Pacific Institute for Research and Evaluation 11710 Beltsville Drive, Suite 300 Calverton, Maryland 20705 Telephone: 301-755-2700 Fax: 301-755-2799 Unit Costs of Medium and Heavy Truck Crashes Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient’s Catalog No. 4. Title and Subtitle 5. Report Date Unit Costs of Medium/Heavy Truck Crashes March 13, 2007 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Eduard Zaloshnja, Ph.D. and Ted Miller, Ph.D 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) Pacific Institute for Research and Evaluation (PIRE) 11720 Beltsville Drive, Suite 900 Calverton, MD 20705 Phone: 301.755.2734 Fax: 301.755.2799 11. Contract or Grant No. 12. Sponsoring Agency Name and Address 13. Type of Report and Period Covered Federal Motor Carrier Safety Administration Federal Highway Administration 400 7th Street, SW Washington, DC 20590 Final Report 14. Sponsoring Agency Code 15. Supplementary Notes 16. Abstract This study provides the latest estimates of unit costs for highway crashes involving medium/heavy trucks by severity. Based on the latest data available, the estimated cost of police-reported crashes involving trucks with a gross weight rating of more than 10,000 pounds averaged $91,112 (in 2005 dollars). These costs represent the present value, computed at a 4% discount rate, of all costs over the victims’ expected life span that result from a crash. They include medically related costs, emergency services costs, property damage costs, lost productivity, and the monetized value of the pain, suffering, and quality of life that the family loses because of a death or injury. 17. Key Words 18. Distribution Statement truck; trailer; bobtail; crash; costs Copy available from National Technical Information Service, Springfield, VA 22160. 19 Security Classif. (of this report) 20. Security Classif. (of this page) 21 No. of Pages 22. Price Unclassified Unclassified Form DOT F 1700.7 (8/72) Reproduction of completed page authorized Table of Contents Executive Summary 1 Introduction 2 Methods 3 Results 5 References 9 Executive Summary This study provides the latest estimates of unit costs for highway crashes involving medium/heavy trucks by severity. Based on the latest data available, the estimated cost of police-reported crashes involving trucks with a gross weight rating of more than 10,000 pounds averaged $91,112 (in 2005 dollars). These costs represent the present value, computed at a 4% discount rate, of all costs over the victims’ expected life span that result from a crash. They include medically related costs, emergency services costs, property damage costs, lost productivity, and the monetized value of the pain, suffering, and quality of life that the family loses because of a death or injury. Other notable findings include: * Crashes in which truck-tractors with two or three trailers were involved were the rarest but their cost was the highest among all crashes – $ 289,549 per crash. * Crashes in which straight trucks with no trailers were involved had the lowest cost – $ 56,296 per crash. * The average cost of property damage only (PDO) crashes was $15,114 * The costs per non-fatal injury crash averaged $ 195,258. * As expected, fatal crashes cost more than any other crashes. The average cost of fatal crashes was $ 3,604,518 per crash. * The cost estimates exclude mental health care costs for crash victims, roadside furniture repair costs, cargo delays, earnings lost by family and friends caring for the injured, and the value of schoolwork lost. Introduction Safety analysts use crash cost data for a variety of purposes, from analyzing the effectiveness of a particular roadway enhancement to measuring the impact of seatbelt use. Crash costs are used to compare the relative efficacy of various crash countermeasures, which are expected to have a differential impact on crashes of different severity. These figures are also used to calculate and compare the cost-effectiveness of proposed safety regulations. Efficient allocation of research, enforcement, and analysis resources requires reliable data on crash costs. Miller, Viner et al. (1991) made a first attempt to estimate truck and bus crash costs. They first computed costs by threat-to-life severity measured by Maximum Abbreviated Injury Score (AAAM, 1985). The AIS scheme is a detailed medical classification developed by physicians as a basis for rating the survival threat injuries pose. It assigns a numeric rating ranging from 0 (uninjured) to 6 (maximum, generally unsurvivable). National Highway Traffic Safety Administration (NHTSA) data sets that are AIS coded add codes for “injured, severity unknown” and “unknown if injured”. MAIS is simply the maximum AIS among the multiple injuries a victim suffers. The purpose of the AIS scale is to differentiate injuries by survival threat, not