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HMCRP Report 1: Hazardous Materials Transportation Incident Data for Root Cause Analysis (2009)
Hazardous Material Cooperative Research Program (HMCRP)

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Transportation Research Board. "3.4.1 Interviews with Agencies Maintaining Databases (PHMSA)." HMCRP Report 1: Hazardous Materials Transportation Incident Data for Root Cause Analysis. Washington, DC: The National Academies Press, 2009.

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Page
28
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Page
28
Front Matter (R1-R11)
Summary (1-8)
1.1 Project Purpose (9-9)
1.2.1 Literature Review (10-10)
1.2.3 Analysis of Databases (11-11)
1.3 Effective Methods to Ensure High-Quality Data (12-12)
1.4 Potential Measures to Enhance the Ability of Databases to Identify the Root Causes of Hazmat Crashes (13-13)
2.2.1 Rail Equipment - Train Accident Data (14-14)
2.2.2 Project 5 Overview - Developing Common Data on Accident Circumstances (15-15)
2.2.4 Transportation Research Circular 231: Truck Accident Data Systems: State-of-the-Art Report (16-16)
2.2.6 The Human Factors Analysis and Classification System - HFACS (17-17)
2.2.9 Highway Safety: Further Opportunities Exist to Improve Data on Crashes Involving Commercial Motor Vehicles (18-18)
2.2.11 Comprehensive Safety Analysis 2010: 2006 Listening Session (19-19)
2.2.16 Hazardous Materials Serious Crash Analysis: Phase 2 (20-20)
2.3 Summary of Findings and Implications (21-21)
2.3.2 Solutions Being Implemented or Under Consideration (22-22)
3.1 Introduction (23-23)
3.2 Summary of Responses from Carriers (24-24)
3.2.1 Carrier Satisfaction with HMIRS (25-25)
3.3.1 Shipper 1 (26-26)
3.3.2 Shipper 2 (27-27)
3.4.1 Interviews with Agencies Maintaining Databases (PHMSA) (28-28)
3.4.2 Interviews with Agencies Maintaining Databases (FMCSA) (29-29)
3.4.3 Interviews with Agencies Maintaining Databases (FRA) (30-30)
3.5 Summary of Findings from Interviews (31-31)
4.1.1 MCMIS Database Description (32-32)
4.1.3 Database Format (33-33)
4.1.6 Types of Fields Covered (34-34)
4.1.7 Database Purpose and Function (35-35)
4.1.10 Accuracy and Completeness of Data (36-36)
4.1.11 Identification of Hazmat Incidents in MCMIS (37-41)
4.1.12 Quality Control Process (42-42)
4.1.13 Interconnectivity with Other Databases (43-43)
4.1.14 Analyses Using Database (44-44)
4.1.15 Summary and Potential Measures for Improving Root Cause Analysis (45-45)
4.2 Hazardous Materials Incident Reporting System (HMIRS) (46-46)
4.2.1 Database Description (47-48)
4.2.3 Data Collection (49-49)
4.2.5 Accuracy and Completeness of Data (50-53)
4.2.8 Analyses Using Database (54-59)
4.2.9 Summary and Potential Measures for Improving Root Cause Analysis (60-60)
4.3 Fatality Analysis Reporting System (FARS) (61-61)
4.3.4 Types of Hazmat Data Included (62-62)
4.3.6 Data Quality (63-63)
4.3.7 Additional Fields (64-64)
4.3.9 Compatibility with Other Databases (65-65)
4.4.4 Types of Hazmat Data Included (66-66)
4.4.5 Usefulness of the Data for Determining Root Causes (67-70)
4.4.7 Additional Fields (71-71)
4.4.10 Data Uses (72-72)
4.5.1 Database Description (73-73)
4.5.3 Data Collection (74-74)
4.5.7 Interconnectivity with Other Databases (75-75)
4.5.8 Analyses Using Database (76-77)
4.5.9 Summary and Potential Measures to Improve Root Cause Analysis (78-78)
4.6 Railroad Accident/Incident Reporting System (RAIRS) (79-79)
4.6.1 Track, Roadbed, and Structures (80-80)
4.6.3 Mechanical and Electrical Failures (81-81)
4.6.5 Summary of Causes and Impact (82-83)
4.7.3 Data Collection (84-84)
4.7.5 Accuracy and Completeness (85-85)
4.8.1 Scope of Investigations (86-86)
4.8.2 Approach to Identifying Root Causes (87-87)
4.8.4 Data Quality (88-88)
4.8.5 Probable Cause Findings (89-89)
4.8.6 Summary (90-90)
4.9.1 Introduction (91-91)
4.9.4 Populating Records and Improving Data Quality (92-92)
4.9.6 Database Enhancements and Limitations (93-93)
4.9.7 Summary (94-94)
5.2 Information System Development (95-95)
5.2.1 Develop Framework for Identifying Contributing Causes and Root Causes of Hazardous Material Accidents (96-96)
5.2.3 Add or Modify Inventory Data in Databases (97-97)
5.2.5 Develop a System for Each Database That Will Target About 5% of Hazmat Crashes for More Detailed Investigation (98-98)
5.3.2 Complete Values for All Parameters (99-102)
5.4.1 Potential Measures for MCMIS (103-104)
5.4.2 Potential Measures for HMIRS (105-106)
5.4.3 Potential Measures for TIFA (107-107)
5.4.4 Potential Measures for RAIRS (108-108)
5.6 Follow-On Project (109-109)
References (110-111)
Appendices (112-112)
Abbreviations used without definitions in TRB publications (113-113)

