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Collaborative primary care for anxiety (general adult population)

Adult Mental Health: Anxiety
Benefit-cost methods last updated December 2023.  Literature review updated December 2016.
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Collaborative primary care for anxiety integrates behavioral health and primary care services to treat patients with anxiety disorders including panic disorder, generalized anxiety disorder, and social anxiety disorder. In the collaborative care model, a care manager coordinates with a primary care provider and other specialists, like a psychologist or psychiatrist, to develop measurement-based treatment plans for individual patients. Care managers can be mental health providers (e.g psychologists) or non-behavioral specialists (e.g registered nurses or social workers) and are located in primary care settings. In this review, patients received treatment for 6 to 12 months.
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 $5,713 Benefits minus costs $17,501
Participants $12,676 Benefit to cost ratio $18.79
Others $389 Chance the program will produce
Indirect ($293) benefits greater than the costs 91%
Total benefits $18,485
Net program cost ($984)
Benefits minus cost $17,501

^^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. 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
43 4 691 -0.244 0.088 44 -0.127 0.107 46 -0.300 0.001
43 2 198 -0.109 0.164 44 -0.057 0.201 46 -0.137 0.402
43 1 116 -0.097 0.291 44 -0.051 0.356 46 -0.123 0.772
43 1 116 0.144 0.450 44 n/a n/a n/a 0.182 0.684
43 1 82 0.236 0.293 44 n/a n/a n/a 0.298 0.354
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
Major depressive disorder Mortality associated with depression $0 $1 $0 $11 $12
Anxiety disorder Labor market earnings associated with anxiety disorder $5,335 $12,568 $0 $0 $17,904
Health care associated with anxiety disorder $377 $107 $389 $189 $1,062
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($492) ($492)
Totals $5,713 $12,676 $389 ($293) $18,485
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $834 2016 Present value of net program costs (in 2022 dollars) ($984)
Comparison costs $0 2016 Cost range (+ or -) 20%
Treatment cost estimates for this program reflect costs beyond treatment as usual. Costs are based on a weighted average of per-participants costs published in Adler et al. (2004), Katon et al. (1996), Katon et al. (1999), Rost et al. (2001), Simon et al. (2000), and Grochtdreis et al (2015). Cost-effectiveness of collaborative care for the treatment of depressive disorders in primary care: a systematic review. PLoS One 10(5): e0123078.
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

Craske, M.G., Stein, M.B., Sullivan, G., Sherbourne, C., Bystritsky, A., Rose, R.D., . . . Roy-Byrne, P. (2011). Disorder-specific impact of coordinated anxiety learning and management treatment for anxiety disorders in primary care. Archives of General Psychiatry, 68(4), 378-88.

Muntingh, A., van der Feltz-Cornelis, C., van Marwijk, H., Spinhoven, P., Assendelft, W., de Waal, M., Ader. A., van Balkom, A. (2014). Effectiveness of collaborative stepped care for anxiety disorders in primary care: a pragmatic cluster randomized controlled trial. Psychotherapy and Psychosomatics, 83(1), 37-44.

Price, D., Beck, A., Nimmer, C., & Bensen, S. (2000). The treatment of anxiety disorders in a primary care HMO setting. The Psychiatric Quarterly, 71(1), 31-45.

Rollman, B.L., Belnap, B.H., Mazumdar, S., Houck, P.R., Zhu, F., Gardner, W., . . . Shear, M.K. (2005). A randomized trial to improve the quality of treatment for panic and generalized anxiety disorders in primary care. Archives of General Psychiatry, 62(12), 1332-1341.