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Washington State Institute for Public Policy
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Mental health courts

Adult Criminal Justice
Benefit-cost methods last updated December 2023.  Literature review updated October 2016.
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Mental health courts, modeled after other therapeutic courts (e.g., drug courts, DUI courts), divert individuals with mental health issues from incarceration to treatment in the community. These courts use mental health assessments, individualized treatment plans, intensive case management, and judicial monitoring with the goal of providing participants with the resources needed to avoid criminal behavior while improving public safety. Most programs have a graduated system of requirements, meaning that as participants progress through the program, assessment and monitoring become less frequent. In some courts, charges are dropped with successful completion of the program. Programs can vary in length; the programs represented in this meta-analysis range from 6-24 months of delivered services.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2022). 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 $5,889 Benefits minus costs $16,665
Participants $0 Benefit to cost ratio $5.56
Others $13,312 Chance the program will produce
Indirect $1,118 benefits greater than the costs 95%
Total benefits $20,319
Net program cost ($3,653)
Benefits minus cost $16,665

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

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. See Estimating Program Effects Using Effect Sizes for additional information.

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 Treatment age 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
36 6 1424 -0.168 0.075 38 -0.168 0.075 48 -0.223 0.001
36 2 211 -0.316 0.330 36 n/a n/a n/a -0.309 0.359
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
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
Crime Criminal justice system $5,889 $0 $13,312 $2,944 $22,145
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($1,827) ($1,827)
Totals $5,889 $0 $13,312 $1,118 $20,319
Click here to see populations selected
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $2,656 2006 Present value of net program costs (in 2022 dollars) ($3,653)
Comparison costs $0 2006 Cost range (+ or -) 10%
Per-participant cost estimate from Ridgely, M.S., Engberg, J., Greenberg, M.D., Turner, S., DeMartini, C., & Dembosky, J.W. (2007). Justice, treatment, and cost: An evaluation of the fiscal impact of Allegheny County Mental Health Court. Santa Monica, CA: RAND.
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.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative 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 discounted dollars. 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.

Citations Used in the Meta-Analysis

Boothroyd, R.A., Mercado, C.C., Poythress, N.G., Christy, A., & Petrila, J. (2005). Clinical outcomes of defendants in mental health court. Psychiatric Services, 56(7), 829-834.

Christy, A., Poythress, N.G., Boothroyd, R.A., Petrila, J., & Mehra, S. (2005), Evaluating the efficiency and community safety goals of the Broward County Mental Health Court. Behavioral Sciences & the Law, 23(2), 227-243.

Cosden, M., Ellens, J., Schnell, J. & Yamini-Diouf, J. (2004). Evaluation of the Santa Barbara County Mental Health Treatment Court with intensive case management. Santa Barbara: University of California, Santa Barbara; Gervitz Graduate School of Education.

Dirks-Linhorst, P.A., & Linhorst, D.M. (2010). Recidivism outcomes for suburban mental health court defendants. American Journal of Criminal Justice. Advance online publication. DOI 10.1007/s12103-010-9092-0

McNiel, D.E., & Binder, R.L. (2007). Effectiveness of a mental health court in reducing criminal recidivism and violence. American Journal of Psychiatry, 164(9), 1395-1403.

Moore, M.E., & Hiday, V.A. (2006). Mental health court outcomes: A comparison of re-arrest and re-arrest severity between mental health court and traditional court participants. Law and Human Behavior, 30(6), 659-674.

Steadman, H.J., Redlich, A., Callahan, L., Robbins, P.C., & Vesselinov, R. (2011). Effect of mental health courts on arrests and jail days: A multisite study. Archives of General Psychiatry, 68(2), 167-172.