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Ability to monitor driving under the influence of marijuana among non-fatal motor-vehicle crashes: An evaluation of the Colorado electronic accident reporting system☆,☆☆,★

Filetype[PDF-499.96 KB]


  • English

  • Details:

    • Alternative Title:
      J Safety Res
    • Description:
      Introduction

      As more states legalize medical/recreational marijuana use, it is important to determine if state motor-vehicle surveillance systems can effectively monitor and track driving under the influence (DUI) of marijuana. This study assessed Colorado’s Department of Revenue motor-vehicle crash data system, Electronic Accident Reporting System (EARS), to monitor non-fatal crashes involving driving under the influence (DUI) of marijuana.

      Methods

      Centers for Disease Control and Prevention guidelines on surveillance system evaluation were used to assess EARS’ usefulness, flexibility, timeliness, simplicity, acceptability, and data quality. We assessed system components, interviewed key stakeholders, and analyzed completeness of Colorado statewide 2014 motor-vehicle crash records.

      Results

      EARS contains timely and complete data, but does not effectively monitor non-fatal motor-vehicle crashes related to DUI of marijuana. Information on biological sample type collected from drivers and toxicology results were not recorded into EARS; however, EARS is a flexible system that can incorporate new data without increasing surveillance system burden.

      Conclusions

      States, including Colorado, could consider standardization of drug testing and mandatory reporting policies for drivers involved in motor-vehicle crashes and proactively address the narrow window of time for sample collection to improve DUI of marijuana surveillance.

      Practical applications

      The evaluation of state motor-vehicle crash systems’ ability to capture crashes involving drug impaired driving (DUID) is a critical first step for identifying frequency and risk factors for crashes related to DUID.

    • Pubmed ID:
      29776525
    • Pubmed Central ID:
      PMC5992600
    • Document Type:
    • Collection(s):
    • Main Document Checksum:
    • File Type:

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