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Hazardous Materials Transportation Incident Data for Root Cause Analysis (2009)

Chapter: Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes

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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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Suggested Citation:"Chapter 5 - Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes." National Academies of Sciences, Engineering, and Medicine. 2009. Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press. doi: 10.17226/14336.
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5.1 Introduction This chapter discusses potential measures to improve the capability of officials and researchers to identify the root causes of hazmat transportation accidents. As discussed in Chapter 1 of this report, the following definition of root cause was used to develop these measures: One or more contributing factors that lead to the occurrence of a transportation accident and/or affect the severity of its consequences. As previously noted, root cause identification may depend on detailed and accurate information available for five major parameters of vehicle, driver, packaging, infrastructure, and situational. Inadequate information in any one of these parameters may result in the inability to accurately identify the root cause of the hazmat crash. If a contributing factor can be mitigated, the likelihood of occurrence and corresponding impacts of an entire class of accidents could be significantly reduced. When focusing on one class of accidents, such as single-vehicle cargo tank rollovers, much can be learned when the data show that a contributing factor is present in a large fraction of the accidents. Consequently, policies can be developed and actions initiated to improve safety. 5.2 Information System Development A key finding emanating from this study is the need to establish a root and contributing cause information system. The system would have the following two major components: • Linking crash databases together so information in different databases can be easily retrieved for the same crash. This incorporates some of the same elements proposed by PHMSA for increasing the effectiveness of hazmat databases and techniques developed for FMCSA’s Serious Hazmat Crash Project. • Selecting a group of hazmat crashes annually for collecting additional information that will enable officials and researchers to identify the root and contributing causes of that class of haz- mat transport accidents. This follows lessons learned from FRA’s detailed examination of selected crashes, NTSB’s focus on investigating a certain class of crashes, techniques used for the Serious Hazmat Crash Project, and the TIFA database for adding to information in the FARS database. In order to move toward the identification of root and contributing causes, officials and researchers need to utilize all available data related to either a single hazmat crash or an entire population. Where crash information is collected in more than one database and by different parties, the data could be combined to provide a thorough accident portrait. For example, the 95 C H A P T E R 5 Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes

same hazmat truck crash may appear in FMCSA’s MCMIS database and in PHMSA’s HMIRS database. The information in these databases could be linked to combine information from dif- ferent sources on the same accident. Similar reasoning could apply for a hazmat rail crash found in FRA’s RAIRS database and HMIRS, or a fatal hazmat truck crash in TIFA and MCMIS. Beyond the inherent advantage in linking hazmat crashes in different databases, additional information is needed to more effectively identify root and contributing causes. Current acci- dent data need to be supplemented by information about the circumstances and conditions that existed before the accident occurred, factors not presently captured. Since these additional pieces of information could come from a variety of sources, the term “information system” and not “database” is used to describe the components and structure of such a system. An example of the value of this approach is an analysis that NTSB performed on grade-crossing accidents. Approximately 60 unprotected private grade-crossing accidents were selected for study, beginning with the information commonly recorded in RAIRS. NTSB gathered additional information by visiting each site, and collecting information that both supplemented RAIRS data and validated on-site conditions listed in RAIRS. NTSB also obtained witness statements from accident sites as soon as possible. None of the information in the witness statements is captured in RAIRS and it is those data that showed driver distractions to be a frequent contributing cause of accidents. The data collected by the NTSB showed that driver grade-crossing visibility was often more limited than documented in RAIRS tables. Had the analysis relied solely on RAIRS data, poor visibility would not have been cited as a major contributing cause for these passive grade-crossing accidents. Although field data collection may be too labor intensive and costly on a recurring basis, this example illustrates the advantages of supplementing data in the databases. Another approach with considerable potential, which is currently being implemented by FRA, is more detailed investigation of a representative sample of accidents. FRA conducts approxi- mately 100 detailed investigations of rail crashes annually. These investigations obtain additional data that are not captured in RAIRS. Using the terminology in this report, approaches taken by NTSB and FRA comprise an infor- mation system for selected accidents. NTSB and FRA investigations illustrate the feasibility of supplementing information contained in current databases to address a specific class of acci- dents, improving the ability to identify contributing and root causes for these classes of accidents. Although site visits and witness statements might be difficult to obtain on a routine basis, clearly, if the FRA chose to target its 100 detailed investigations on a particular class of accidents, addi- tional data could be obtained for those targeted accidents. In successive years, the focus of the detailed investigations could be switched to a different class of accidents. For example, if FRA targeted private grade-crossing accidents for 60 of the detailed investigations, it could have pro- duced a report similar to the one produced by NTSB, concluding that the contributing cause, perhaps even the root cause, of many of the accidents was crossing visibility. 5.2.1 Develop Framework for Identifying Contributing Causes and Root Causes of Hazardous Material Accidents This section focuses on developing an information system capable of capturing the data for thousands of hazmat accidents that occur each year. This information system would not reside in a single database. Rather, the system would use a number of relatable databases, analysis tools, and reports that can, in their totality, contain the information in sufficient detail and quality to identify root and contributing causes of accidents. This would include those databases that are currently used to collect information on hazmat crashes. To identify the root and contributing causes of various classes of accidents, an analyst must be able to relate inventory information to the accident tables. Inventory information character- 96 Hazardous Materials Transportation Incident Data for Root Cause Analysis

