Some research shows that an estimated 65% percent of the United States prison population has an active substance use disorder (SUD). Another 20% percent did not meet the official criteria for an SUD but were under the influence of drugs or alcohol at the time of their crime.
Unfortunately, far too many individuals return to drug use and crime upon reentry into society.
Because of the revolving cycle of incarceration for many justice-involved individuals, supervised population organizations (prisons, probation, jails and detention centers) play a critical role in developing and implementing effective SUD strategies that can significantly impact and disrupt this disturbing cycle.
Using data, organizations responsible for supervised populations must be able to answer the following critical SUD questions:
- Who needs to receive SUD services, when and in what capacity?
- Which services are most effective in improving outcomes? Where are the gaps?
- What are the relative returns (cost/benefits) to current SUD practices and policies?
- What effect are strategies having on long-term recovery and reduced recidivism?
Assessing risks and needs
Supervised population organizations rely on risk assessment tools to measure the likelihood of future risk and recidivism. It is critical to screen and assess all individuals at intake and other key points during their incarceration for risk, particularly those with SUD.
Applying analytical modeling, risk assessment tools can individualize risk profiles, linking real-time data across all information systems. A comprehensive view based on all available data and analysis helps in effective case management planning, including targeted SUD treatment interventions.
The importance of data collection and integration
Data analysis is critical when evaluating SUD treatment interventions and policies to identify gaps, effectiveness, and availability of evidence-based strategies. Using analytics is also critical when connecting individuals with the appropriate SUD strategies. To drive effective change, we can:
- Gather data from various sources, including law enforcement, criminal justice, healthcare systems and social services.
- Integrate these data sets to create a comprehensive profile of justice-involved individuals, including criminal history, substance use, mental health history, demographics and prior treatment experiences.
Data can also be used to understand how Medicated Assisted Treatment (MAT) programs improve outcomes and break the cycle of harm. Continuous data analysis means establishing, adjusting and maintaining a longitudinal treatment plan that drives successful results.
Re-entry and recidivism reduction
Each year, thousands of justice-involved individuals are released into the community. Those with a history of SUD are at higher risk for continued substance use, overdose, suicide and increased recidivism. More data and analysis are needed by agencies to inform the decision making necessary to drive effective treatment and prevention approaches. Analytics play a critical role in predicting risk and validating plans and policies that provide long-term recidivism and recovery strategies for justice-involved individuals.
Creating a better future for justice-involved individuals
In this journey, analytics is a critical tool for predicting risk, validating plans and charting a course toward long-term recovery and reduced recidivism for justice-involved individuals. Ultimately, by embracing data-driven strategies and reinforcing our commitment to addressing SUD, we can make meaningful strides in breaking the cycle and creating a better future.
Read more about how SAS can help agencies combat substance use disorder using data and analytics.
Mary Beth Carroll and Kevin Harrington contributed to this article