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Support for Research on Forensic Toxicological Laboratory Testing and Reporting Practices

项目名称：	Support for Research on Forensic Toxicological Laboratory Testing and Reporting Practices
摘要：	Comprehensive and consistent toxicological data is needed to better inform our understanding of the potential of drug-impaired driving as a public health problem. It is also essential to increasing the effectiveness of law enforcement and adjudication efforts in drug-impaired driving cases to make America’s roads safer for the public. Until recently, there has been no systematic implementation of guidelines for testing and reporting that public and private forensic laboratories should adopt. To help address this gap, an expert panel of toxicologists published "Recommendations for Toxicological Investigation of Drug-Impaired Driving and Motor Vehicle Fatalities" in the March 2018 issue of the Journal of Analytical Toxicology. These voluntary guidelines provide standardized lists of drugs, matrices (blood, oral fluid, urine, etc.), and cutoff levels for testing. The National Institute of Justice (NIJ) Office of Investigative and Forensic Sciences is the Federal government’s lead agency for forensic science research and development, as well as for the administration of programs that facilitate training, improve laboratory efficiency, and reduce backlogs. The purpose of this inter-agency agreement (IAA) is for the National Highway Traffic Safety Administration to provide support for NIJ's efforts to evaluate the potential of forensic toxicology laboratories to implement the guidelines for drug-impaired driving cases. The objectives of this IAA are to (1) determine the appropriateness of the Guidelines (2) evaluate whether sufficient information is obtained and whether valuable information is lost; and (3) examine the reasonableness of “stop testing” policies.
状态：	Active
资金：	400000
资助组织：	National Highway Traffic Safety Administration
执行机构：	National Institute of Justice
开始时间：	20200727
预计完成日期：	20250726
主题领域：	Highways；Safety and Human Factors