izes the hazmat information system, including driver characteristics (e.g., age and experience); hazmat package characteristics (e.g., tank type and age); and vehicle characteristics, carrier char- acteristics, and mileage traveled. With this information, an analyst can mine a dataset and search for the common contributing causes of various classes of hazmat accidents. For example, with- out information on the number of hazmat truck drivers in various age and experience categories, it is impossible to determine those age and experience categories that are over-represented in hazmat accidents. Note that this kind of analysis is appropriate to identify coarse-grained factors that increase risk. For example, the result could be used to determine that older or younger drivers are at higher risk. This should be used with stable characteristics, such as age, vehicle type, and road type, but cannot be used to identify specific errors or transitory conditions that generated a crash, such as a distracted driver or tire failure. Currently, PHMSA is completing Phase I of the Multi Modal Hazmat Intelligence Portal (HIP) system. The system is being designed to acquire hazmat information at a single location. Under HIP, data from FAA, FMCSA, NTSB, the Coast Guard, and PHMSA will be available by carrier, shipper, manufacturer, and packaging company. Only parts of the system, which is being designed for the enforcement staff, will be available to the public. Although FMCSA is supply- ing cargo tank and hazmat compliance reviews as well as inspection results, sharing hazmat crashes in the MCMIS database is not yet part of the system and PHMSA has no immediate plan to incorporate this information into HIP. The incorporation of crash files in the future could enhance system capability. 5.2.2 Availability of Carrier Characteristics Inventory Information for Analysis with Accident Data FMCSA maintains both the MCMIS Census and Crash files. The MCMIS Census file contains inventory information that, if routinely updated and validated, could be useful for identifying which motor carrier characteristics are over-represented in hazmat crashes. A study that made such comparisons for a targeted group of 100 accidents over a one-year period might identify changes to the type of inventory information that should be collected. As a result, a program could be initiated requiring that the new information be obtained when existing carriers re-register and new carriers register for the first time. PHMSA has an annual hazmat carrier registration requirement. These data also could be used to determine which carrier characteristics are being over-represented in hazmat crashes. It is likely that additional information would be required on the vehicle configuration, pack- aging, and driver if one wished to determine whether these characteristics are being over- represented in hazmat accidents. Clearly, changes to the data elements in the current HMIRS and Hazmat Registration file would be required to capture more than carrier inventory data. Note that although privacy issues arise when a driver’s name is tied to age, experience, phys- ical condition, or the extent of injuries, there is no privacy issue if the driver’s name, license number, or Social Security number is not associated with the physical characteristics of the driver. Packaging could be handled in a similar fashion, without disclosing any business- sensitive information. 5.2.3 Add or Modify Inventory Data in Databases This subsection includes specific potential measures for adding inventory data to the system in key locations such as in the major incident databases or supplemental databases such as PHMSA Registration Database or MCMIS Census file. Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes 97

5.2.4 Link Data from HMIRS, MCMIS, RAIRS, and Other Information Sources Existing fields suitable for linking individual hazmat crashes in different databases would be described. Where needed, fields that describe the event location, such as lat/long coordi- nates, street addresses, river and rail mile points, and FIPS codes, could be added and/or better quality controlled (using GIS technology) to facilitate the linking of databases. Common accident identifiers are suggested to encourage data integration, validation, and sharing. For all hazmat truck crashes, the DOT number could be correctly reported and entered into the Crash file. The use of a police report number would be another possibility, for link- ing traffic accidents. To ensure this takes place, a copy of the police report could be submit- ted with the crash report. FIPS codes for all geographic entities (such as states, counties, cities) would be used as available. Time could be entered from the police report. MCMIS also could make sure that the report submitted to the crash file includes the police accident report number. 5.2.5 Develop a System for Each Database That Will Target About 5% of Hazmat Crashes for More Detailed Investigation Ideally, the chosen accidents would be from a common class of accidents. As one potential example, a sample of hazmat crashes involving rollovers of hazmat tanker trucks could be selected for more detailed root cause investigation. Another potential application could be the selection of crashes involving a particular commodity, such as propane, to determine if these accidents are over-represented and, if so, what measures could be developed to decrease both their frequency and severity. A further option could be the selection of hazmat crashes occurring on a particular type of roadway or involving a certain category of driver based on age and experience. Finally, a random sample from all accidents could be selected for further investigation. This approach is already being implemented, although not exclusively for crashes involving haz- mat. FRA currently supplements selected rail accidents in the RAIRS data by about 100 detailed accident investigation reports published annually. The Coast Guard does a few detailed accident investigations, and NTSB investigates almost all air crashes as well as selected serious crashes for other modes. By examining 100 accidents in detail, FRA is able to obtain additional data for acci- dents of interest and thereby probe deeper into the root and contributing causes of those accidents. The FRA example provides a workable framework for investigating the root and contributing causes of hazmat accidents. Similar additional investigations could be undertaken by each agency responsible for a major database. For trucks, a slightly different approach was taken in the Large Truck Crash Causation Study (LTCCS). This study obtained detailed parameters for approximately 1,000 heavy truck accidents. While no attempt was made to use the data in MCMIS or HMIRS, it is an example of a comprehensive approach whose only limitation is that it could not be performed on an annual basis. Although the LTCCS and NTSB reports provide potential models for these investigations, the TIFA framework that provides detailed analyses for all fatal large truck crashes is a more feasible model because it is performed annually, relies on telephone calls to check information, and is less expensive than the LTCCS approach. The Hazardous Materi- als Serious Crash Analysis: Phase 2 (Battelle 2005) applied a similar approach as that used in TIFA on a sample of hazmat crashes found in MCMIS for a particular year. In addition, the project used information for the same crash found in HMIRS wherever possible. 98 Hazardous Materials Transportation Incident Data for Root Cause Analysis

