In the United States, adults with serious mental illness are overrepresented in the criminal justice system. The sequential intercept model is a novel framework that identifies three major stages where interventions for this population can best be utilized: pretrial diversion, post-plea alternative to incarceration (ATI), and community reentry from jail and prison. This paper begins with a review of the literature that supports the application of Forensic Assertive Community Treatment (FACT) across these three stages. This paper will also draw on the influences of therapeutic jurisprudence, which holds that the courts can be used to both advance public safety and enhance access to mental health services for justice involved people with serious mental illness.
The literature has suggested that patients receiving FACT services have been found to have lower rates of psychiatric hospitalization and criminal justice recidivism in comparison to those who received traditional mental health services. This paper will touch on cutting edge practices to reduce psychiatric hospitalization and criminal justice recidivism rates among people with mental illness that are currently in use. In particular, programs involving law enforcement integration such as ACT-PI teams, co-response teams, and crisis intervention training will be explored. This paper will focus on applications and limitations of FACT across the various stages of the sequential intercept model, with a particular focus of using FACT as a way to reduce racial and gender disparities within the criminal justice system among people with serious mental illness. In light of the broad support the literature highlights for FACT when applied earlier within the criminal justice system, social work practice efforts should accordingly focus on expansion of early access to FACT services. In particular, criminal justice policy efforts should be expanded with respect to utilization of these services at the pretrial diversion and ATI stages, where they are historically underutilized.