Assessing the Feasibility of Evaluating the Legal Implications of Marijuana Per Se Statutes in the Criminal Justice System

Introduction

The legalization and decriminalization of cannabis is occurring at a rapid pace for both medical and recreational use. In total, 31 states have legalized medical cannabis, along with Washington, D.C.; Guam, and Puerto Rico (NCSL, 2018). This legalization trend creates numerous potential public health challenges, but traffic safety may be particularly impacted. One critical concern is developing effective policy related to driving under the influence of cannabis (DUIC). Yet, only limited research exists on the effects of many impaired-driving policies as they specifically relate to cannabis, including the establishment of an illegal per se concentration of cannabis, above which a driver is considered to be impaired.

Currently, six states have per se laws with non-zero tolerance limits for cannabis (Illinois, Montana, Nevada, Ohio, Pennsylvania, and Washington). While intended as an effective legal countermeasure to cannabis-impaired driving, it is unclear how the establishment of non-zero tolerance per se limits affects the criminal justice system. This is largely due to the limitations of commonly used drugged-driving data sources, as well as the necessary linkage of these data to judicial outcomes, to appropriately assess these effects. Thus, the objective of this research is to assess the feasibility of studying the effect of non-zero-tolerance per se limits for cannabis on the legal system. The effects of these laws on judicial outcomes (e.g., convictions) are of particular interest.

Methodology

The research herein was conducted using a literature review, as well as guided discussions with key state-level officials. The literature review focused on available data sources, data dictionaries, state legislation, and research on per se concentrations for cannabis and driving. Structured interviews were then conducted with representatives and stakeholders in each of the six states with non-zero tolerance per se limits for cannabis presence in drivers. The project sought to understand, for each state, what data is currently linked or would need to be linked in order to track outcomes of cases from the arrest through the disposition of the case, and what data processes would need to be enacted to link these data (i.e., whether records would need to be manually linked using case identifiers).

Results

The literature review focused on available data sources, data dictionaries, state legislation, and research on per se concentrations for cannabis and driving. Literature on the effects of non-zero tolerance per se concentrations for cannabis on the legal system is limited in breadth, and very few studies have attempted to quantify the impact of per se laws on traffic safety outcomes. The literature review was not designed to evaluate the body of literature on per se limits, but rather to gain information on state data systems, data quality, data linkage, and the feasibility of conducting later analyses on the effects of these policies using available state data. The results are presented in sections detailing (1) empirical research on the effects of per se laws and (2) data management and integration.

Each state examined in this study has its own unique policy, data systems, and potential for integration. Thus, separate feasibility assessments are provided for each, in addition to a description of the state’s statute, law enforcement testing and citation data, toxicology testing and procedures, and judicial processing and court data. A process flow chart has also been developed for each study state. In general, the ideal analytic approach requires data that specifically tracks all individuals arrested for per se violations throughout the entire legal process (including dropped or reduced charges and across all dispositions) from the time of arrest through the final disposition of the case. Furthermore, these data should differentiate cannabis-related offenses (specifically per se violations due to THC) from other types of impaired driving. This requires high-quality data across three general domains: law enforcement (e.g., when drug testing may be conducted, where the data are maintained), toxicology (e.g., laboratory capabilities and limitations, reporting of results), and judicial outcomes (e.g., how and where records are stored and maintained). The report discusses each in turn.