County Associations and State Governments: … Center...-- Sheriff Tom Dart, Cook County, IL Case Study: Florida Counties St. Petersburg Times, November 2007 Council of State Governments

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 branches of state government

• Provides practical, nonpartisan advice informed by the best available evidence

Council of State Governments Justice Center | 2


Austin, TX

New York, NY Seattle, WA

Bethesda, MD

90 staff in 4 offices


Criminal Justice / Mental Health Consensus Project

School Discipline Consensus Project

National Reentry Resource Center

Major Initiatives Underway Regarding Youth, Mental Health, and Reentry


Justice Reinvestment in 18 States

NV

AZ

TX

WI

IN

VT

RI CT

HI

OK

KS

NH

WV

PA

ID

MI

NH

NC

OH

County data and stakeholder input enriches analysis and justice reinvestment policies

Council of State Governments

6

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 offenders – with a 3-

month average length of stay

Misdemeanor offenders may be housed in a jail if:

The sheriff voluntarily accepts Bed space exists Reimbursed by new state funds

Probation violators spend lengthy periods

in jail awaiting hearings

Create a 30-day cap in statute for probationers awaiting violation

hearings

STATE FINDING POLICY


Overview

Understand the latest science and research

Improve outcomes for people with mental illnesses in contact with justice system

Reduce re-offense rates for people released from jail

Recidivism across the states


Knowledge on Improving Criminal Justice Outcomes Has Increased Dramatically Over the Last 20 Years

Academics and practitioners have contributed to this growing body of research


What are 3-4 things I need to know about what works to reduce recidivism?


“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.”

-The Washington Post, February 27, 2011

1. Focus on individuals most likely to reoffend

2. Base programs on science and ensure quality

3. Implement effective community supervision policies and practices

4. Apply place-based strategies

Identify and Focus on Higher-Risk Offenders

Who?

LOW 10%

re-arrested

MODERATE 35%

re-arrested

HIGH 70%

re-arrested

Risk of Re-offending

Without Risk Assessment… With Risk Assessment…



TITLE (Ohio)

• Adopted a common set of risk assessment instruments across the state’s criminal justice system.

• Ensured that program placement is driven by risk assessment score. *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

- 6 %

High Risk

- 14 %



Target the Factors that Evidence Shows Are Most Central to Criminal Behavior

Criminal Behavior

Leisure

Family

Employment/ Education

Substance Use

Thinking

Peers

Personality

Past Criminality*

Antisocial The Big Four

(impacting these are the major drivers to reducing

criminal behavior)

Higher-risk offenders are likely to have more of the

Big Four. Programs targeting these

needs can significantly lower recidivism rates

* Past criminality cannot be changed.

Housing

What?



After Who and What Are Answered, Supervision and Programming Should Be Well Targeted

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



Ensure Funded Programs Are Reducing Recidivism




Ensure Programs Are High Quality and Properly Implemented

Program Effectiveness (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?


Where and How Treatment Is Delivered Impacts the Degree of Recidivism Reduction

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

-24% -30%

-17%

Supervision with Risk Need + Responsivity

Drug Treatment in the

Community

Drug Treatment in Prison




Elements of Effective Supervision

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. Dosage/Intensity

Consistency

Swiftness

Cost-effectiveness

3. Implement effective community supervision policies and practices

Prison Admissions Hotspots Arizona, 2004

60% of the State’s prison population comes from and returns to the Phoenix-Mesa metropolitan area.



Prison Admissions Hotspots 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% of the state’s prison population


Central City Estrella

Laveen

Encanto

Alhambra

North Mountain

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

South Mountain

Prison Expenditures in Dollars Maricopa County, 2004


High Density of Probationers in South Phoenix



Reducing Criminal Behavior Requires Focusing on Risk, Need, and Responsivity

Responsivity

Risk

Need

Deliver programs the same way to every

offender

Deliver programs based on offender learning style, motivation,

and/or circumstances

Supervise everyone the same way

Assess risk of recidivism and focus supervision on the highest-risk

offenders

Assign programs that feel or seem effective

Prioritize programs addressing the needs most associated with

recidivism

Evidence-Based Practices Traditional Approach



Overview




Alcohol and Drug Use Disorders: Significant Factor in Jail and Prisons

0

10

20

30

40

50

60

Household Jail State Prison

Alcohol use disorder(Includes alcoholabuse anddependence)

Drug use disorder(Includes drug abuseand dependence)

2 %

47 %

54 %

44 %

53 %

Source: Abrams & Teplin (2010)

Perc

ent o

f Pop

ulat

ion

8 %


5%

95%

72%

83%

17% 28%

General Population Jail Population

Serious Mental Illness

No Serious Mental Illness


No Serious Mental Illness

Co-Occurring Substance Use Disorder No Co-Occurring Substance Use Disorder

Prevalence of Serious Mental Illness and Co-Occurring Disorders in Jail Populations


County Officials: “Jails are the wrong place to treat mental illnesses”

“New York City jails, like jails across the country, have disproportionately high numbers of inmates whose mental health needs present unique challenges.” -- Deputy Mayor Gibbs, Health and 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.” -- Commissioner Dora Schriro, 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.” -- Sheriff David Mahoney, Dane County, WI


“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].” -- Sheriff Tom Dart, Cook County, IL

Case Study: Florida Counties

Council of State Governments Justice Center | 28 St. Petersburg Times, November 2007

Ocala Star-Banner, November 2007 Lakeland Ledger, February 2001

Flowchart of select events in the Orange County Criminal Justice System

Council of State Governments Justice Center | 29 http://static.nicic.gov/Library/022134.pdf

Identification of mental health pretrial release program participants

http://static.nicic.gov/Library/022134.pdf

Entry into mental health pretrial release program 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

