Model Impaired Driving Records Information Systems Tying Together Data Systems to Manage Impaired Drivers

Greer, Pamela · 2011 · ROSA P / United States. Department of Transportation. National Highway Traffic Safety Administration

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Summary

This report documents the Model Impaired Driving Records Information System (MIDRIS) demonstration project, sponsored by the National Highway Traffic Safety Administration (NHTSA) to address the fragmentation of impaired driving data. The primary motivation was the inability of most states to link critical data elements from the three key stakeholders in the impaired driving process: law enforcement, state driver licensing agencies, and the courts. Without integrated systems, offenders were often not charged or sentenced appropriately due to a lack of access to driving and criminal histories, undermining the integrity of the criminal justice system and the deterrent effect of sanctions. The project aimed to demonstrate how states could improve and expand existing systems to create a comprehensive tracking model that manages impaired drivers from arrest through sanction completion. The methodology involved a demonstration project conducted between 2002 and 2004, selecting Alabama, Iowa, Nebraska, and Wisconsin as pilot states. NHTSA provided funding, ongoing support, and implementation guidelines to help these states enhance their existing infrastructure rather than building new systems from scratch. The report details the specific goals, accomplishments, and lessons learned for each state. Alabama developed the Model Impaired Driving Access System (MIDAS) to integrate court referral officer data with criminal and driver histories. Iowa focused on filling gaps in its existing Traffic and Criminal Software (TraCS) system, integrating roadside data and breath testing results. Nebraska prioritized linking disparate systems to provide real-time access to warrant and criminal history data. Wisconsin improved system functionality by standardizing data definitions and creating interfaces with local government record management systems. The findings highlight significant improvements in data integration and operational efficiency across all four states. Alabama achieved real-time electronic tracking of offenders from arrest to disposition, automating court referral processes and saving approximately $100,000 annually in assessment fees. Iowa successfully integrated driver and vehicle data into its law enforcement software, enabling seamless data transfer from evidentiary breath testing devices and online reporting of substance abuse evaluations. Nebraska enhanced search methods to quickly identify offenders, provided real-time access to warrant data, and automated notifications for probation officers when offenders committed additional offenses. Wisconsin implemented a search function allowing officers to verify state statutes at the time of arrest, improving accuracy, and established real-time data transmission between courts and the Department of Motor Vehicles. The significance of this report lies in its provision of a validated framework for managing impaired driving records. It demonstrates that comprehensive data integration is achievable by leveraging existing systems and adhering to national standards, such as the ANSI and NIEM. The report concludes that MIDRIS components—such as statewide coverage, real-time access, electronic citations, and information linkage—enable states to charge and sentence offenders appropriately, gauge the effectiveness of countermeasures, and reduce administrative burdens. By connecting the dots between law enforcement, courts, and licensing agencies, states can better identify trends, ensure equitable imposition of penalties, and ultimately improve public safety by keeping dangerous drivers off the road.

Key finding

The demonstration states successfully integrated law enforcement, court, and licensing data systems to enable real-time tracking of impaired driving offenders from arrest through sanction completion.

Methodology

field_study

Sample size: 4

Provenance

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