation. By definition, no motor vehicle passenger is included in this group. Altogether, police reported that there were 5,396 drivers, bicyclists and pedestrians whose alcohol consumption was a factor in the motor vehicle crash (MVC) they were involved with. As one would guess, most alcohol related crashes are due to motor vehicle drivers (95%) and motorcyclists (3%), with some pedestrians and a few bicyclists also being at fault. Overall, 91.8% of those persons received a citation. The percentage was greatest for motor vehicle drivers (93%) and motorcyclists (75%), with half or less of bicyclists and pedestrians receiving citations. 5 Table 1. Number & Percent of Persons Whose Alcohol Consumption Police Reported as Being a Factor in Causing the Crash, and the Number & Percent of Those Persons Receiving a Citation, Wisconsin, 2013 Number with Type of Person Alcohol as a Number Factor in Crash Percent Cited Percent Motor Vehicle Drivers 5, % 4, % Motorcycles/Moped Operators % % Bicyclists 22.5% % Pedestrians % % TOTAL 5, % 4, % 5
6 Table 2, below shows the number of responsible persons in alcohol related crashes, and the number of other victims, by age group; along with the total number hospitalized and who died. While there were 5,396 responsible persons, there were almost as many non-responsible victims involved 4,983. There were 438 hospitalizations caused by the responsible parties (4.2% of all persons), and there were 187 persons (1.8%) who died. As can be seen, children and persons under 19 years make up almost 14% (731) of all non-responsible crash victims. For all persons under 19 years of age (responsible and not responsible) 30 of them were hospitalized and 6 died. The rates of hospitalization were highest for persons aged 66 or older (6.4%), as was the percent who died (4.9%). 6 Table 2. Number of Responsible Persons, Number of Other Victims, Number and Percent Hospitalized and Died, For Alcohol Related Crashes, Wisconsin, 2013 Number Number Number of Other Persons Percent Number Percent AGE Responsible Persons Hospita- Hospita- Persons Who Persons Involved Lized Lized Died Died Less Than 19 Years % 6.7% Years 1, % % Years 1, % % Years 1, % % Years % % 66+ Years % % Age Missing 11 1, % 0.0% Total 5,396 4, % % 6
7 Table 3, below, shows a variety of health related outcomes, and costs, for persons involved in motor vehicle crashes where no alcohol was involved, and where alcohol was involved. The results clearly show the greater injuries sustained by persons in alcohol related crashes. MVC victims in crashes where alcohol is involved make up just over 3% of all crash victims. But they represent 17% of all hospitalizations and over 35% of all deaths. Alcohol related MVC crash victims are 70% more likely to end up at an ER, 4.8 times as likely to be hospitalized and are 13.8 times as likely to die, as non-alcohol related MVC victims. On average, 16 times as many years of life are lost for each person involved in an alcohol related MVC by comparison to those involved in non-alcohol related MVCs. In total, over 40.5% of all years of life lost due to MVCs result from alcohol related crashes. Alcohol related crashes account for almost $ 903 million in comprehensive costs, compared to $3.1 billion for non-alcohol related crashes or a quarter of all costs. Alcohol related MVC victims have average overall costs which are almost six times higher than are those for non-alcohol related crashes ($94,240 compared to only $15,469). 7 Table 3. Costs, and Health Events and Outcomes, for Persons Involved in Crashes in Which Alcohol was a Factor or Not, Wisconsin, 2013 No Alcohol No Alcohol Alcohol Alcohol Ratio of OUTCOME Involvement Involvement Involvement Involvement Alcohol to Non- MEASURE in Crash in Crash in Crash in Crash Alcohol # or $ Totals % or Average # or $ Totals % or Average Total Persons 277, % 10, % Ratio ER Visit 18, % 1, % 1.9 Hospitalized 2,190.8% % 4.8 Died % % 13.8 Years of Life Lost 9, , Medical Costs $ 488 million $ 1,792 $ 76 million $ 7, Other Costs $2.37 billion $ 8,527 $ 438 million $ 43, Quality of Life Costs $1.48 billion $ 5,150 $ 447 million $ 43, Total Costs $3.13 billion $ 15,469 $ 903 million $ 92,
8 Table 4, below, shows the cost of drinking and driving for non-responsible victims across a variety of health related outcomes for alcohol related motor vehicle crashes. Out of 4,975 non-responsible victims: (11.0%) visited an emergency room 144 victims (2.9%) were hospitalized over three times the rate for non-alcohol related crash victims in victims (.8%) were killed over eight times the rate for non-alcohol related crashes 1,454 years of expected life were lost For children (under 19 years): 18 were hospitalized and 4 died. Table 4. Health Events and Outcomes, for Persons Involved in Alcohol Related Crashes Who Are Not Responsible, by Age Group, Wisconsin, 2013 Non- Responsible All Occupants ER Visit ER Visit Hospitalized Hospitalized Died Died Persons # % # % # % Years of Life Lost Age < % % 4.6% % % 9.9% % % 6.9% % % % % 8 2.7% 4 1.4% % 6 4.0% 5 3.3% 8 Missing 1, % 0 0.0% 0 0.0% 0 ALL 4, % % 41.8% 1,454 8
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