the cost, functional losses, or course of recovery they involve. For example, loss of teeth is an AIS- 1 injury that can involve substantial costs and lifetime pain and suffering. Conversely, timely surgery often allows complete and rapid recovery from ruptured spleens and other AIS 3-5 internal injuries. Nevertheless, average costs per case within a body region almost always rise with MAIS (Miller 1993). By multiplying average costs per highway crash victim by MAIS times the MAIS distribution of victims in crashes sorted by the heaviest vehicle involved, Miller, Viner et al. (1991) estimated costs by vehicle type. Those estimates implicitly assumed that the distribution of injuries by body region within an AIS severity level did not vary with vehicle type. Only property damage and crash-related travel delay costs were tailored to truck and bus crashes. Miller, Levy et al. (1998) and Miller, Spicer et al. (1999) improved on Miller, Viner et al. (1991) by computing medium/heavy vehicle crash costs by vehicle type from 1982-1992 data on victim MAIS and body region in medium/heavy vehicle crashes. Zaloshnja, Miller, and Spicer (2000) paralleled their methods. It updated their estimates and substantially increased the number of cases used to estimate the injury distribution for occupants of light passenger vehicles involved in medium/heavy vehicle crashes. With the larger sample, it was able to more finely differentiate costs among heavy vehicle types. That study was the first to differentiate costs of single versus multiple trailer crashes. Zaloshnja Miller, and Spicer (2004) updated the results of Zaloshnja, Miller, and Spicer (2000) using methods described in Blincoe, Seay, et al (2002) and Zaloshnja, Miller, et al (2004). Notably, costs per non-fatally-injured victim of a highway crash were estimated by maximum AIS (MAIS), body part, and whether the victim suffered a fracture/dislocation. In addition to the more detailed diagnoses used in estimation, the accuracy of estimates was increased by using latest medical cost, wage, and income data. Property damage costs were updated using the latest insurance data on commercial vehicles. In estimating the productivity loss due to travel delays, it was assumed that only police reported crashes delay traffic. This was based on the premise that any substantial impact on traffic would attract the attention of police. This report provides costs per victim and per crash in of medium/heavy truck crashes stated in 2005 dollars. Differently from the previous report’s estimates (Zaloshnja Miller and Spicer, 2004), which were based on the injury severity profile of truck crashes from the 1982-86 period, the estimates presented in this report are based mainly on the injury severity profile from the 2001-03 period. Within the constraints of available data, this study provides economically sophisticated, reliable estimates of the average costs of medium/heavy truck crashes with different levels of severity. Methods Modeling crash injury costs requires estimates of the number of occupants involved in crashes, the medical details of each person’s injuries, and the costs of those injuries and associated property damage and travel delay. No data system that contains a nationally representative sample of recent U.S. medium/heavy truck crashes and records medical descriptions of the injuries is available. The National Highway Traffic Safety Administration’s (NHTSA’s) National Accident Sampling System [NHTSA, 1987] collected data containing medical descriptions of injuries for a representative sample of all police- reported U.S. motor vehicle injury victims in 1982-86. In 1988, NASS was replaced by two ongoing sampling systems. The Crashworthiness Data System (CDS) collects data similar to NASS but focuses on crashes involving automobiles and automobile derivatives, light trucks and vans with gross vehicle weight less than 10,000 pounds (4,537 kg) that are towed due to damage. The General Estimates System (GES) collects data on a representative sample of all police-reported crashes, but the only injury description it gives is the severity that a police officer assigned in the police accident report. The 2001-03 Large Truck Crash Causation Study (LTCCS) data provides the only sample of recent U.S. truck incidence data on crash injuries that records medical descriptions of the injuries, but to qualify for the LTCCS sample, a crash was to involve a large truck and at least one fatality that could be classified as “K” or injury that could be classified as “A” or “B” on the KABCOU scale (K - killed, A - incapacitating injury, B - non-incapacitating injury, C - possible injury, O - no injury, and U - injury, severity unknown). We used the 2001-03 LTCCS data in this study to estimate injury costs for these crashes and the 1982-86 NASS for the rest. To