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28 Hazardous Materials Transportation Incident Data for Root Cause Analysis Regarding ways to improve HMIRS, Shipper 2 believes that the highest priority should be to make the data contained therein more accurate and consistent, only adding more reporting ele- ments if they have a direct connection to establishing root cause. Improved accuracy could per- haps be accomplished by having PHMSA request that the reporting entity update the HMIRS record after a certain amount of time has elapsed since the date of the accident. Techniques to improve data consistency might be to utilize tools that facilitate more automated data entry (e.g., Web-based data entry) and to employ checks and balances in judging whether reported infor- mation makes logical sense. Part of the problem with reporting, the company believes, is a lack of education on the part of shippers/carriers/LSPs in terms of the importance of filing accurately with HMIRS, how best to accomplish this task, and pitfalls to avoid. To that end, PHMSA could provide better training to these stakeholders. Although perhaps a bit removed from the task at hand, the shipper's vision for HMIRS is that motivation for reporting should be based on industry desire to put improvements in place to mitigate future risk rather than feeling obligated to report in order to achieve regulatory com- pliance. To that end, the company would recommend that the federal government produce data that not only accentuates failures, but successes as well. 3.4 Interviews with Database Managers The research team also conducted interviews with selected agencies that are responsible for managing key databases. The agencies include PHMSA, FMCSA, and FRA. The complete inter- views are found in Appendix B (available on the TRB website at www.TRB.org by searching for HMCRP Report 1). The discussion below presents a summary of findings deemed most significant. 3.4.1 Interviews with Agencies Maintaining Databases (PHMSA) The PHMSA officials indicated that reports go right into the database, which includes high- level quality control processing. They employ character-to-character checks to ensure that their process translated the paper form properly. During this process, they examine the form for personally identifiable information (PII), busi- ness rule inconsistencies, invalid dates, and invalid commodities (by cross-checking with the commodities in the database). To determine if they were caused by the hazardous materials, fatalities and injuries are validated by PHMSA using their own subprocess. Additional checks include cases such as when the report shows that 5.5 gallons were spilled from a 5-gallon con- tainer. PHMSA will go back and ask the filer whether there were multiple packages that failed and request that they file a supplemental report or they will sometimes use an e-mail reply as confirmation to correct the data themselves. They look for city/county inconsistencies. If a ship- per is an individual, they will not put that name in the database. The PHMSA official believes there would be a benefit from more verification, not just form- based validation. Sometimes important information such as costs, injuries, or other important information is left off. Sometimes this is because many big companies hire spill centers to com- plete the forms for them. Rather than checking all submittals, the officials believe that checking the significant or serious incidents would provide the most benefit. With respect to underreporting, PHMSA staff use a Web crawler and look for incidents, which they put in the HMIRS. In addition, they match things up with the telephonics [National Response Center (NRC) record]; if there is no match, it is flagged. They wait 60 days and then marry up the unreported incidents (URIs) to telephonics.