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The Crash Outcome Data Evaluation System (CODES)

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English


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    The CODES Technical Report presents state-specific results from the Crash Outcome Data Evaluation System project. These results confirm previous NHTSA studies and show that safety belts and motorcycle helmets are effective in reducing fatalities and injuries. The Report also shows that safety belt and motorcycle use in the seven CODES states (Hawaii, Maine, Missouri, New York, Pennsylvania, Utah, and Wisconsin) could save millions of dollars in direct medical costs. The CODES project represents the first time that occupant-specific medical outcome and cost data for all occupants involved in motor vehicle crashes were available for highway safety evaluation. The technical report provides detailed descriptions of the crash, EMS, emergency department, hospital discharge and other state data files used to generate the population-based information for the Report to Congress. It describes the background of the CODES project, the selection of the seven states, the formation of the CODES advisory committees within each state (crucial to a project which depended on the cooperation of various data owners and data users) and the concepts of probabilistic linkage. Variations and similarities among the states are discussed regarding the availability of state data, file preparation, linkage variables, the linkage process and resulting linkage rates, and validation of the linkage results. It elaborates on the uniform research model used and discusses the outcome variables, additional risk factors used as covariates, models used in the logistic regressions, and methods of computing weighted averages of odds ratios and effectiveness. It compares odds ratios to risk ratios and 'effectiveness' and presents state-specific results for the safety-belt analyses of injury and cost of injury. Finally, the document gives digests of other state-specific analyses, covering topics such as: data quality, additional linkages to improve the results, data outliers (extreme values, as in inpatient charges), alcohol and drug use, age factors, types of safety belts, and geographic patterns in crash characteristics.
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    urn:sha-512:b8ee3a256170aad94a643c6aae03e4c6e8293ab741f9bf32ac082aa4a40f16f59144f5712c897b5aed05996e5c3f303721ee1d45e753882e212ba01394bb0590
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English
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