update the incidence of injury in less severe crashes, we adjusted the weights by truck type involved in crash, victim injury severity, and belt use, reflecting the incidence estimated from the 2001-2003 GES file. Same as Zaloshnja, Miller, and Spicer (2004), we adopted unit costs from Zaloshnja Miller, et al. (2004) and Blincoe, Seay, et al. (2002) to cost injuries in the 2001-03 LTCCS and 1982-86 NASS files. Those studies provide costs per victim in 2000 dollars by body part, whether or not a fracture/dislocation was involved, and Abbreviated Injury Scale (AIS) score. We updated the costs to 2005 dollars and merged them onto the crash files, calculating the comprehensive and economic costs per victim. Comprehensive costs represent the present value, computed at a 4% discount rate, of all injury-related costs that result from a crash over the victim’s expected life span. We chose this discount rate in order to be consistent with NHTSA’s and FHWA’s methodology. We included the following major categories of costs: (1) medically related, (2) emergency services, (3) lost productivity (wage and household work), and (4) the monetized value of pain, suffering, and lost quality of life. Together, the literature calls these comprehensive costs. Economic costs exclude the last item. Zaloshnja Miller, et al. (2004) and Blincoe, Seay, et al. (2002) medical cost estimates drew on data from 1992–1994 Civilian Health and Medical Program of the Uniformed Services (CHAMPUS) data for physician and emergency department fees, 1994–95 data on hospital costs in MD and NY (the only two states where costs, not charges or payments were known), and 1987 National Medical Expenditure Survey (NMES) and 1979–1987 National Council on Compensation Insurance (NCCI) data on the percentage of costs that occur more than 6 months post injury. Zaloshnja Miller, et al. (2004) and Blincoe, Seay, et al. (2002) based short-term productivity loss on information from the CDS 1988–1991(for AIS85) and CDS 1993–1999 (for AIS90) about the probability an employed person would lose work for a specific injury and the 1993 Survey of Occupational Injury and Illness (SOII) of the U.S. Bureau of Labor Statistics on the days of work lost per person who lost work. Mean probabilities of work loss were estimated from just those CDS records that had the relevant information, which frequently was missing. Sample size considerations drove the decision to pool several years of CDS data. Long-term productivity loss by diagnosis was based on 1979–1987 NCCI Detailed Claims Information (DCI) data on the probability that injuries would cause permanent partial/total disability and 1997 DCI data on the percentage loss of earning power for partially disabled injury victims. Zaloshnja Miller, et al. (2004) and Blincoe, Seay, et al. (2002) included a variety of other direct costs. Among them were emergency services, insurance claims administration, legal and court costs, and workplace disruption costs. These estimates used insurance data and data from prior NHTSA studies. Monetary losses associated with medical care, other resources used, and lost work do not fully capture the burden of injuries. Injuries also cost victims and families by reducing their quality of life. The good health lost when someone suffers a health problem or dies can be accounted for by estimating quality- adjusted life years (QALYs) lost. A QALY is a health outcome measure that assigns a value of 1 to a year of perfect health and 0 to death (Gold et al., 1996). QALY loss is determined by the duration and severity of the health problem. To compute it, following Miller (1993), Zaloshnja Miller, et al. (2004) and Blincoe, Seay, et al. (2002) used diagnosis and age-group specific estimates from Miller et al. (1995) of the fraction of perfect health lost during each year that a victim is recovering from a health problem or living with a residual disability. Such an impairment fraction was estimated by body part, AIS, and fracture/dislocation. Following the guidance of the Office of the Secretary of Transportation on the value of statistical life (OST, 2002), the monetary value of a QALY ($119,487) was derived by subtracting lost productivity from the Value of Statistical Life (VSL: $3 million) and then dividing by the number of years in the occupant’s life span. To avoid the variability that comes from age and gender differences of people involved in different crashes, in this report, differently from Zaloshnja, Miller, and Spicer (2004), we calculated occupants’ life span based on the median age of the U.S. population in 2005 (36.4). In addition to the monetary value per QALY used in this study, we present also values based on VSL greater that $3 million, which can easily be applied to our estimates if the VSL is increased in the future. Travel delay and property