Managing Drug-Involved Offenders

1. Managing Drug-Involved Offenders Angela Hawken Associate Professor of Economics and Policy Analysis & James Q. Wilson Fellow Pepperdine University, Malibu Mark A.R. Kleiman Professor of Public Policy University of California, Los Angeles National Institute of Justice December 18, 2012 This project was supported by Award No. 2011-IJ-CX-K059, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this seminar are those of the author(s) and do not necessarily reflect those of the Department of Justice.

2. WHY DRUG-INVOLVED OFFENDERS MATTER To crime rates To incarceration To drug markets

3. WHY PROBATION FAILS Random severity is no substitute for swiftness and certainty.

4. IS TREATMENT THE ANSWER? The “treatment gap” Supply side Demand side Time-inconsistent preferences

5. TREATMENT MANDATES Varieties Diversion: TASC, P36 Drug courts

6. MOTIVATION FOR THE SHIFT TO TREATMENT DIVERSION • Prison and jail overcrowding • Budget pressures • Advocacy • Public opinion • Data is used selectively by advocacy groups • 3 in 4 Americans prefer treatment to incarceration for non-violent drug offenders • Little attention is paid to the public’s low tolerance for repeat offenses. 2 in 3 feel that testing positive for drugs while under community supervision should result in incarceration

7. CHARACTERISICS OF DIVERSION PROGRAMS • Mandates treatment for all; even those without a diagnosable substance abuse disorder • Treatment decisions based on self-reported behavior • Limited use of sanctions

8. CALIFORNIA IS AN IMPORTANT EXAMPLE (e.g., Prop 36) • Only 25% complete the treatment to which they were mandated. Why? • No enforcement • Poorly matched treatment • The result?

9. Increase in Arrests (30 Month follow-up) 100 80 61 60 56 Percent of offenders 43 40 40 17 17 20 10 11 6 5 4 4 0 New drug arrest New property arrest New violent arrest Referred but untreated Comparison Group Entered but did not complete treatment Completed treatment

10. OTHER IMPORTANT OUTCOMES • The spirit of the law was to help probationers who are drug-involved • Those with serious drug dependency issues received LESS care under treatment diversion • Massively displaced self-referrals to treatment • Massively displaced alcoholics (with ugly cost-benefit implications)

11. DRUG COURTS • The drug court movement has been very successful and has demonstrated good outcomes • Resource intensive =>problems with scale • And in many jurisdictions the wrong clients are being served • Eligibility and prosecutor discretion • Concern with evaluation outcomes

12. WHY DRUG COURTS FACE PROBLEMS WITH SCALE • Role of the judge: regularly scheduled meetings • Role of treatment: all clients are mandated to treatment => $$$

13. SWIFT-and-CERTAIN PROBATION • A new approach to community supervision • Potential to scale • At relatively low cost

14. TRADITIONAL PROBATION • Many rules • Behavior not closely monitored • Violations are rarely detected signals violating is OK, risk is low • Violations, when detected, are rarely sanctioned reinforces violating is OK, risk is low • Sanctions, when delivered, tend to be too harsh signals system is arbitrary and unfair

15. SWIFT-and-CERTAIN PROBATION: Principles Transparent goodwill Procedural fairness Clear warnings Close monitoring Swift, certain, proportionate sanctions

16. EXAMPLE: Hawaii’s HOPE • A swift and certain sanctions model • A move away from the trap of “too much” or “too little” • Probation conditions are actually enforced • Probationers are warned in open court • Regular random drug testing • Violations result in swift and certain but modest sanctions • No one mandated to treatment if complying (but provided if requested) • Three or more violations => mandated treatment

17. SWIFT-and-CERTAIN Examples Project Sentry DC Pretrial DC Drug Court experiment TX SWIFT/Honolulu HOPE/AZ SAFE Washington State WISP HOPE DFE NYC CLIMB

