Washington State Institute for Public Policy
Case management ("swift, certain, and fair") for drug-involved persons
Adult Criminal Justice
Benefit-cost estimates updated May 2017.  Literature review updated November 2016.
In general, case management is a process that coordinates and monitors services on behalf of a participant. The studies included in this meta-analysis evaluate a variety of case management approaches for individuals involved in the criminal justice system who have histories of drug involvement and are being supervised in the community under a “swift, certain, and fair” approach. The primary goals of case management for this population are 1) to improve collaboration between correctional staff and substance abuse treatment staff and 2) to increase participation in substance abuse treatment.

Case managers or specially-trained supervision officers use a variety of strategies to assess the participant’s treatment and programming needs, coordinate access to substance abuse treatment, monitor the participant, and advocate on the participant’s behalf. In some circumstances, the case manager or officer can provide these services, such as counseling or therapy, directly to the client. Program length ranges from three to six months.

“Swift, certain and fair” is an approach to community supervision wherein participants receive immediate sanctions when they violate the conditions of supervision. Sanction severity is proportional to the severity of the violation, with minor violations resulting in only a few days of incarceration. In response to repeat violations, sanctions gradually increase in severity. Participants are required to check in with their supervising officer regularly and are tested frequently and randomly for substance use. Case management studies that did not incorporate "swift, certain, and fair" approach were analyzed separately.
BENEFIT-COST
META-ANALYSIS
CITATIONS
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2016). The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $4,389 Benefits minus costs $15,451
Participants $9 Benefit to cost ratio n/a
Others $8,275 Chance the program will produce
Indirect $2,398 benefits greater than the costs 100 %
Total benefits $15,069
Net program cost $381
Benefits minus cost $15,451
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Benefits from changes to:1 Benefits to:
Taxpayers Participants Others2 Indirect3 Total
Crime $4,380 $0 $8,270 $2,203 $14,853
Labor market earnings associated with illicit drug abuse or dependence $4 $8 $0 $0 $12
Health care associated with illicit drug abuse or dependence $5 $1 $5 $2 $13
Adjustment for deadweight cost of program $0 $0 $0 $191 $191
Totals $4,389 $9 $8,275 $2,398 $15,069
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $3,972 2016 Present value of net program costs (in 2016 dollars) $381
Comparison costs $4,353 2016 Cost range (+ or -) 10 %
There are three components of this per participant cost estimate. First, the cost of supervision is based on WSIPP's analysis (see Technical Documentation) of community supervision delivered by the Washington State Department of Corrections. Second, we include the cost of violation behavior. For this estimate, we rely on the cost of violations for the treatment group in Hamilton, Z., van Wormer, J., Kigerl, A., Campbell, C., & Posey. B. (2015). Evaluation of Washington State Department of Corrections Swift and Certain Policy Process, Outcome and Cost-Benefit Evaluation. Washington State University. Finally, we include the cost for the Washington State Department of Corrections to provide outpatient substance abuse treatment with the assumption that most persons on supervision are required to engage in treatment. We assume both the treatment and comparison groups receive community supervision, but that treatment participants incur less violation costs. We assume 50% of the treatment group receives substance abuse treatment.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Estimated Cumulative Net Benefits Over Time (Non-Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in non-discounted dollars to simplify the “break-even” point from a budgeting perspective. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

^WSIPP’s benefit-cost model does not monetize this outcome.

^^WSIPP does not include this outcome when conducting benefit-cost analysis for this program.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease over time. For those effect sizes, we estimate outcome-based adjustments which we apply between the first time ES is estimated and the second time ES is estimated. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Primary or secondary participant No. of effect sizes Treatment N Adjusted effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
Crime 9 4570 -0.183 0.072 33 -0.183 0.072 43 -0.174 0.023
Illicit drug use disorder 3 777 -0.050 0.249 31 0.000 0.187 34 -0.050 0.842
Illicit drug use^ 4 962 -0.287 0.115 31 0.000 0.187 34 -0.287 0.013
Technical violations^^ 2 514 -0.260 0.105 33 -0.260 0.105 43 -0.260 0.013
Citations Used in the Meta-Analysis

Baird, C., Wagner, D., Decomo, B., & Aleman, T. (1994). Evaluation of the effectiveness of supervision and community rehabilitation programs in Oregon. San Francisco: National Council on Crime and Delinquency.

Grommon, E., Cox, S.M., Davidson, W.S., & Bynum, T.S. (2012). Alternative models of instant drug testing: evidence from an experimental trial. Journal of Experimental Criminology, 9(2), 145-168.

Grommon, E., Davidson, I.I. W.S., & Bynum, T.S. (2013). A randomized trial of a multimodal community-based prisoner reentry program emphasizing substance abuse treatment. Journal of Offender Rehabilitation, 52(4), 287-309.

Harrell, A., Mitchell, O., Hirst, A., Marlow, D., & Merrill, J. (2002). Breaking the cycle of drugs and crime: Findings from the Birmingham BTC demonstration. Criminology and Public Policy, 1(2), 189-216.

Harrell, A., Roman, J., Bhati, A., & Parthasarathy, B. (2003). The impact evaluation of the Maryland Break the Cycle initiative. Washington, DC: The Urban Institute.

Hawken, A., & Kleiman, M. (2009). Managing drug involved probationers with swift and certain sanctions: Evaluating Hawaii's HOPE. Malibu, CA: Pepperdine University, School of Public Policy.

Hawken, A., Kulick, J., Smith, K., Mei, J., Zhang, Y., Jarman, S., Yu, T., Carson, C., Vial, T. (2016). HOPE II: A Follow-up to Hawaiʻi’s HOPE Evaluation.

Mitchell, O., & Harrell, A. (2006). Evaluation of the breaking the cycle demonstration project: Jacksonville, FL and Tacoma, WA. Journal of Drug Issues, 36(1), 97-118.

O'Connell, D.J., Brent, J.J., & Visher, C.A. (2016). Decide your time: A randomized trial of a drug testing and graduated sanctions program for probationers. Criminology & Public Policy, 15(4), 1073-1102.

For more information on the methods
used please see our Technical Documentation.
360.664.9800
institute@wsipp.wa.gov