Impaired Driving Tracking System
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Summary
This report, commissioned by the National Highway Traffic Safety Administration (NHTSA) and conducted by 2M Research, addresses the critical need for effective Impaired Driving Tracking Systems (IDTS) to combat rising alcohol-impaired traffic fatalities and recidivism. Despite a 15 percent increase in impaired driving deaths between 2019 and 2022, many states struggle with fragmented data sharing among law enforcement, courts, and licensing agencies. The study aims to evaluate current state implementations, identify barriers to sustainability, and compile best practices to help jurisdictions establish or improve systems that track offenders from arrest through adjudication. The researchers employed a mixed-methods approach involving a comprehensive literature review, stakeholder discussions, and data synthesis. They initially identified 22 jurisdictions with potential tracking capabilities through a web scan of state transportation documents and federal reports. From this pool, eight states were selected for in-depth analysis based on specific inclusion criteria: California, Missouri, Nebraska, Iowa, Tennessee, the District of Columbia, Wisconsin, and Utah. Researchers conducted qualitative discussions with stakeholders in these states to assess system architecture, resource allocation, maintenance strategies, and data utilization. The findings categorized the eight states into three distinct system types. California and Missouri utilize unified, standalone systems dedicated solely to impaired driving, offering seamless tracking but facing challenges in securing broad agency buy-in. Nebraska, Iowa, Tennessee, and the District of Columbia integrate impaired driving tracking into larger criminal justice or traffic safety systems, which reduces redundancy but can lead to data entry inconsistencies and reporting backlogs. Wisconsin and Utah operate decentralized systems with fragmented data management, resulting in delayed information sharing and limited real-time access for stakeholders. Across all types, common challenges included insufficient funding, staff turnover, lack of legislative backing, and difficulties in integrating data from disparate agencies. The report concludes by outlining essential best practices for establishing sustainable IDTS. Key recommendations include securing long-term dedicated funding, obtaining legislative mandates to ensure data privacy and court admissibility, and establishing central coordination with formalized interagency collaborations. The authors emphasize the importance of auto-integrated data with uniform fields, ongoing staff training, and the inclusion of pre-trial diversion data to evaluate program effectiveness. By implementing these strategies, states can enhance their ability to identify repeat offenders, allocate resources efficiently, and ultimately reduce alcohol-impaired driving fatalities. The findings serve as a roadmap for policymakers seeking to strengthen data-driven countermeasures against impaired driving.
Key finding
States employ three distinct approaches to impaired driving tracking—unified standalone, integrated, and decentralized systems—each facing specific challenges related to funding, data integration, and interagency collaboration that can be mitigated through central coordination and sustained legislative support.
Methodology
mixed_methods
Sample size: 8
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (5 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 18 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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Information type
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- Applied Guidance: countermeasure evaluation
- Methodological Resource: dataset resource