5.3 Improving the Effectiveness of All Databases Required to Identify Root Causes 5.3.1 Ensure Data Completeness and Accuracy Data completeness includes accidents that are not reported as well as accident reports with incomplete data. If the system reports only one-half of the accidents that occurred, then it may take twice as long to obtain a good understanding of how the system responds to a set of changing conditions. Even then, this may not be possible because those accidents that were unreported may not be representative of those that are reported. For example, accident sever- ity, driver, and/or carrier characteristics might differ. Typically, less severe accidents are underreported. This is true whether the cases are self-reported or not. In addition, carriers with poor records are less likely to self-report. This means less safe carriers are less likely to be identified in a timely fashion. Incomplete reports can also have a negative effect on accident analysis since a complete record of cause and effect is not captured. Moreover, when one parameter is not filled out for one accident record and a different parameter is missing in another accident record, the sit- uation is worse than if the same parameter value is not filled in for each accident. When the negative consequences of underreported accidents and incomplete reporting are combined, the ability of an analyst to draw conclusions from the data is significantly compromised. For example, for semitrailer truck accidents with hazmat releases, if only 70% of the accidents are reported and, for those that are reported, only 75% of the truck configurations are known and speed at the time of a crash is populated only 50% of the time, it is virtually impossible to have any confidence in an estimate of the annual number of semitrailer truck hazmat releases in which excess speed is a contributing cause. This is because there would be com- plete data for only about 25% of the accidents that occurred (0.70 × 0.75 × 0.50 = 0.2625). Moreover, there is no assurance that every accident with complete information is represen- tative of the three that are missing. 5.3.2 Complete Values for All Parameters No credible information system can operate using records in which many fields are blank. Parameters are specified in a database because they can be collected and are important to collect. Seemingly unimportant parameters are essential for specifying the causal chain of events or char- acterizing the circumstances of the event. For any database incorporated into the proposed information system, required fields should not be left blank. In some instances, it may be necessary to provide an estimate of the appro- priate data entry. Some databases allow for this, but maintain a code to distinguish between measured and estimated values. This type of information is valuable for parameters that change as a result of the accident sequence, such as speed. Although the code for “unknown” will always be an option, it should be used only if it is truly impossible to estimate a value for one of the required parameters. Often, an estimate is good enough, since categories are gen- erally aggregated for analysis. Techniques would need to be implemented for ensuring that information required for the data fields is both collected and correctly entered into the database. For example, the overwhelm- ing majority of truck carriers surveyed believe that PHMSA should contact carriers to collect data for fields that are incomplete. Some techniques that could be implemented by database man- agers include the following: • Computerize data collection to enforce and validate data coding. • Create required fields that will not accept the record until those fields are complete. Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes 99

• Develop incentives that will reward those that provide complete and accurate data into a data- base. For example, for states, a system could be developed to provide feedback in the form of crash data for the state. Or for carriers, data could be provided that defines how a company compares to its competitors. 5.3.2.1 Add Latitude and Longitude Add latitude and longitude to all databases to provide the exact location of a hazmat crash and enable the identification of the same accident when it appears in more than one database. This would facilitate linkages between databases where information on the same crash is com- pared and also would aid in obtaining site-specific information associated with a particular location. 5.3.2.2 Add a Specific Description of the Hazmat A specific hazmat description could be added to the database and would include the type or hazmat class identified on the placard and/or shipping papers, name of the chemical being trans- ported, quantity being transported, and—if there is a spill—the quantity spilled. Adding this information will provide significantly more detail on the hazmat being shipped and make the database more valuable for identifying root causes of hazmat crashes. 5.3.2.3 Electronic Submission of All Crash Reports to the Major Databases Using the Web to Facilitate Accuracy All crash reports could be submitted electronically using the web to facilitate accuracy. Cur- rently, information is submitted from the states using the SafetyNet System. Although this approach is undoubtedly fixed for the near future, the electronic submission of the complete police accident reports (PARs), including truck and hazmat supplements, to the states could reduce the opportunity for error when the information is entered into SafetyNet. Similarly, if HMIRS reports were submitted using a web interface, an added source of errors would be removed by eliminating one data transfer step. In addition, an automated system could be devel- oped to check the forms for completeness and identify incorrect coding. 5.3.2.4 Add “Error Trapping” “Error trapping” could be applied to all databases in order to eliminate errors by applying a program that would test whether certain logical connections have been made within the same accident record. One example of an error that could be eliminated is a situation where a travel speed of 40 mph is listed for a crash associated with a truck backing into a loading dock. Another example of a “logical inconsistency” could involve an accident where a single-truck cargo tank is reported to have lost 20,000 gallons of a hazmat liquid. The error-trapping pro- gram would flag this spill size as erroneous because it is inconsistent with realistic truck cargo tank capacities. 5.3.2.5 Increase State Checks of the Quality of Hazmat Crash Submittals to FMCSA As part of their reporting obligation, each state could quality-check reports for all hazmat crashes in MCMIS. States could read the reports, complete missing fields, and make any needed corrections before submittal to FMCSA. This step would increase the reliability of the MCMIS Crash file. As the use of electronic submissions becomes the norm at all levels, states could be encouraged to develop translational programs that automatically populate the fields in the MCMIS Crash file from the electronic entries in the PARs, thereby eliminat- ing translation errors and the need to check for such translation errors between the PAR and the MCMIS Crash file. States with demonstrated higher quality submittals might be rewarded. 100 Hazardous Materials Transportation Incident Data for Root Cause Analysis

