The costs of crime during and after publicly funded treatment for opioid use disorders: a population‐level study for the state of California

Abstract

Background and aims Treatment for opioid use disorders (OUD) reduces the risk of mortality and infectious disease transmission; however, opportunities to quantify the potential economic benefits of associated decreases in drug-related crime are scarce. This paper aimed to estimate the costs of crime during and after periods of engagement in publicly-funded treatment for OUD to compare total costs of crime over a hypothetical 6-month period following initiation of opioid agonist treatment (OAT) versus detoxification. Design Retrospective, administrative data-based cohort study with comprehensive information on drug treatment and criminal justice systems interactions. Setting Publicly-funded drug treatment facilities in California, USA (2006–2010). Participants 31,659 individuals admitted for the first time to treatment for OUD, and who were linked with criminal justice and mortality data, were followed during a median 2.3 years. Median age at first treatment admission was 32, 35.8% were women, and 37.1% primarily used prescription opioids. Measurements Daily costs of crime (2014$US) were calculated from a societal perspective and were composed of the costs of policing, court, corrections, and criminal victimization. We estimated the average marginal effect of treatment engagement in OAT or detoxification adjusting for potential fixed and time-varying confounders, including drug use and criminal justice system involvement prior to treatment initiation. Findings Daily costs of crime during treatment compared with after treatment were $126 lower for OAT (95% CI: $116, $136) and $144 lower for detoxification ($135, $154). Summing the costs of crime during and after treatment over a hypothetical 6-month period using the observed median durations of OAT (161 days) and detoxification (19 days), we estimated that enrolling an individual in OAT as opposed to detoxification would save $17,550 ($16,840, $18,383). Conclusions In publicly-funded drug treatment facilities in California USA, engagement in treatment for opioid use disorders is associated with lower costs of crime in the six months following initiation of treatment, and the economic benefits were far greater for individuals receiving time-unlimited treatment.

The costs of crime associated with stimulant use in a Canadian setting

“…Our finding of positive and significant associations between monthly crime costs and drug use for the majority of stimulant use categories was consistent with other studies (Bennett et al, 2008; Oser et al, 2011), and similar in magnitude to crime cost estimates of drug users in-relapse or out-of-treatment, compared to in-treatment or abstinent (Flynn et al, 1999; Krebs et al, 2014; Krebs et al, 2016). Our finding that monthly crime costs associated with powdered cocaine use were not significantly different than crack cocaine was consistent with Vaughn et al (2010), who found no differences in violent behavior after controlling for contextual variables and co-morbid disorders.…”

“…The treatment variables included in our analysis represented an exploratory assessment of the potential for positive effects for stimulant users from non-stimulant-specific treatments, however, we would expect an effective, evidence-based treatment regimen for stimulant use disorders to have considerably larger effects. For example, if an effective treatment regimen was identified and capable of generating an 80% reduction in crime costs, similar to what has been recently estimated for OAT and opioid users (Krebs et al, 2014; Krebs et al, 2016), as well as individuals in long-term residential treatment for cocaine use disorders (Flynn et al, 1999), there are potential average monthly cost savings of $4691 per cocaine user, $4676 per daily MA user, and $7114 per daily polystimulant user treated. This is in addition to many other potential health benefits and cost savings, such as reduced health care costs, that could be generated by an effective treatment program (Baser et al, 2011; French and Martin, 1996).…”

“…Since neither treatment was specifically targeted toward stimulant use, we were not necessarily expecting to observe a significant association with lower crime costs among those in our analytic sample, however, we wanted to consider the potential for positive spillover effects and increased pro-social behaviour resulting from any type of addiction treatment. This was informed by results from Krebs et al (2014) and Krebs et al (2016), which found that OAT was more effective in reducing crime costs among opioid users who were co-using stimulants. Although estimates for OAT in our study were not independently associated with lower crime costs, opioid users comprised only a subset of our analytic sample, as the inclusion criteria was not related to opioid use or OAT history.…”

Economic impact of faith‐based residential addiction recovery for the homeless

“…The study demonstrated net savings from reduced health problems, illegal activity, and missed school days as a result of the criminal justice intervention. Krebs et al (2017) found significant cost reductions from implementing an opioid medication assisted therapy program in California. Researchers found that enrolling a client in the opioid assisted therapy program reduced the daily costs of crime during treatment compared with after treatment by $126 and that enrolling an individual in opioid assisted treatment (161 days) rather than traditional detoxification (19 days) reduced costs by $17,550.…”

Estimating State Transitions for Opioid Use Disorders

“…Vital statistics data was obtained from the NDI, maintained by the Centers for Disease Control and Prevention (CDC), which contains records of all deaths occurring nationwide and probabilistic data linkage was performed by CDC staff 44 Mortality outcomes, treatment utilization and outcomes as well as the costs of crime associated with treatment engagement within the specified cohort have been described elsewhere and include further data collection details. 5,20,45,46 …”