County Associations and State Governments: Working Together Toward Smart Justice
By Michael Thompson
October 24, 2013
County Associations and State Governments: Working Together Toward - - PowerPoint PPT Presentation
County Associations and State Governments: Working Together Toward Smart Justice By Michael Thompson October 24, 2013 National non-profit, non-partisan membership association of state government officials Represents all three
By Michael Thompson
October 24, 2013
membership association of state government officials
advice informed by the best available evidence
Council of State Governments Justice Center | 2
Council of State Governments Justice Center | 3
Austin, TX New York, NY Seattle, WA Bethesda, MD
90 staff in 4 offices
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Criminal Justice / Mental Health Consensus Project School Discipline Consensus Project National Reentry Resource Center
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NV AZ TX WI IN VT RI CT HI OK KS NH WV PA ID MI NH NC OH
Council of State Governments
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Require the use of a pretrial risk screen within 3 days of booking to identify those with greatest risk of flight 42% of the regional jail population is pretrial 25% of prison admissions are misdemeanor
month average length
Misdemeanor offenders may be housed in a jail if:
Probation violators spend lengthy periods in jail awaiting hearings Create a 30-day cap in statute for probationers awaiting violation hearings
STATE FINDING POLICY
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“Just as helpful as pointing out commonly made mistakes are the cutting-edge practices identified in the report. … The report, in other words, should be required reading.”
Who? LOW 10% re-arrested MODERATE 35% re-arrested HIGH 70% re-arrested Risk of Re-offending Without Risk Assessment… With Risk Assessment…
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individuals most likely to reoffend
*Presentation by Latessa, “What Works and What Doesn’t in Reducing Recidivism: Applying the Principles of Effective Intervention to Offender Reentry”
Average Difference in Recidivism by Risk for Halfway House Offenders
Low Risk
+ 3 %
Moderate Risk
High Risk
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individuals most likely to reoffend
Criminal Behavior
Leisure Family Employment/ Education Substance Use
Thinking Peers Personality Past Criminality*
The Big Four
(impacting these are the major drivers to reducing criminal behavior)
Programs targeting these needs can significantly lower recidivism rates
* Past criminality cannot be changed.
Housing
What?
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individuals most likely to reoffend
Low Supervision/ Program Intensity Moderate Supervision/ Program Intensity High Supervision/ Program Intensity LOW 10% re-arrested MODERATE 35% re-arrested HIGH 70% re-arrested Risk of Re-offending
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ensure quality
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ensure quality
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(reduced recidivism)
Is the program based on principles demonstrated to be effective? Are program staff properly trained? Is program matched with appropriate client population? Is program implemented as designed? Is performance tracked and measured against expectations?
How Well?
ensure quality
Source: Lee, S., Aos, S., Drake, E., Pennucci, A., Miller, M., & Anderson, L. (2012). Return on investment: Evidence-based options to improve statewide outcomes, April 2012 (Document No. 12-04-1201). Olympia: Washington State Institute for Public Policy.
Impact of Treatment Intervention on Recidivism Rates
Supervision, with effective “RNR” principles, yields the biggest recidivism reduction
Source: Latessa, Lovins, and Smith, “ Follow-up Evaluation of Ohio’s Community Based Correctional Facilities, Outcome Study, February 2010
Supervision with Risk Need + Responsivity Drug Treatment in the Community Drug Treatment in Prison
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ensure quality
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Use a graduated range of sanctions and incentives to guide specific type of response to violations and compliance. Enable officers to respond meaningfully to violations without delay or time-consuming processes. Prioritize the most expensive, restrictive sanctions for offenders committing the most serious violations. Focus supervision officer time and program resources on the highest-risk offenders.
community supervision policies and practices
Arizona, 2004
60%
tate’s prison population comes from and returns to the Phoenix-Mesa metropolitan area.