5.3.2.6 Ensure that the Databases’ MCMIS Report Number for Serious Hazmat Crashes Can Be Linked to the PAR Agencies checking the quality of MCMIS crash reports should be able to link the PARs with the MCMIS report. Including the PAR number in all MCMIS hazmat crash reports would allow the PAR associated with each crash to be easily identified and quickly retrieved. Currently, in many states this is a time-consuming manual process that could be easily remedied if the PAR number was referenced in the MCMIS Crash file and the PAR was electronically retrievable. Linking the MCMIS report number to the PAR could be a suggestion for police reports and require the following: • States could be encouraged to automate collecting standard administrative data as much as possible since MCMIS data are extracted from police reports. • Include non-spill hazmat crashes in HMIRS for all “serious crashes” involving placarded shipments. • Include digital photos of the accident scene in all of the major databases. • For truck carriers in MCMIS and HMIRS, include carrier out-of-service (OOS) rate per mil- lion miles. MCMIS inspection data could be able to determine the count of OOS vehicles for a carrier. Could then be normalized by the VMT estimate in the Census file. • For HMIRS and MCMIS, include violations for drivers during the crash. • Involve other parties such as emergency responders and insurance companies in data collec- tion and reporting. In HMIRS, the IEVENT Table could be used to capture remarks made by multiple individuals. 5.3.2.7 Include All Applicable Hazmat Accidents Each database should include a process for ensuring that all hazmat accidents that meet the specifications for inclusion are recorded. In order to accomplish this objective, agencies manag- ing these databases could consider the following: • Conduct training for carriers and police in how to complete accident reports. For truck acci- dents reported to MCMIS, because there are tens of thousands of different police officers fill- ing out PARs each year and individuals from more than 50 states and territories filing crash reports, Web-based training is likely to be the most cost-effective method of delivering such training. Although the situation is simpler for other modes (e.g., rail and barge) because fewer individuals are responsible for compiling and reporting crash data, Web-based training might be cost effective for these individuals as well. • Develop more efficient systems for entering data at the accident scene, such as greater depen- dence on electronic data entry and use of bar codes. • Review news reports of hazmat accidents to identify those that should have been included in the database. Investigate the techniques used by financial news reporting services to automatically flag newsworthy statements made by company officials and reported in news reports. • Check PARs to identify those accidents that should be included. For truck transport, this would be greatly facilitated if PARs were available electronically, thereby making the identifi- cation of reportable crashes more accurate and uniform. • Provide incentives to states to verify that all hazmat truck crashes that should be reported have been included in crash databases. One suggested project would be to establish a multi-agency task force to identify all hazmat accidents that meet the reporting threshold, considering all modes of transport. The project would perform the searches listed above and compare the results with HMIRS, FARS, RAIRS, and MCMIS, as appropriate for the mode. The outcome would come close to being a census of hazmat accidents. This census could then be used by HMIRS, FARS, MCMIS, and RAIRS as a Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes 101

measuring tool to determine their respective completeness. It could also provide the sampling frame for in-depth investigations as suggested in this subsection. 5.3.2.8 Ensure Accuracy and Consistency of All Data Entered into the Databases Reporting incorrect data can make it impossible to identify causal relationships, even with an infinite amount of data. Thousands of vehicles might experience the same initiating event and correct for it without incident. The next vehicle might experience the same initiating event and, through a series of unique conditions, be unable to correct for the initiating event. If these unique conditions are not accurately recorded, then the true cause(s) will never be identified. Potential measures for ensuring data accuracy fall into the following categories: 1. Include parameters that are directly measurable such as how far from the roadway a vehi- cle was after a crash or parameters that are directly observable, such as whether it was dark or light. Such parameters should be recorded with high accuracy. 2. Include event data recorders on hazmat transporters. Hazmat vehicles are a good test bed for these devices. Knowing vehicle parameters for the 5 seconds prior to a crash would be invaluable. Just knowing the vehicle speed, when the brakes were applied, and with what force the brakes were applied would be insightful. 3. Record parameters that occurred before or during an accident and could be objectively described but are no longer apparent to the accident reporter. An example of this type of parameter could be an accident that occurred as a result of a white-out condition that is no longer present at the accident scene. 4. Include parameters that are based on highly subjective witness statements. Police officers are highly trained to recognize unusual driver behavior and these subjective observations should be recorded. The identification of contributing causes falls into this class of recorded information. 5. Record parameters that become available some time after the accident. Investigating offi- cers will frequently require a driver submit to a drug test when impaired performance is sus- pected. Even though this information is not available for several weeks, such information can be obtained and is routinely captured in the TIFA database. Other accident databases could adopt the TIFA procedures for capturing this information. 5.3.2.9 Place All Components of the Proposed Information System Under a Quality Assurance Program A process should be implemented that provides periodic reports stating the accuracy of the data entry process. The program could include the following measures: 1. A consistent data dictionary that provides accurate definitions of the parameters such that two individuals, when assessing the same accident, would fill in the same cause codes (where multiple interpretations are possible, the question/answer format adopted in RAIRS provides an effective means to ensure more consistent reporting); 2. Consistent PAR forms that contain the minimum amount of data required to identify root causes; 3. Training for individuals responsible for completing PARs or reports for HMIRS and MCMIS. As stated previously, since an individual might only need to fill out a report once every few years, Web-based training that could be accessed to assist the reporting official might be a very cost-effective training tool; and 4. A data checking procedure to ensure quality control of information using such techniques as: • Checking a sample of all data submitted and entered into the database, • Making telephone calls to participants for a sample of accidents, • Comparing reports with press accounts of hazmat crashes, and • Carefully reviewing the database to identify inaccuracies and inconsistencies. 102 Hazardous Materials Transportation Incident Data for Root Cause Analysis