Completion of mental health pretrial release program 53,091 7,260

Offenders have satisfied their charges with the court system without further arrests. Time in 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

Not all Substance Use Disorders are Alike

Abstinence

Dependence

The Substance Use Disorder Continuum


Mental Illnesses In the General Population

Diagnosable mental

disorders 16%

Serious mental

disorders 5%

Severe mental

disorders 2.5%


Not All Mental Illnesses Are Alike

Risk/Needs Assessment 101: Science Reveals New Tools to Manage Offenders, http://www.pewstates.org/uploadedFiles/PCS_Assets/2011/Pew_Risk_Assessment_brief.pdf

Criminal Justice Risk on a Continuum


http://www.pewstates.org/uploadedFiles/PCS_Assets/2011/Pew_Risk_Assessment_brief.pdf

• Develop a shared language around the risk of criminal activity and public health needs

• Integrate the best practices in mental health treatment, substance abuse treatment, and recidivism reduction

• Help system administrators allocate scarce resources more

wisely • Maximize the impact of interventions on public safety and

public health


Why a Framework Was Needed


The Framework

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 of

Mental Illness(low)


(med/high)

Low Severity of

Mental Illness(low)


(med/high)

Low Severity of

Mental Illness(low)


(med/high)

Low Severity of

Mental Illness(low)


(med/high)

Group 1I – L CR: lowSA: lowMI: low

Group 2II – L CR: lowSA: lowMI: med/high

Group 3III – L CR: lowSA: med/highMI: low

Group 4IV – L CR: lowSA: med/highMI: med/high

Group 5I – H CR: med/highSA: lowMI: low

Group 6II – H CR: med/highSA: lowMI: med/high

Group 7III – H CR: med/highSA: med/highMI: low

Group 8IV – HCR: med/highSA: med/highMI: med/high


NYC: Why is the number of people with mental illnesses increasing in our jail?


3,319 4,391

10,257 7,557

2005 2012

M GroupNon-M Group

76% 63%

37% 24%

13,576 Total 11,948

Total

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

Pretrial 62% Sentence

d 24% State Prison

Sentence 15%

ALOS for Pretrial Admissions (Days)

79

40

81 60

ALOS for Sentenced Admissions (Days)

NYC Analyses Reveal Greatest Potential Impact by Addressing Pretrial Detainee Population


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

NYC Adopts Changes & Begins Implementation


City releases RFP for CIRT Provider Applications City starts development of IT infrastructure to share appropriate

information

December Spring Fall 2012 2013

Spring

2011 2013 Summer

2013

Mayor announces the allocation of nearly $10 million to create “Court-based Intervention and Resource Teams” (CIRTs) to serve over 3,000 clients with mental health needs annually

Justice Center Final Report City selects CIRT providers for each

borough and negotiates performance based contracts

Borough-specific implementation 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

✔−

Significant Challenge #1: No county effectively screening and assessing, and recording in an info

system


Concerns that too much information undermines defense or prosecution strategies

Confusion about distinctions between risk and need, dangerousness, and failure to appear

Few sites using information to inform conditions of release, supervision intensity, or service package

Significant Challenge #2: Results of assessment not driving decision making


Static Risk Factors Dynamic Risk Factors

Criminal history number of arrests number of convictions type of offenses Current charges Age at first arrest Current age Gender

Anti-social attitudes Anti-social friends and peers Anti-social personality pattern Substance abuse Family and/or marital factors Lack of education Poor employment history Lack of pro-social leisure activities

Significant Challenge #3: Workforce not ready to apply these concepts/strategies


Behavioral Health

Criminal Justice

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

Significant Challenge #3: Workforce not ready to apply these concepts/strategies



Overview





Texas Counties: How do we compare rates of recidivism across counties?

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


Recidivism is a Return to Criminal Activity after Previous Criminal Involvement

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 outcome (Y) within (Z) number of

months

Number of offenders under community supervision or released from custody during time period (X)

http://www.lbb.state.tx.us/Public_Safety_Criminal_Justice/Reports/UniRecid.pdf


Need Standard Definition of Recidivism

Definition Re-arrest

Percent Re-arrested One Year Uniform

Tracking Period

Uniform one, two and three year follow-up Follow-up


Harris Probation “Learning Site” Report to Judicial Officials, April 18, 2012

Re-arrest Rate for Probationers in Harris County

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%


Need to Access Data in Multiple Storage Systems

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


Need to Make Rates Comparable Across Counties by Controlling for Risk

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


Harris Probation “Learning Site” Report to Judicial Officials, April 18, 2012

Recidivism Probationers by Risk in Harris County

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

Summary

Outcome Measurement

Risk Offense level

Demographics

Key Elements

Uniform Follow-Up Period Control for Risk

365 days from release for each offender

County Jail Release: Rearrest Probation and Parole: Rearrest



Determine Logistics for Extracting Data

• Houses the data? Who

• Data is available for extraction? What

• Can the data be extracted? When • Do we need to get permission for the

extraction? Where • Do we want to structure the file

extract? How

• Leverage state county association networks to offer trainings, disseminate latest information

• Coordinate closely with state county associations when we

work intensively in a state/county • Partner with state county associations to pilot concepts in

particular sites and then replicate lessons in other counties • Imbed capacity in state county associations to provide

technical assistance to county officials


Counties Are Where It’s At


Thank You Report at: www.justicecenter.csg.org [email protected]

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.

http://www.justicecenter.csg.org/

mailto:[email protected]

Documents

County Associations and State Governments: … Center...-- Sheriff Tom Dart, Cook County, IL Case Study: Florida Counties St. Petersburg Times, November 2007 Council of State Governments