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Washington State Institute for Public Policy
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Police diversion for individuals with mental illness (pre-arrest)

Adult Criminal Justice
Benefit-cost methods last updated December 2023.  Literature review updated March 2017.
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Diversion programs for individuals with mental illness redirect these individuals from the traditional criminal justice system into mental health treatment programs.
This review focuses on pre-arrest diversion programs, which are police-based programs. Police-based diversion programs divert participants to services without applying criminal charges. Programs included in this meta-analysis followed the Crisis Intervention Team model, which involves specialized police training and partnerships between police and mental health providers in the community. Mental health courts and post-arrest diversion programs were reviewed separately from this meta-analysis.
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 ($2,213) Benefits minus costs ($20,976)
Participants ($610) Benefit to cost ratio ($2.72)
Others ($3,031) Chance the program will produce
Indirect ($9,489) benefits greater than the costs 24%
Total benefits ($15,343)
Net program cost ($5,633)
Benefits minus cost ($20,976)

^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
37 3 290 0.089 0.081 39 0.089 0.081 49 0.089 0.275
37 3 290 0.068 0.170 37 0.000 0.187 40 0.068 0.690
37 3 290 0.325 0.205 37 0.000 0.187 40 0.325 0.113
37 3 290 0.036 0.081 37 n/a n/a n/a 0.036 0.659
37 3 290 0.289 0.388 37 0.000 0.118 38 0.289 0.456
37 3 290 0.059 0.186 37 n/a n/a n/a 0.059 0.751
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 ($1,322) $0 ($2,334) ($661) ($4,317)
Alcohol use disorder Property loss associated with alcohol abuse or dependence $0 ($1) ($2) $0 ($2)
Illicit drug use disorder Labor market earnings associated with illicit drug abuse or dependence ($159) ($375) $0 $0 ($534)
Health care associated with illicit drug abuse or dependence ($677) ($105) ($696) ($339) ($1,816)
Mortality associated with illicit drugs ($55) ($130) $0 ($5,673) ($5,858)
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($2,816) ($2,816)
Totals ($2,213) ($610) ($3,031) ($9,489) ($15,343)
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $8,347 2016 Present value of net program costs (in 2022 dollars) ($5,633)
Comparison costs $3,537 2015 Cost range (+ or -) 10%
Program costs include general program administration/coordination costs from Cowell et al., 2015 combined with the difference in treatment costs between experimental and control groups in Cowell et al., 2004. Control group costs are from WSIPP’s internal estimates of the cost of 77 days of jail. Cowell, A. J., Hinde, J. M., Broner, N., & Aldridge, A. P. (2015). The cost of implementing a jail diversion program for people with mental illness in San Antonio, Texas. Evaluation and Program Planning, 48, 57–62. Cowell, A.J., Broner, N., & Dupont, R. (2004). The Cost-effectiveness of criminal justice diversion programs for people with serious mental illness co-occurring with substance abuse four case studies. Journal of Contemporary Criminal Justice, 20(3), 292-314.
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

Broner, N., Lattimore, P.K., Cowell, A.J., & Schlenger, W.E. (2004). Effects of diversion on adults with co-occurring mental illness and substance use: Outcomes from a national multi-site study. Behavior Sciences and the Law, 22(4), 519-541.