5.3.2.10 Data Breadth This section covers the type of data breadth required to upgrade the system. This is difficult to specify because it depends on the type of analysis that must be performed to get to the root cause of a class of accidents. There is not, a priori, an assumption that can be made regarding what information is important since this relates to the contributing causes. 5.3.2.10.1 Data Breadth for Trucks. For trucks, basic data may be needed in one of five areas including vehicle, driver, packaging, infrastructure, and situational. Table 5-1, adapted from the Hazardous Materials Serious Crash Analysis: Phase 2 (Battelle 2005), can be used to insure that there is no missing data in each of the five areas. 5.3.2.10.2 Data Breadth for Trains. For trains, basic data may be needed in one of five areas including train consist, engineer/crew, packaging/hazmat, track type, and situational. 5.3.2.10.3 Data Breadth for Water Carriers. For water carriers, basic data may be needed in one of five areas including barge or vessel type, captain/crew, cargo configuration/hazmat, waterway, and situational. 5.4 Potential Measures for Improving Capability of Specific Databases to Identify Root Causes 5.4.1 Potential Measures for MCMIS The following potential measures apply to enhancing the ability of MCMIS to identify root causes of hazmat accidents. 5.4.1.1 Provide Training in Completing Reports for Carriers and Police The goal of this effort would be to improve the reliability of the MCMIS database by provid- ing targeted training for those individuals responsible for submitting accident reports. The source of MCMIS data is the PARs that are completed by police officers. The most effective method for improving the quality of PARs would be to develop an online training package that provides police departments with guidance for investigating a crash and completing the PAR for serious hazmat crashes. The California Highway Patrol’s Collision Investigation Manual could serve as a model for developing these materials. Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes 103 Vehicle Driver PackagingHazmat Infrastructure Situational Configuration Age Package Type Hazardous Material Road Surface Pre-Crash Condition Cargo Body Experience Quantity Shipped Road Condition Dangerous Event GVW Condition Quantity Lost Road Type Vehicle Speed Vehicle Defect Valid License Age (Cargo Tank) Traffic Way Impact Location Vehicle Response Citation Issued Rollover Protection Access Control Primary Reason Response Inspection History Speed Limit Accident Type Training Design Specification No. of Lanes Weather Condition Location Light Condition Time of Day Health Consequence Table 5-1. Accident parameters.

5.4.1.2 Complete All Parameter Fields Fully completed MCMIS parameter fields offer the potential for the single biggest improve- ment in MCMIS crash reporting. Some fields could be required to be filled out before an acci- dent record can be uploaded, particularly those related to the vehicle, carrier, driver, route characteristics, and point of contact information. • Complete Driver Condition Field Since 2004, the DRIVER_CONDITION_CODE field has been left blank. In Hazardous Materi- als Serious Crash Analysis: Phase 2 (Battelle 2005), the code “Appeared Normal” was the com- mon entry for about 94% of the vehicle crash records. Being able to flag those 6% for more detailed study might result in improved driver performance not only for the 6% identified but for some of the 94% that appeared normal but, in fact, were impaired. Since this is the only field that captures driver performance in MCMIS, it is suggested that this field be filled out again. • Complete Hazmat Fields All five hazmat fields should be completely and accurately filled out for accidents involving trucks carrying hazmat. As described in Section 4.1, this is often not accomplished. If two fields must be filled out for a consistency check, this can occur in only 32% of the cases—the acci- dents where four or five of the fields are filled out. Furthermore, for the 32% of the cases where two or more descriptive fields are filled out, the entries are often inconsistent, making it difficult to accurately determine even the class of hazardous material being transported. Although it is normally possible to identify the name of the hazardous material from the data reported in the VEHICLE_HAZMAT_MATERIAL field, it should be noted that in either the recording of the information or in the electronic transmission of the data, the field is often being truncated. Bar codes could be used to supplement placards to supply the police officer with accurate data on the carrier, vehicle, driver, and type of hazardous material. These data could be read easily with an inexpensive hand-held bar code reader then transferred to a police officer’s com- puter or printed and attached to the PAR. The use of radio frequency identification (RFID) tags on all large trucks transporting the most dangerous hazmat, such as TIH and explosives, should be considered. Information in the tags could include the driver, vehicle, hazmat cargo, carrier, and vehicle. This system would improve the accuracy of police reporting and also provide a valuable tool for emergency responders to identify hazmat remotely. • Specify the Location Accurately The location field should be specified in a manner that enables the accident location to be found on a map. Presently, the accident location can be found on a map for about 30% of the crashes. Specifying the route number or street name followed by the longitude and latitude would appear to be a straight-forward way to register the location. The difficulty in identifying the accident location on a map is exasperated by truncation errors occurring somewhere in the recording or record transmission process, thereby eliminating key information in the LOCATION field. • Provide State Personnel Access to Other Key Data State personnel entering the data into the MCMIS crash record system should have access to databases containing related information, such as the MCMIS Registration file and the 49 CFR Part 172 Hazardous Material Table. Having access to such files would enable state personnel to perform a quality control check on the hazmat entries and fill in any information missing from the PAR. Linking the data entry process with these, and other, files would make it easier to accurately populate fields in the MCMIS Crash file. • Ensure that the MCMIS Report Number Be Linked to the PAR Agencies checking the quality of MCMIS crash reports should be able to easily link the PARs with the MCMIS report. Therefore, it is suggested that the PAR number be included 104 Hazardous Materials Transportation Incident Data for Root Cause Analysis