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based strategies
Maricopa County, 2004
South Mountain Zip Code 85041 Prison Admissions = 31.8 per 1000 adults Jail Bookings = 96.5 per 1000 adults Probation = 25.1 per 1000 adults
A single neighborhood in Phoenix is home to 1% of the state’s total population but 6.5%
based strategies
Cent ral Cit y Est rella Laveen Encant o Alhambra Nort h Mount ain Camelback East
Within high expenditure neighborhoods there are numerous, smaller area, million dollar block groups
$1.8 Million $1.1 Million $1.6 Million
Glendale Maryvale S
Maricopa County, 2004
based strategies
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based strategies
Deliver programs the same way to every
Deliver programs based on
and/or circumstances
Supervise everyone the same way
Assess risk of recidivism and focus supervision on the highest-risk
Assign programs that feel or seem effective
Prioritize programs addressing the needs most associated with recidivism Evidence-Based Practices
Traditional Approach
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10 20 30 40 50 60 Household Jail State Prison
Alcohol use disorder (Includes alcohol abuse and dependence) Drug use disorder (Includes drug abuse and dependence)
2 % 47 % 54 % 44 % 53 %
Source: Abrams & Teplin (2010)
Percent of Population
8 %
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5% 95% 72% 83% 17% 28%
General Population Jail Population
Serious Mental Illness No Serious Mental Illness Serious Mental Illness No Serious Mental Illness Co-Occurring Substance Use Disorder No Co-Occurring Substance Use Disorder
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“New York City jails, like jails across the country, have disproportionately high numbers of inmates whose mental health needs present unique challenges.”
Human Services, New York, NY “Our jails are increasingly a place of last resort for offenders who are mentally ill. Even as the department’s total inmate population continues to fall, this group is unable to get out or stay out.”
Department of Corrections, New York, NY ”I would welcome the chance to take all of our mentally ill and medically challenged inmates…and put them somewhere they could get programming, but I haven’t heard anyone stepping up to do that.”
County, WI
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“In every city and state I have visited, the jails have become the de facto mental institutions…there are not enough resources out there to care for them [mentally ill].”
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Ocala Star-Banner, November 2007 Lakeland Ledger, February 2001
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http://static.nicic.gov/Library/022134.pdf
http://static.nicic.gov/Library/022134.pdf
53,091 7,260 Detainees who participated in the program were released from jail and put under the MHPTR program’s supervision. 36 percent of the 1,101 detainees referred to the program did not participate because they had already been released from jail. Others did not participate because they did not meet the clinical criteria, declined to participate, had a history of violence, were not an Orange County resident, or had been referred to another program.
http://static.nicic.gov/Library/022134.pdf
53,091 7,260 Offenders have satisfied their charges with the court system without further
program for successful participants varies depending on when participants satisfy their charges without further arrests Offenders are returned to jail on an outstanding warrant, another arrest/charge, or a revocation due to noncompliance with the conditions of the MHPTR program prior to the disposition of current charges
http://static.nicic.gov/Library/022134.pdf
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Diagnosable mental disorders 16% Serious mental disorders 5% Severe mental disorders 2.5%
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Risk/Needs Assessment 101: Science Reveals New Tools to Manage Offenders, http://www.pewstates.org/uploadedFiles/PCS_Assets/2011/Pew_Risk_Assessment_brief.pdf
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Low Criminogenic Risk (low) Medium to High Criminogenic Risk (med/high) Low Severity of Substance Abuse (low) Substance Dependence (med/high) Low Severity of Substance Abuse (low) Substance Dependence (med/high) Low Severity
Mental Illness (low) Serious Mental Illness (med/high) Low Severity
Mental Illness (low) Serious Mental Illness (med/high) Low Severity
Mental Illness (low) Serious Mental Illness (med/high) Low Severity
Mental Illness (low) Serious Mental Illness (med/high) Group 1 I – L CR: low SA: low MI: low Group 2 II – L CR: low SA: low MI: med/high Group 3 III – L CR: low SA: med/high MI: low Group 4 IV – L CR: low SA: med/high MI: med/high Group 5 I – H CR: med/high SA: low MI: low Group 6 II – H CR: med/high SA: low MI: med/high Group 7 III – H CR: med/high SA: med/high MI: low Group 8 IV – H CR: med/high SA: med/high MI: med/high
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3,319 4,391 10,257 7,557
2005 2012 M Gr
Non- M Gr
76% 63% 37% 24%
13,576 T
11,948 T
NYC Jail Population (2005-2012) Average Daily Jail Population (ADP) and ADP with Mental Health Diagnosis Analyses Revealed Greatest Potential Impact by Addressing Pretrial Detainee Population
Pr e tr ial 62%
Se nte nc e d 24% Sta te Pr ison Se nte nc e 15% AL OS for Pr e tr ia l Admissions (Da ys) 79 40 81 60 AL OS for Se nte nc e d Admissions (Da ys)
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20.8% 11.8%
0.0% 5.0% 10.0% 15.0% 20.0% 25.0%
Similar minimum bail amounts set but M group much less likely to make bail
% Making Bail Post-Arraignment Lowest amount needed for release (grouped median)
Felony Misd.
