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Database Analysis 61 and indicate that the carriers have done enough accident investigation to identify some changes that would decrease the frequency of similar accidents in the future. The usefulness of this infor- mation would be greatly improved if a cause table, similar to the WHAT FAILED Table, was devel- oped so the carrier could list some contributory causes from a pick list. Although there might be some resistance to adding that field because of liability issues, moving toward being able to rou- tinely list contributing causes would be helpful. 22.214.171.124 Potential Measures for Improving Root Cause Analysis The following potential measures would enhance the ability of HMIRS to identify the root causes of hazmat accidents. 1. Require that the DOT number be a mandatory input for all reports filed with PHMSA for en route incidents. 2. Perform an additional Q/A check on carrier names to verify that the name being entered cor- responds to the name provided on the annual PHMSA Registration form. 3. Require PKGFAIL entries to be filled out for all reports submitted to PHMSA. 4. Continue to emphasize 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 cargo tanks of 1,000 gal- lons or greater, even though there is no loss of hazardous material. This is the new requirement to report Class C accidents. Such a notice might be given to carriers when PHMSA notifies them that it has received and approved their annual hazmat registration application. 5. Capture driver condition information without compromising the confidentiality of the driver. The following design option from MCMIS can be enhanced for use in HMIRS. Based on analysis of the data, the list of options can be enhanced by using the following driver con- dition categories: 1 = Appeared Normal, 2 = Had Been Drinking, 3 = Illegal Drug Use, 4 = Sick, 5 = Fatigue, 6 = Asleep, 7 = Medication, and 8 = Unknown. The project team believes that adopting the potential measures above would decrease errors in data entry and make it easier to query the database for potential causes of accidents. 4.3 Fatality Analysis Reporting System (FARS) This section briefly describes the FARS file. Since the TIFA database incorporates the FARS records for trucks involved in fatal accidents, to avoid a fragmented analysis, much of the detailed evaluation is covered in Section 4.4, which describes TIFA. The FARS file is the primary national crash data file for fatal traffic accidents. It is a census of all fatal motor vehicle traffic crashes. The TIFA file covers all medium and heavy trucks involved in a fatal crash, and includes virtually all FARS variables for the crash, vehicle, and driver. TIFA survey data supplements FARS data for trucks (hereafter the word "trucks" will be used to refer to medium and heavy trucks, i.e., trucks with a gross vehicle weight rating [GVWR] over 10,000 lbs). The TIFA data include a more accurate identification and descrip- tion of trucks in fatal crashes, along with details about the cargo, configuration, motor carrier operating the vehicle, and crash type.