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Database Analysis 37 state-by-state basis. To date, 27 states have been evaluated. It is known that states are taking the evaluations into consideration in improving their systems and have instituted changes to correct the problems identified by UMTRI. The UMTRI program is just one facet of a comprehensive pro- gram at FMCSA to assist the states in improving their accident reporting. In general, significant progress has been made, but the completeness and accuracy of the data in MCMIS remains a seri- ous issue. Moreover, there are many fields in the PAR that are either not filled out or not translated into the MCMIS format, and when fields that must be used to identify serious accidents are left blank or inaccurately filled out, then either serious accidents that should be reported are not reported or accidents that are not serious are filed because the inaccurate information provided makes them appear serious. Additional analyses reflecting on the accuracy and completeness of the data in the MCMIS Crash file are found in Appendix C (available on the TRB website at www.TRB.org by searching for HMCRP Report 1). 4.1.11 Identification of Hazmat Incidents in MCMIS Table 4-2 lists some of the key parameters recorded in MCMIS and the percentage of the entries for which no information is presented in calendar year (CY) 2005. Overall, there is about a 20% underreporting rate. As shown in Table 4-2, the percentage of blanks in the MCMIS Crash file tables varies from zero to about 30%. For fields like FATALITIES and INJURIES, there are no blank entries because zero is entered if there were no injuries or fatalities. Similarly, there are no blank entries for Y/N fields such as TOW AWAY. There is one parameter, DRIVER CONDITION CODE, which is left blank in all crash records after CY 2001. In 2001, the field was coded as "driver appeared normal" for about 94% of the crashes. It is the other 6% of the crashes where the contributing cause, or even the root cause, might have been "driver condition." Since there is a location on the PAR to enter this information and since a police officer is trained to observe a person's behavior, some weight can be assigned to the officer's opinion regarding the driver's suitability to be operating a motor vehicle. Since this is the Table 4-2. Percentage of entries blank by parameter name. Percentage Parameter Name Blank Carrier Name Provided for Each Incident 0% Fatalities 0% Injuries 0% Tow Away 0% County Code 1% Driver Name Provided for Each Vehicle 2% Vehicle Configuration 4% Weather 7% Light Condition 8% Road Surface Condition 8% Cargo Body 9% No Event Sequence Provided for Each Incident 16% Vehicle Identification Number 17% Traffic Way 18% Access Control 23% Accident Location Adequate 23% Vehicle Hazmat (Y/N) 24% GVWR 26% DOT Number 31%

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38 Hazardous Materials Transportation Incident Data for Root Cause Analysis only driver condition parameter included in the MCMIS Crash file, leaving this parameter blank is considered a significant loss. For the remaining parameters that have less than complete coverage, either the PAR did not pro- vide the value or the state staff person translating the information into the MCMIS crash format did not enter a value for the parameter. In Hazardous Materials Serious Crash Analysis: Phase 2 (Battelle 2005), PARs were obtained for all vehicles that were believed to be transporting hazardous materials in 2001, over 1,800 PARs. For almost all the parameter fields that were left blank in the MCMIS crashes in 2001, it was possible to fill in missing parameter values from the PARs. There were some notable exceptions. One state did not provide the commercial vehicle truck supplement to the PAR and, without that, it was impossible to fill in the vehicle configuration and gross vehi- cle weight rating (GVWR). That supplement also contained the hazmat data. If the staff person has access to all the PAR data, all the blank percentages would probably be less than 10%. The reasons for the information being lost are unknown. The last four entries in Table 4-2 provide some statistics regarding how well the informa- tion is coded into MCMIS. The MCMIS Catalog, published on the FMCSA website, provides no standard regarding how to fill out the location field. The information provided is sufficient to locate the accident on a map only 23% of the time. These entries typically occurred at inter- sections or the location was specified as a route name or number along with the number of the nearest milepost. There are a variety of reasons for this low percentage. In many cases, only the route name is given and if the state and county are given, which is normally the case, then the best that can be done is to locate the accident on a route somewhere in a county through which the route passes. Evidently, at some point in the translation between the PAR and the MCMIS Crash file, a 30-character limit was imposed on the location field. There were numer- ous cases where the entry stopped mid-word and, as a result, truncated the milepost informa- tion needed to locate the accident on the route. A comparison of the entries in the CRASH_EVENT and CRASH_MASTER Tables reveals that no crash event is provided for 16% of the crashes. Of the remaining 84% of the crashes with event sequences, 57% list one event, 13% list two events, 5% list three events, and 9% list four events. Based on these percentages, for 16% of the crashes, it is impossible to even identify the type of crash. For slightly more than one-half of the crashes, one event sequence is provided. Based on the statistics shown in Table 4-3, the use of one event to define the acci- dent often can be justified. The dominant single-event sequence accident in which a truck is involved is coded as EVENT_ID=13, "collision involving motor vehicle in transit." This is the event code for 82% of the vehicle incidents with a single event listed in the CRASH_EVENT Table. The next most likely entry is "other," occurring 4% of the time. Table 4-3 lists, in order of decreasing percentages, the name of the single event followed by the percentage of crash records and the number of crash records listing this single event to describe the accident sequence. In going down the list shown in Table 4-3, there are several significant features. If the number of single events that fall into the equipment failure category were totaled, although individually they each show a zero percentage, the combined number would be above 1%. There also are a fair number that could be better described using more than one sequence. For example, it is highly unlikely that striking an animal would cause sufficient damage to the vehicle to result in an injury to one of the truck occupants or result in the truck being towed from the scene, mak- ing it a serious accident that would be reported to MCMIS. Did striking the animal result in a jackknife or the truck running off the road or overturning? A two-element event sequence prob- ably should have been used for that class of accidents. Overall, the biggest concern remains underreporting, closely followed by failure to enter parameter values for a significant fraction of the records.