$4,784 $4,769 $1,055 $1,001
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information
December Spring
Fall
2012 2013
Spring 2011
2013 Summer 2013
Mayor announces the allocation
“Court-based Intervention and Resource Teams” (CIRTs) to serve over 3,000 clients with mental health needs annually Justice Center Final Report
borough and negotiates performance based contracts
planning begins with goal of serving first clients by December 2013
Johnson County, KS Hillsborough, NH New York City, NY Bexar County, TX Mental Health Assessment ✔ ✔ ✔− Substance Abuse Assessment ✔− Risk Assessment ✔−
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Reluctance to focus on higher risk individuals Insufficient skillsets involving cognitive behavioral interventions targeting needs Serious shortages in treatment capacity Judges are skeptical (NY training example) Community corrections, jail, and prison staff need improved understanding of mental health issues and how to serve this population effectively
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County Recidivism Rate Harris 40% Dallas 30% Bexar 28% Tarrant 30% Travis 37% Average 33% Comparable Recidivism Measure
Step 1: Set baseline for counties to get comparable recidivism measure Measure recidivism of jail releases, probationers and parolees to the county Later steps: Track changes in recidivism over time Review why recidivism rates may vary by county Review relation of recidivism rates to county practices and programs
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Fabelo, Tony and Nancy Arrigona. March 1991. Recommended Methodologies for State Criminal Justice Agencies. State of Texas. Accessed March 4, 2013 http://www.lbb.state.tx.us/Public_Safety_Criminal_Justice/Reports/UniRecid.pdf
Y. Outcome tracked Rearrest Conviction Return to Incarceration Z. Uniform follow up period Follow up matters – a one year rate will track offenders for 12 months X. Released during time period Fiscal year Calendar year Recidivism Rate
The number of offenders in a county under community supervision (probation or parole) or released from custody during time period (X) with
months Number of offenders under community supervision or released from custody during time period (X)
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Definition Re-arrest
Percent Re-arrested
One Year Uniform Tracking Period
Uniform one, two and three year follow-up Follow-up
Council of State Governments Justice Center | 50 Harris Probation “Learning Site” Report to Judicial Officials, April 18, 2012
Felons Percent Re- arrested after Three Years 1 year 2 year 3 year 36% Misdemeanors Percent Re- arrested after Three Years 1 year 2 year 3 year 27% Overall Recidivism Rate 30% 18% 27% 13% 21%
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Case Data to Be Requested – Calendar Year 2011 County Jail Releases CSTS Probation Admissions TDCJ Releases to Parole Data – CY 2011-12 DPS Criminal History SID Admission Date Release Date Release Type Offense Type Offense Level SID Admission Date Completion Date County Offense Type Offense Level Risk Score Risk Cutoff SID Parole Start Date Parole End Date County of Release Offense Type Offense Level Risk Score Risk Cutoff Arrests for each SID Date of Arrest Date of Birth Gender Race/Ethnicity
Recidivism Data Collection Elements
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Use risk assessment from county jail data for offenders
Ideal Measure
Build a proxy risk score using static factors (age, gender, criminal history) from the county jail and criminal history file
Working Measure If unavailable
Risk assessment in criminal justice is a systematic methodology to determine the risk of recidivism of an offender for a variety of purposes using:
Static Factors
(cannot change)
Dynamic Factors
(can change)
Prior conviction history Age at first conviction Employment status Treatment completion
Council of State Governments Justice Center | 53 Harris Probation “Learning Site” Report to Judicial Officials, April 18, 2012
Minimum Three Year Recidivism Rate for Felons by Wisconsin and Combined LSI-R Risk Categories Wisconsin LSI-R 23.6% 25.2% Medium Wisconsin LSI-R 36.8% 34.1% Maximum Wisconsin LSI-R 47.9% 41.3% Wisconsin = 11 Risk Factors LSI-R = 44 Risk Factors
Outcome Measurement
Risk Offense level Demographics
Key Elements Uniform Follow-Up Period Control for Risk
365 days from release for each
County Jail Release: Rearrest Probation and Parole: Rearrest
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extraction?
extract?
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mthompson@csg.org
The presentation was developed by members of the Council of State Governments Justice Center staff. The statements made reflect the views of the authors, and should not be considered the official position of the Justice Center, the members of the Council of State Governments, or the funding agency supporting the work. Citations available for statistics presented in preceding slides available on CSG Justice Center web site.