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Using Data to Design Reentry & Reinvestment Initiatives

Using Data to Design Reentry & Reinvestment Initiatives. Marshall Clement Project Director, Justice Reinvestment. Why Use Data? Lessons for Designing Initiatives Justice Reinvestment & NH Case Study. The case for recidivism reduction strategies couldn’t be stronger….

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Using Data to Design Reentry & Reinvestment Initiatives

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  1. Using Data to Design Reentry & Reinvestment Initiatives Marshall Clement Project Director, Justice Reinvestment

  2. Why Use Data? Lessons for Designing Initiatives Justice Reinvestment & NH Case Study

  3. The case for recidivism reduction strategies couldn’t be stronger…

  4. Spending on corrections is up One out of every three state workers is employed by the Michigan DOC As a share of general fund expenditures, corrections grew from 16 to 23 percent Spending on corrections increased 57 percent over the past 10 years

  5. Recidivism rates climb, driving prison population growth Recidivism Rates Have Increased New Hampshire Recidivism Rate Percent Returning to Prison Within Three Years of Release

  6. Current levels of state spending are unsustainable

  7. Yet, spending on correctional programs is being reduced in many states… For state prisons, cuts present new problems By John Gramlich, Stateline Staff Writer “We have no drug treatment programs at medium security or above (facilities),” says Justin Jones, director of the Oklahoma Department of Corrections. “We eliminated all sex offender treatment, even though it was mandated by statute.”

  8. To survive, initiatives must be data-driven to ensure their impact on prison/jail populations.

  9. Impact of Ohio Residential Correctional Programs on Recidivism (Annual State Funding: $104m) * Results for all participants

  10. Why Use Data? Lessons for Designing Initiatives Justice Reinvestment & NH Case Study

  11. Lessons for Designing Initiatives • Start by analyzing who goes to prison, not who comes out • Use risk assessment to narrow target population • Ensure that your approach has a solid research base and is of high quality • Establish a regular tracking system

  12. 1. Start by analyzing who goes to prison Fully Loaded Cost (@$30K) Estimated Bed Impact Number in 2009 Average LOS Admission Type 2,000 3,000 beds Parole/Post-Release Revocations 18 months $90m = X 1,500 4,500 beds Probation Revocations 36 months $135m = X 3,000 10,000 beds New Sentences 40 months $300m = X

  13. Narrow the population by geography Admission Type Parole/Post-Release Revocations Probation Revocations New Sentences

  14. Explore reasons for reincarceration Admission Type Revocation Reason Violation Reasons Parole/Post-Release Revocations Allegations or arrests for new criminal conduct: 41 percent Drug use: 75 percent Probation Revocations Failure to participate/complete program: 41 percent Violating the Conditions of Supervision: 59 percent Absconded: 25 percent New Sentences

  15. 2. Use risk assessment to narrow target pop. 100 people released from prison 60 “successful” (i.e. not reincarcerated) 40 reincarcerated ?

  16. Focus on high risk offenders Average Difference in Recidivism by Risk for Halfway House Offenders Low Risk + 3 % High Risk - 14 % Moderate Risk - 6 % *Presentation by Latessa, “What Works and What Doesn’t in Reducing Recidivism: Applying the Principles of Effective Intervention to Offender Reentry”

  17. Simulation of how risk affects program impact 100 people released from prison 30 Low Risk 40 Medium Risk 30 High Risk Recidivism rate without intervention 20 percent 6 people 40 percent 16 people 60 percent 18 people Recidivism rate with intervention 21 percent 6-7 people 38 percent 15 people 51 percent 15 people For every 100 all risk levels served, 3-4 fewer people will be reincarcerated. 3x bigger impact For every 100 high risk served, 9 fewer people will be reincarcerated.

  18. Ensure the risk assessment has been validated Distribution by Risk Level Re-Offense Rates by Risk Level Re-offense refers to a new offense within 3 years

  19. 3. Ensure that your approach has a solid research base and is of high quality Steve Aos, Marna Miller, and Elizabeth Drake. (2006). Evidence-Based Adult Corrections Programs: What Works and What Does Not. Olympia: Washington State Institute for Public Policy.