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Database Analysis 39 Table 4-3. Crashes described by a single event. Percentage of Number of Event Description Single Events Crash Records Collision involving motor vehicle in transit 82% 73,591 Other 4% 3,358 Collision involving a parked motor vehicle 3% 2,462 Collision involving fixed object 3% 2,424 Non collision overturn (rollover) 2% 2,147 Collision with other movable object* 1% 1,074 Non collision other 1% 901 Non collision ran off road 1% 792 Collision involving pedestrian 1% 767 Collision involving animal 1% 606 Non collision explosion or fire 0% 352 Non collision jackknife 0% 308 Non collision cargo loss or shift 0% 299 Non collision equipment failure (brake failure, 0% 254 blown tire, etc.) Collision involving pedalcycle 0% 237 Collision involving a train 0% 134 Non collision separation of units 0% 96 Collision with unknown movable object 0% 70 Non collision downhill runaway 0% 44 Collision with work zone maintenance equipment 0% 35 Non collision unknown 0% 33 Non collision cross median/centerline 0% 31 *Previously "collision involving other object." 4.1.11.1 Overall Reporting Rating for the States Table 4-4 provides a summary of state reporting rates for different factors for those states that UMTRI has evaluated. The rates are recorded as the percent of reportable cases that were actu- ally reported, by crash severity (in the MCMIS scale). Table 4-4 shows that reporting rates have tended to improve in recent years and that the lowest rates are associated with earlier years. For completeness, UMTRI has compiled the percentage of missing data for the primary vari- ables. They also compare variables as reported in MCMIS to how they appear in the state file. Unfortunately, comparing the values doesn't reveal if the MCMIS information is accurate, just whether it is the same as what was reported to the state. To get a further handle on accuracy, it would be necessary to compare the information with an independent source. This is accomplished in the next section for fatal crashes using the TIFA database. In the TIFA survey, individuals are called and asked about the crash. These contacts include the driver, owner, safety director, and reporting police officer. 4.1.11.2 Comparing MCMIS with TIFA to Evaluate Crash Data Accuracy The TIFA file maintained by UMTRI provides a unique opportunity to evaluate the accuracy of the data reported to the MCMIS Crash file. TIFA data are collected independently from the MCMIS Crash file data, using a different methodology. MCMIS Crash file data are extracted by the states from their crash data and uploaded to the MCMIS Crash file using the SafetyNet System. Some states extract the data from a supplementary crash reporting form, while others incorporate the required data on their primary crash report. Many states use a computer algo- rithm to identify reportable crashes, while others manually identify reportable crashes and extract the data. Whatever the method, the data originate with the officer responsible for filing the crash report.