18. SWIFT-and-CERTAIN Examples Project Sentry DC Pretrial DC Drug Court experiment TX SWIFT/Honolulu HOPE/AZ SAFE Washington State WISP HOPE DFE NYC CLIMB

19. SWIFT-and-CERTAIN PROBATION:What have we learned from our studies

20. Honolulu Hawaii • The first HOPE trial was launched in Honolulu • Implemented as an intent-to-treat RCT • Eligible probationers were identified as: • Drug-involved • Demonstrated histories non-compliance • Facing high risk of revocation • We used third-party batch randomization to determine study groups

21. ASSIGNMENT TO STUDY CONDITIONS RCT using an intent-to-treat design This had important implications for outcomes.

22. ASSIGNMENT TO STUDY CONDITIONS RCT using an intent-to-treat design This had important implications for outcomes. NEW HOPE SITES RESPOND!

23. SUBJECT CHARACTERISTICS

24. DRUG OF CHOICE *Other sites have different drug mix. *Drug of choice doesn’t seem to matter.

25. OUTCOMES Hawaii RCT results at 1-year followup

26. RESOURCE ALLOCATION Among the most-important insights into offender management: Behavioral Triage

27. Distribution of positive drug tests Percentage Number of positive drug tests ** Results are from the Hawaii RCT. But a similar pattern holds at other HOPE sites

28. BEHAVIORAL TRIAGE MODEL • Not every drug users needs treatment to desist from drug use • Monitoring and treatment decisions based on probationers’observedbehavior not self-report • Allocates treatment resources more efficiently • Many drug-involved probationers do not have a diagnosable substance abuse disorder, wasting scare treatment resources and displacing self-referrals in greater need of care.

29. WHAT ELSE HAVE WE LEARNED? • From Washington WISP • Small trial (n=70) to test concept with high-risk parolees • High risk parolees respond similarly • Drug use falls (similar triage pattern to Hawaii) • Incarceration days fall (mostly driven by pre-hearing confinement) • Can WISP go to scale? • It has……

30. WHAT ELSE HAVE WE LEARNED? • From Hawaii – for probationers entering after year 1, results are not nearly as rosy. • WHY? • The researchers went away! • No more monitoring => reduced fidelity • File reviews show that outcomes track closely with fidelity • What to do? • Get smart about operational details. Are you FIT?

31. WHAT ELSE HAVE WE LEARNED? • From Hawaii – magnitude of sanction doesn’t seem to matter. • Differential judge sentencing didn’t affect outcomes, only drove up cost • Most HOPE sites now focus on modest sanctions

32. WHAT HAVE WE LEARNED? • From Arizona – How Often is Often Enough? • Drug testing is expensive (cost of tests and staff time, burden on probationer and probation office) • Probation department interested to know if reduced testing would yield similar results • They tried • It didn’t! • What to do? • We have a proposal under review to identify an optimal testing strategy. • Ties in well with new Behavioral Econ literature on perceptions of probability of detection

33. WHAT ELSE HAVE WE LEARNED? • From thousands of hours in the field…… • Not all good ideas originate in universities and think tanks • There’s a disconnect between the suppliers of good ideas (often practitioners) and the evaluators (the PhDs) who get to bless (or not) their programs • Many great ideas are never tested • Many bad programs linger • The timeline to produce new knowledge is too long • We could have 500 pilot CJ RCTs a year, rather than 5!

34. SERVICES AND SUPERVISION As competitors As complements Swift&Sure re-entry Job development Reputational externality

35. UNKNOWNS Optimal sanctions Initial sanction: is confinement necessary? Escalation When (if) to revoke? Services mix (methadone/buprenorphine?) Service mandates? Program/client matching

36. PSYCHOLOGICAL MECHANISMS Beyond deterrence Locus-of-control and self-command

37. JUSTICE REINVESMENT IN COMMUNITY SUPERVISION Incarceration costs $25k/yr. Close supervision costs $2.5k/yr. Reduce prison headcount Increase community supervision Reduce crime