in all MCMIS hazmat crash reports. FMCSA could restore the rule for how the REPORT_ NUMBER field is constructed. Prior to 2001, states were instructed to use the PAR num- ber in the REPORT_NUMBER field. Although that rule is no longer required, some states embed the PAR number in the REPORT_NUMBER field. The PAR number of a crash would permit a hard link to a specific crash and not only provide more definite access to the PAR, but it would also facilitate linkages to crashes found in other databases such as HMIRS. 5.4.1.3 Add Data on Pre-Crash Conditions Pre-crash data concerning the driver and the vehicle would be entered into SafetyNet by the states. Driver information would include the driver’s safety, violation, and health records. Vehi- cle information would include vehicle defects discovered at the scene. At the very least, for a crash involving hazmat, a Level I inspection would be conducted at the scene or another location, with special attention to such defects as brake adjustment and tire condition. In addition, information about the vehicle’s maintenance history could be provided. This may simply reflect that the main- tenance records were current and required maintenance had been conducted. This is considered a long-term measure. At present, this information could be obtained for targeted accidents, say 100 per year as FRA does currently. If it is shown to be cost effective, the number of targeted acci- dents could be expanded over time. 5.4.1.4 Enhance the MCMIS Crash File Data Dictionary The MCMIS data dictionary could be enhanced so that it contains not only the definition of a parameter and the format for the field in the database, but also the format of the data to be entered. Specifying the format in the database does not necessarily define the data entry format as evidenced by the current dataset. A section answering some commonly asked questions would be valuable as well. For instance, if the PAR lists the carrier location as one of the carrier’s freight depots, should that address be entered in the MCMIS Crash file or should the address of the carrier’s home office, taken from the MCMIS Registration file, be entered? Another consideration might be related to the choice of entering a street address or a postal box number. Another example is whether an Interstate route should be designated as I-70, IR70, I070, I70, or some other format. If the use of longitude and latitude when specifying the location is adopted, then the format and accuracy also should be specified. If the coordinates were expressed in decimal degrees, then specifying the longitude and latitude to two decimal places would place the accident on a high- way, yet if specified to three decimal points the location would be shown as either being on the left- or right-hand side of the right-of-way. 5.4.2 Potential Measures for HMIRS The following potential measures apply to enhancing the ability of HMIRS to identify root causes of hazmat accidents. • Provide Training for Carriers Training in completion of the 5800.1 report should be provided to carriers. Included in the course would be a unit on root cause identification. Some of the training elements given to NTSB inspectors could form the basis for this training unit. The course would be presented in a webinar format, comprised of two four-hour sessions. • Use Drop Down Lists HMIRS could use drop down lists for such data as place, carrier name, vehicle type, container type, and hazmat type. This would prevent unneeded mistakes resulting from different inter- pretations of particular spelling. Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes 105

• Include a Copy of the PAR with Reports Carriers would submit a copy of the PAR for any HMIRS reportable traffic accidents. This provides another tool for PHMSA to confirm the accuracy of material in the 5800.1 report. PHMSA could check the carrier’s report against the PAR to identify inconsistencies. These inconsistencies could be sent to the carrier for confirmation or clarification. Changes to the 5800.1 report could be made where needed. • Ensure that Filers Fix Incorrect Data Before the Submission Is Accepted In FY09, PHMSA will introduce an online Incident Reporting System that will require filers to fix incorrect data before the submission will be accepted. However, since the carriers will also be able to file the reports via other methods, the effectiveness of these checks will be lim- ited to electronically submitted reports. • Include Non-Spill Hazmat Crashes in HMIRS Most serious crashes are potential spills even if none occurs. Therefore by including all of these “serious crashes” involving placarded shipments, officials analyzing the crash data in HMIRS will be able to more effectively determine root causes. The definition FMCSA uses for the inclusion of a crash in the MCMIS database could be applied to all non-spill hazmat crashes that are not currently included among the incidents that must be reported to HMIRS. By including non-spills, PHMSA would be able to provide data on “successes”; that is, what worked well in the hazmat transportation system. For example, if a particular packaging was involved in multiple rollover crashes and resulted in fewer spills than another packaging, this information could provide valuable evidence for use of a particular packaging type. The recent requirement that Type C accidents be reported is a step in this direction, showing that it is considered feasible to include such non-spill accidents in the database. • Encourage Carriers to Enter Multiple Hazardous Materials in the 5800.1 Form Carriers sometimes carry more than one hazardous material. This is true for less than truck- load cargo shipments. Therefore, carriers can easily enter this information in the 5800.1 report sent to PHMSA. Many do not break the information down, making it impossible to distin- guish good and poor package behavior. • Send All Reports to the Carrier for Confirmation A report could be generated automatically after data are entered into HMIRS and a letter or email sent to the reporting carrier to confirm the data. A certain amount of time, such as one month, could be used to allow the carrier to check the accuracy of their submittal and to add information their internal investigations may have discovered. PHMSA could change the con- tent of the 5800.1 report, if required. • Subject Crashes That Meet a Certain Threshold to Follow-Up Audits All crashes involving certain classes of hazardous materials could be subject to a more detailed PHMSA audit. The audit would thoroughly check the accuracy and completeness of the acci- dent description and collect additional information where required. Specific material types with a certain hazard threshold could be selected for this audit. For example, the hierarchy below could be followed with the top of the list having the highest priority for audit. – Class 1: explosives, – Class 7: radioactive, – Class 6.2: infectious substances, – Classes 2.3 and 6.1: toxic inhalation hazard (TIH), – Class 2.1: flammable gas, – Class 3: flammable liquid, – Class 4: dangerous when wet, and – Class 5: oxidizer. • Provide a DOT Number for All Reports A DOT number should be reported in all HMIRS records for en route accidents. This will facilitate matching information on the same crash in other databases. 106 Hazardous Materials Transportation Incident Data for Root Cause Analysis