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40 Hazardous Materials Transportation Incident Data for Root Cause Analysis Table 4-4. Reporting rates of states to MCMIS Crash file compiled from UMTRI reports. Overall State Data Year Reporting Fatal Injury Tow Away Rate Alabama 2005 76.0 91.4 76.4 75.0 Arizona 2005 78.2 93.8 83.4 75.6 Connecticut 2005 Likely <30% California 2003 72.0 84.2 73.9 70.9 Florida 2003 24.0 55.6 26.5 20.0 Georgia 2006 68.1 78.8 68.4 67.4 Idaho 2006 72.9 92.3 90.5 60.7 Illinois 2003 43.0 71.0 42.3 42.6 Indiana 2005 80.5 90.3 81.9 79.6 Iowa 2005 71.6 94.1 86.4 61.4 Louisiana 2005 56.6 79.6 57.0 54.7 Maryland 2005 31.1 84.6 56.0 15.6 Michigan 2003 73.7 92.4 73.1 73.4 Missouri 2000 60.9 76.8 63.7 58.8 Missouri 2005 83.3 94.6 84.9 81.8 Nebraska 2005 86.8 100.0 82.0 82.7 New Jersey 2003 82.5 67.4 81.5 83.2 New Mexico 2003 9.0 27.5 11.0 6.8 North Carolina 2003 48.2 63.3 49.4 47.1 Ohio 2000 38.8 50.7 58.2 28.6 Ohio 2005 42.5 85.4 52.7 32.3 Pennsylvania 2006 77.0 91.7 74.5 77.6 South Dakota 2005 66.4 78.9 64.9 66.4 Tennessee 2004 51.3 93.5 54.8 47.4 Washington 2003 37.6 to 53.7 67.2 About 40 In contrast, the TIFA protocol uses state crash reports, but primarily to identify persons with knowledge of the crash for a telephone interview. Interviewers typically contact the driver, owner, or safety director of the carrier for a detailed interview about the truck, driver, and carrier that operated the truck. If the driver or carrier can not be contacted or refuses to cooperate, the inter- viewer will contact the reporting officer, tow operator, or other witness. But the great majority of interview information comes from sources that actually operated the truck. In addition, all sur- vey information is reviewed by experienced editors who decode the vehicle identification num- ber (VIN), look up the manufacturer's original specifications for the vehicle to compare with interview information, and also consult a library of information on typical cargoes, trailers, and carrier operations. Information that is ambiguous or unusual is clarified by return calls to the orig- inal respondent. Rarely, if no other information is available, some limited descriptive informa- tion may be coded from the police report. But the overwhelming majority of information in the TIFA file is collected directly from the vehicle operators. Because TIFA data are assembled by a completely separate process and entity, the TIFA file can serve as a relatively independent view of trucks involved in traffic crashes that are reported to the MCMIS Crash file. We say relatively because there are occasional instances where certain information may be coded from a police report. But there are good reasons for regarding TIFA data as reasonably accurate. Most cases have more than one source for the data (unless all infor- mation can be collected from a single source). Any ambiguous or contradictory information is clarified by further calls. TIFA editors have over 20 years of experience in working with large trucks, and they are knowledgeable about the variety of vehicles and operations. Finally, all cases are checked using computer algorithms for consistency, and to identify unusual cases for further

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Database Analysis 41 review. The TIFA file is not free of errors, but there are multiple layers of checks to keep the error rate low. Accordingly, the TIFA file can be used to check the accuracy of fatal truck crashes in MCMIS. The TIFA file includes only fatal crash involvements, significantly limiting the number of MCMIS records that can be checked. Nevertheless, since fatal crash involvements often receive the most detailed investigations by police, the records in MCMIS for fatal involvements arguably should be the most accurate. In that sense, the results of the comparison with TIFA represents the best-case scenario. To perform the comparison, records in four years of TIFA crash data were matched to the cor- responding records in the MCMIS Crash file. Crash involvements for 2002 through 2005 were matched, producing 11,914 records for comparison. Table 4-5 shows the comparison of the identification of hazardous material in the MCMIS Crash file and the matching record in the TIFA file for the period from 2002 to 2004. In the TIFA file, the value recorded was whether the cargo body had amounts of hazardous materials suffi- cient to require a placard. In the table, cases where that information was unknown for all cargo bodies are counted as no hazardous materials. In MCMIS, the unknowns are shown as "(blank)," to indicate the value was left unknown. Valid entries for the variable in MCMIS are "Y" or "N." The one case with an "M" is considered to be a typo in which "N" was meant. Table 4-5 shows some disconcerting patterns. Of the cases where the TIFA interview indicated the truck had placarded amounts of hazmat, the MCMIS hazmat placard was coded "Y" for 212, "N" for 172, and left blank for 50. There were also 95 cases where the hazmat placard was coded "Y" in MCMIS, but the TIFA interview showed that the truck did not have hazmat cargo. Thus, of the 434 cases in the TIFA file recorded as carrying hazmat, only 212 or 48.8% were coded as carrying hazardous material in the MCMIS file. Similarly, of the 307 cases coded as carrying haz- ardous material in the MCMIS file, only 212 or 69.1% actually had hazardous material. One possible explanation for the discrepancy could be that the MCMIS variable captures trucks showing a hazmat placard, regardless of whether the truck actually had hazmat. In fact, there were 60 cases identified in the MCMIS Crash file with hazmat placard coded "Y" for trucks that were empty at the time of the crash. Another 34 had some cargo, but the TIFA interview showed that it did not include hazmat. Comparisons also were made for several other variables. For truck cargo body and configuration, a comparison was made of the detailed code levels. The TIFA file includes more detailed types of cargo bodies and truck configurations than allowed in the MCMIS Crash file but, for the purpose here, both were aggregated to the levels permitted in MCMIS. Table 4-6 shows the distribution of Table 4-5. Identification of hazmat cargoes in TIFA and MCMIS, 20022004. TIFA Code MCMIS Code N Hazmat Hazmat Cargo Placard Total N 172 Yes Y 212 (blank) 50 M 1 N 8,484 No Y 95 (blank) 2,900 Total 11,914