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Contingency management (lower cost) for opioid use disorder

Substance Use Disorders: Treatment for Adults
Benefit-cost methods last updated December 2024.  Literature review updated December 2016.
Contingency management is a supplement to counseling treatment that rewards participants for attending treatment and/or abstaining from substance use. The intervention reviewed here focused on those with opiate abuse or dependence who were also receiving medicated-assisted drug treatment (methadone, buprenorphine or naloxone) and counseling. Contingencies were provided for remaining abstinent. Two methods of contingency management were reviewed: (1) A voucher system where abstinence earned vouchers that were exchangeable for goods provided by the clinic or counseling center, (2) a prize or raffle system where clients who remained abstinent could earn the opportunity to draw from a prize bowl. Treatment in the included studies lasted between 1 and 6 months with a weighted average of 3.3 months of contingency management and reward opportunities occurring two to three times per week, on average. The value of contingencies in the programs reviewed ranged from $59-$253 per participant, with an average of $168 (in 2016 dollars).

Based on a statistical analysis of contingency management studies, we determined that programs with a maximum value of vouchers or prizes less than or equal to $500 (in 2012 dollars) represent lower-cost contingency management.
 
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 (2023).  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 $877 Benefits minus costs $4,749
Participants $1,132 Benefit to cost ratio $11.91
Others $418 Chance the program will produce
Indirect $2,756 benefits greater than the costs 59%
Total benefits $5,184
Net program cost ($435)
Benefits minus cost $4,749

^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 to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on 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 on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change 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. 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 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
Opioid use disorder
Clinical diagnosis of opioid use disorder or symptoms on a validated scale.
38 9 520 -0.291 0.068 38 0.000 0.075 39 -0.291 0.001
Engagement/Retention^
Retention and engagement in treatment or care.
 38 7 433 0.314 0.145 38 n/a n/a n/a 0.314 0.031
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
Opioid use disorder Criminal justice system $0 $0 $0 $0 $0
Labor market earnings associated with opioid drug abuse or dependence $322 $759 $0 $0 $1,081
Health care associated with opioid drug abuse or dependence $421 $57 $418 $211 $1,107
Mortality associated with opioids $134 $316 $0 $2,763 $3,214
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($218) ($218)
Totals $877 $1,132 $418 $2,756 $5,184
Click here to see populations selected
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $1,007 2016 Present value of net program costs (in 2023 dollars) ($435)
Comparison costs $651 2016 Cost range (+ or -) 10%
Program cost estimates reflect costs beyond treatment as usual. The per-participant cost of treatment is based on physician/therapist time, multiplied by Medicaid reimbursement rates, plus the average amount of incentive received by treatment participants. Reimbursement rates are based on individual or group treatment sessions for non-disabled adults in Mercer (2016) Mental Health and Substance Use Disorder Services Data Book for the State of Washington. Program and comparison group costs are weighted by treatment and comparison group samples. Costs were obtained from Carroll et al. (2001), Hser et al. (2011), Kidorf et al. (2013), Preston et al. (2000), and Preston et al. (2002).
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

Brooner, R.K., Kidorf, M.S., King, V.L., Stoller, K.B., Neufeld, K.J., & Kolodner, K. (2007). Comparing adaptive stepped care and monetary-based voucher interventions for opioid dependence. Drug and Alcohol Dependence, 88, S14-S23.

Carroll, K.M., Ball, S.A., Nich, C., O'Connor, P.G., Eagan, D.A., Frankforter, . . . Rounsaville, B.J. (2001). Targeting behavioral therapies to enhance naltrexone treatment of opioid dependence: efficacy of contingency management and significant other involvement. Archives of General Psychiatry, 58(8), 755-761.

Chen, W., Hong, Y., Zou, X., McLaughlin, M.M., Xia, Y., & Ling, L. (2013). Effectiveness of prize-based contingency management in a methadone maintenance program in China. Drug and Alcohol Dependence, 133(1), 270-274.

Hser, Y.I., Li, J., Jiang, H., Zhang, R., Du, J., Zhang, C., Zhang, B., . . . Zhao, M. (2011). Effects of a randomized contingency management intervention on opiate abstinence and retention in methadone maintenance treatment in China. Addiction, 106(10), 1801-1809.

Kidorf, M., Brooner, R.K., Gandotra, N., Antoine, D., King, V.L., Peirce, J., & Ghazarian, S. (2013). Reinforcing integrated psychiatric service attendance in an opioid-agonist program: A randomized and controlled trial. Drug and Alcohol Dependence, 133(1), 30-36.

Ling, W., Hillhouse, M., Ang, A., Jenkins, J., & Fahey, J. (2013). Comparison of behavioral treatment conditions in buprenorphine maintenance. Addiction, 108(10), 1788-1798.

Preston, K.L., Umbricht, A., & Epstein, D.H. (2000). Methadone dose increase and abstinence reinforcement for treatment of continued heroin use during methadone maintenance. Archives of General Psychiatry, 57(4), 395-404.

Preston, K.L., Umbricht, A., & Epstein, D.H. (2002). Abstinence reinforcement maintenance contingency and one-year follow-up. Drug and Alcohol Dependence, 67(2), 125-137.

Rowan-Szal, G.APD., Joe, GWED., Hiller, MLPD., & Simpson, DDPD. (1997). Increasing early engagement in methadone treatment. Journal of Maintenance in the Addictions, 1(1), 49-61.