damage costs were updated directly from Zaloshnja, Miller, and Spicer (2004) using the wage index for the first and the consumer price index for the second Results Table 1 presents the annual number of victims and cost per victim by truck type involved in the crash and police-reported injury severity. The highest costs per victim are for fatalities (over $3 million) because they include the VSL. Excluding fatalities, the highest cost per victim is for incapacitating injury in crashes involving truck-tractor with 2-3 trailers ($783,017). Table 2 presents the annual number of crashes, the average number of victims and costs per crash by truck type involved in the crash and maximum police- reported injury severity. Again, the most costly crashes are fatal crashes (over $3 million). Excluding fatal crashes, the most expensive crashes are those involving truck-tractor with 2-3 trailers in which at least one victim had an incapacitating injury ($1,291,936) Table 3 presents the estimated costs per crash for all crashes and Table 4 presents the estimated costs per crash for injury crashes only. The $ 289,549 average cost per crash for vehicles with two or three trailers far exceeds the $ 97,574 for a tractor-trailer crash. In average, the total cost per large truck crash reported here is 53% higher than that reported in Zaloshnja, Miller, and Spicer (2004). Nearly half of this increase can be explained by the different dollar years used - from 2000 to 2005, the medical expenditure index rose 40%, the wage index rose 20% and the consumer price index rose 13%. The remaining increase can be mainly explained by the change in the injury severity profile (the average number of people involved in a crash was only slightly increased – from 1.21 to 1.25). As mentioned earlier, Zaloshnja Miller and Spicer (2004) based cost estimates on the injury severity profile of truck crashes in the 1982-86 NASS file, whereas the estimates presented in this report are based mainly on the injury severity profile in the 2001-03 LTCCS file. Table 5 present different values based on VSL from $3-$7 million. These values can be easily multiplied by the QALYs presented in previous tables, if the VSL is increased in the future. TABLE 1. Costs per Medium/Heavy Truck Crash Victim by Truck Type Involved in Crash and Police- Reported Injury Severity, 2001-03 (in 2005 dollars) * Annual number of fatal victims estimated from 2001-03 FARS, annual number of victims involved in crashes with maximum severity not A, B, or K estimated from 2001-03 GES 2001-03, and the rest from 2001-03 LTCCS TABLE 2. Costs per Medium/Heavy Truck Crash by Truck Type Involved in Crash and Police-Reported Maximum Injury Severity, 2001-03 (in 2005 dollars) * Annual number of fatal crashes estimated from 2001-03 FARS, annual number of crashes with maximum severity not A, B, or K estimated from 2001-03 GES 2001-03, and the rest from 2001-03 LTCCS TABLE 3. Costs per Crash by Truck Type Involved in Crash, 2001-03 (in 2005 dollars) * Annual number of fatal crashes estimated from 2001-03 FARS, annual number of crashes with maximum severity not A, B, or K estimated from 2001-03 GES 2001-03, and the rest from 2001-03 LTCCS TABLE 4. Costs per Injury Crash (Max Injury: A, B, C, or U ) by Truck Type Involved in Crash, 2001-03 (in 2005 dollars) * Annual number of crashes with maximum severity not A or B estimated from 2001-03 GES 2001-03 and the rest from 2001-03 LTCCS Table 5. Value of a QALY Based on Different Values of Statistical Life (in 2005 dollars) References AAAM. (1985) The Abbreviated Injury Scale 1985. Des Plaines IL: Association for the Advancement of Automotive Medicine. Blincoe, L. J., Seay, A. G., Zaloshnja, E., Miller T.R., Romano E.O., Luchter, S., Spicer, R.S. (2002). The economic impact of motor vehicle crashes, 2000. Report DOT HS 809 446. U.S. Department of Transportation, NHTSA, Washington, DC. Gold, M. R., Siegel, J. E., Russell, L. B., & Weinstein, M. C. (Eds.). (1996). Cost- effectiveness in health and medicine. New York, NY: Oxford University Press. Miller, T. R., Viner, J., Rossman, S., Pindus, N., Gellert, W., Dillingham, A., and Blomquist, G. (1991) The Costs of Highway Crashes. The Urban Institute, Washington DC. Miller, T.R. (1993) Costs and Functional Consequences of US Roadway Crashes. Accident Analysis and Prevention. 25, 593-607. Miller, T.R., Pindus, N.; Douglass, J.; Rossman, S. (1995) Databook on Nonfatal Injury -- Incidence, Costs, and Consequences. 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Zaloshnja, E., Miller, T.R., Romano, E.O., & Spicer, R.S. (2004). Crash costs by body part injured, fracture involvement, and threat to life severity, United States, 2000. Accident Analysis and Prevention, 36(3), 415–427. COSTS OF LARGE TRUCK- AND BUS-INVOLVED CRASHES 1 UNIT COSTS OF MEDIUM/HEAVY TRUCK CRASHES V