• Verify Carrier Names An additional quality assurance check could be performed to verify that the name being entered corresponds to the name provided on the annual PHMSA registration form. This may be already being done but was not mentioned at the time of interviews with officials. • Include the Number of Power Units and Drivers For HMIRS, the number of power units and drivers could be included as data elements. All carriers reporting to HMIRS should be in the DOT Census file, so the number of power units and drivers could be extracted from there. This information provides an indication of carrier size that may reflect on the carrier’s ability to complete the 5800.1 report. • Ensure Package Failure Entries Are Complete PKGFAIL entries should be filled out for all reports submitted to PHMSA. If incomplete, the report would be returned to the carrier for completion of the information and submitted either by phone or e-mail. • Continue to Emphasize the Importance of New Reporting Requirements for Damage to Lading and Lading Protection Systems The new requirement that carriers must file a 5800.1 form following an accident if there was damage to lading and lading protection systems on a cargo tank of 1,000 gallons or greater, even if there is no loss of hazardous material, could be emphasized. This is the new requirement to report Class C accidents. Such a notice might be given to carriers when they are informed that their annual hazmat registration application has been reviewed and approved. (This measure would be superseded if all non-spill hazmat accidents were reported in HMIRS.) 5.4.3 Potential Measures for TIFA 5.4.3.1 Potential Measures for Additional Fields Although the TIFA survey adds valuable detail to the FARS data, additional data fields could add important detail about hazmat packaging and also enhance the information available on crash causation. Some elements could be added with little modification of the program. Others would take additional resources, but are nevertheless possible. • Right of way could identify which vehicle, if any, within a crash had the right of way prior to the collision. This could be coded readily from the PAR in most cases. Some state crash reports already include right of way. Right of way would be useful in identifying the vehicle that pri- marily contributed to the crash. • Critical event is a field that identifies and describes the event that precipitated the crash. This field is included in both the GES and CDS files. Coding manuals are available and could be used to ensure that coding is consistent with NCSA standards. • The managers of the TIFA survey might also consider adding a critical reason field. Critical reason captures the “reason” for the critical event, classified broadly as driver, vehicle, or envi- ronment, with detailed levels under each. This variable is useful for identifying the immedi- ate failure that led to the crash and would shed light on crash causation. The field was used in the Large Truck Crash Causation Study (LTCCS) and in the National Motor Vehicle Crash Causation Survey (NMVCCS). Therefore, coding procedures are available. The suggestion to add critical reason to TIFA is tentative, however, as it is not clear whether the TIFA protocol can uncover this information. • The TIFA program could also add additional information about hazmat cargo, in particular – MC number of the cargo tank. This information has been collected in the past as part of a special data collection, so the feasibility of collecting this information has been demonstrated. – Quantity of hazmat transported. Cargo weight could be added back to the survey. The program should consider capturing the quantity in terms of liquid measure, where appropriate. Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes 107