  20. 2005 Study of Ohio Prison Diversion Programs Related Program Quality to Impact on Recidivism • The Correctional Program Assessment Inventory (CPAI) scores programs based on use of practices known to be associated with reducing recidivism. • 31% of the programs have reduced recidivism by more than 10% • The programs that impacted the most recidivism were following most elements of Evidence-based Practices. • These programs score highly on the Correctional Program Assessment Inventory indicating the quality of the program and adherence to principles of effective interventions (Evidence-based Practices) that can lead to decreases in recidivism including placing offenders into appropriate interventions associated with assessed risk.

  21. 4. Establish a regular tracking system Admission Type July 2010 Admissions Parole/Post-Release Revocations Statewide August: 90 FY10 Monthly Avg: 85 From Program Y • August: 10 • FY10 Monthly Avg: 12 From County X • August: 20 • FY10 Monthly Avg: 25 From Caseload Z • August: 10 • FY10 Monthly Avg: 12 If populations are changing or program is just getting started, present numbers also as a percentage currently being supervised or participating in program.

  22. Kansas Example Revocations from Post-Release Supervision Technical Violations 46% New Offenses 40%

  23. Arizona Example Change in Felony Probation OutcomesFY08 to FY09 following passage of SB1476 -13% Probation Revocations to Prison Probation Revocations to Jail -14% -2% Probationers w/ New Felony Convictions $17.8m Estimated Averted State Prison Costs

  24. Why Use Data? Lessons for Designing Initiatives Justice Reinvestment & NH Case Study

  25. Justice Reinvestment Approach Bipartisan, inter-branch, bicameral structure 1 Analyze data & develop policy options 2 Adopt new policies 3 Measure performance • Crime, arrest, conviction, jail, prison, and probation and parole supervision data • Engage & solicit input from stakeholders • Map prison admissions and social services • Develop policy options & estimate cost savings

  26. 1 Analyze data & develop policy options 2 Adopt new policies 3 Measure performance • Identify assistance needed to translate policies into practice • Develop a coordinated implementation plan with state and local officials • Deploy targeted reinvestment strategies to increase public safety

  27. 1 Analyze data & develop policy options 2 Adopt new policies 3 Measure performance • Track the impact of enacted policies/programs • Monitor recidivism rates & other key measures • Update prison population projections

  28. New Hampshire’s Criminal Justice System FY 2000-2008 Reported Crime Low & Stable Arrests 2005-2008 +4% Superior Court Filings +40% Jail /HOCPopulation +21% Probation Placements FY2000-2009 ? Admissions to Prison for New Offenses FY2000-2009 +3% Probation Population FY2000-2009 +26% Prison Population FY1999-2009 +31% Parole Revocations FY2000-2009 +50% Probation Revocations Stable Parole Population FY2000-2009 +93% Releases to Parole FY2000-2009 +33%

  29. Prison Population & Costs Have Increased State Spending on Corrections + 100 percent $52m$104m FY1999-2009 Prison Population+ 31 percent FY1999-2009

  30. Revocations Driving NH Prison Admissions Parole revocationsincreased from 35% to 43% of all prison admissions In 2009, probation and parole revocations account for 57% of all admissions to prison Parole revocations in FY 2009 will cost approximately $13.3 million based on a $90 per day cost of incarceration.

  31. Prison Population Past Minimum Parole Eligibility Prison Population November 20, 2009 2,915 65%Still Serving Minimum Sentence 1,907 35%Past 100% of Minimum Sentence 1,008 36%Admitted for Parole Revocation 359 64%Admitted for New Offense or Probation Revocation 649 Median # of Days Beyond Minimum: 500

  32. People Released From Prison Without Supervision Prison Releases FY 2009 1,394 5%Other 79%Paroled/Released to Supervision 1,100 16%Discharged (“Maxed Out”) & Released without supervision 224

  33. Policy Framework Goal 1: Reduce spending on corrections. Goal 2: Reinvest in treatment and sanction programs. Goal 3: Increase public safety by reducing recidivism. A. Focus supervision on high risk offenders. D. Reinvest in treatment for high-risk, high-need probationers and parolees. B. Use short, swift and certain jail sanctions. E. Ensure everyone leaving prison receives at least nine months of supervision. C. Establish intermediate sanction program & designated parole revocation facility. F. Require nonviolent offenders to serve 100-120% of their minimum sentence.

  34. Impact of Policy Framework

  35. Thank You Marshall Clement Project Director, Justice Reinvestment mclement@csg.org

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