5.4.3.2 Potential Measures to Improve Data Quality The TIFA system is complete and mature. It is subject to annual review and adjustment, including continuing training of the coders. However, greater cooperation with the FARS pro- gram could probably help to increase the accuracy with which trucks are identified. 5.4.3.3 Compatibility with Other Databases The comments previously associated with the FARS data apply equally to TIFA, since TIFA uses the same case number system. However, there is an additional constraint on linking the TIFA file to other data systems, in that it raises a risk of identifying specific individuals or orga- nizations. The TIFA program is bound by commitments to respondents to protect their identity, and by the terms of its operations under the University of Michigan’s Institutional Review Board (IRB). Thus, any effort to link the data to other data systems would be unlikely to be allowed. 5.4.4 Potential Measures for RAIRS For rail transport of hazardous materials, Item 1, and to a substantial extent Item 2, are fairly well developed, thanks to a combination of company, industry, and government programs. The requirement that railroads provide the reporting mark and number of all cars involved in releasing hazmat and the quantity released is useful because this facilitates acquisition of more infor- mation about the design of the car via the AAR’s Universal Machine Language Equipment Register (UMLER) database. An audit of the 2007 FRA data found that for all of the hazmat cars that the Class 1 railroads indicated had released hazardous materials, they provided the required informa- tion for all but one that they indicated had released product. The single discrepancy was a case in which a railroad indicated two cars had released product, but only one car was identified. It is not possible to determine which was incorrect, the number of cars that actually released hazardous materials in the accident, or if a second car’s identity and information should have been provided. The same level of compliance was not evident for the non-Class 1 railroads. However, non-Class 1 railroads are responsible for a much smaller percentage of the hazmat cars that release in accidents so the impact of these on overall data completeness is much less. The value of this requirement could be considerably enhanced in terms of root cause analysis if the following changes were made with regard to reporting mark, car number, and identification of the commodity being transported: 1. Provision of the reporting mark and number of all derailed cars of any type; 2. Provision of the commodity, reporting mark, and car number for all derailed cars placarded as transporting hazardous materials; 3. Provision of the commodity, reporting mark, car number, and quantity released for all tank cars, whether or not they are transporting hazardous material; and 4. Provision of the same information called for in No. 3 for all intermodal, portable tanks being transported on cars that derail, along with the reporting mark and number of the railcar transporting them. The reasoning for each is as follows: • Knowledge of all derailing cars would provide the all-important “denominator” data needed to establish normalized rates of failure for various railcars and their critical design elements. It does little good to know if 10 times as many of one car type release compared to another if one does not know if there were 10 times as many cars of the former type being transported compared to the latter. • Although tank cars transport the majority of hazardous materials, covered hoppers, boxcars, and intermodal cars transport significant quantities as well. It is useful to be able to distinguish the performance of different car types in accidents, which implementing these potential meas- ures would allow. 108 Hazardous Materials Transportation Incident Data for Root Cause Analysis

• Tank cars used to transport some non-regulated materials are often identical to cars transport- ing certain regulated materials. Knowledge of their exposure to accidents and performance in accidents will substantially improve the robustness of the data, and consequent confidence in, and accuracy of, the statistics pertaining to tank cars of similar design that are used to transport hazardous materials. • Development of information on intermodal portable tanks (isotainers) is needed to understand their performance in accidents and strengths and weaknesses in their damage-resistant design. This could be achieved in a manner analogous to the understanding that has developed during the past 38 years of studying railway tank cars. This mode of bulk transport is expanding, espe- cially in the area of import and export of hazardous materials. Recording the information described in this subsection will provide a basis for development of such statistics. Although the information presented in this subsection is not all that is needed for improved root cause analysis of rail transport of hazardous materials, in combination with detailed data on equip- ment design recorded by the railroads in the Universal Machine Language Equipment Register (UMLER) and the data on releases recorded by PHMSA in HMIRS, it would substantially strengthen our understanding of the factors affecting railcar performance and failure modes in accidents. 5.5 Conclusions The research conducted under this project has demonstrated that there has been considerable progress during the past 20 years in the development and refinement of databases that include haz- mat accidents. The project focused on identifying potential measures for improving the identifica- tion of the root causes of hazmat accidents using these databases. The project findings have provided researchers and officials with an overview and analysis of the individual databases and resulted in many potential measures for improving specific databases. However, implementation of the major measures—including establishing an information system, linking databases to take advantage of accident descriptions in more than one database, performing detailed sampling of a specific set of crashes to assemble more detailed information, and the adoption of techniques to improve data quality and completeness—could yield the greatest improvements in the ability of interested parties to conduct root cause analysis. This, in turn, would enable officials to identify problems for which a solution or mitigation will result in an improvement in hazmat shipment safety. 5.6 Follow-On Project If implemented, the findings of this report could lead to the enhanced identification of root and contributing causes of hazmat crashes. The implementation of the potential measures that were identified will likely present both technical and institutional challenges. Consequently, the project team also suggests that in order to evaluate the feasibility, usefulness, and costs of implementation, a pilot program be implemented to demonstrate that the system will work effectively in identify- ing root causes. The team suggests that the pilot test focus on truck hazmat accidents and involve linking the HMIRS database, which provides excellent data on the hazmat material and package, with the MCMIS database, which provides superior data on the driver and accident environment. To supplement the data found in the two databases, the pilot program could link at least 100 crashes and supplement the data primarily by telephoning carriers and other key sources such as police officers and tow truck drivers. The pilot project would select the sample of hazmat crashes based on a set of consistent criteria for a similar group of crashes such as hazmat truck rollovers. The pilot study would also document the costs associated with linking the two databases, identifying the sample for more detailed data collection, and the actual collection of the additional data through telephone contacts and other methods. Finally, the pilot test could use the hazmat crash data to demonstrate the system’s ability to identify root cause and analyze the results from a number of crashes to pinpoint areas where suggestions can be made to improve hazmat safety. Potential Measures for Improving the Identification of Root Causes for Hazardous Materials Crashes 109

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TRB’s Hazardous Materials Cooperative Research Program (HMCRP) Report 1: Hazardous Materials Transportation Incident Data for Root Cause Analysis examines potential technical improvements to hazardous materials accident databases that are collected and managed by various agencies. The report explores gaps and redundancies in reporting requirements and attempts to estimate the extent of the under-reporting of serious incidents.

Appendixes A through E to HMCRP 1 are available online.

Appendix A: Questionnaires

Appendix B: Questionnaire Results for Carriers and Database Administrators

Appendix C: Brief Summary of the 2005 MCMIS Crash Records

Appendix D: The Percent of Missing Data for Variables from TIFA/FARS, 1999–2004

Appendix E: Selected Analyses Performed with the Hazmat Accident Database

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