Washington State Institute for Public Policy
Collaborative primary care for depression with comorbid medical conditions
Adult Mental Health: Depression
Benefit-cost estimates updated December 2016.  Literature review updated May 2014.
A care manager collaborates with the primary care provider, mental health specialists, and other providers to develop treatment plans for each patient. The care manager manages these treatment plans and follows up with patients to ensure treatment adherence. Care managers predominantly focus their efforts on improving depression and chronic illness symptoms.
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2015). 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 $1,255 Benefits minus costs $2,775
Participants $1,653 Benefit to cost ratio $4.24
Others $734 Chance the program will produce
Indirect ($9) benefits greater than the costs 92 %
Total benefits $3,632
Net program cost ($857)
Benefits minus cost $2,775
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
Labor market earnings associated with major depression $663 $1,459 $0 $122 $2,244
Health care associated with major depression $592 $193 $734 $295 $1,814
Adjustment for deadweight cost of program $0 $0 $0 ($426) ($426)
Totals $1,255 $1,653 $734 ($9) $3,632
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $831 2012 Present value of net program costs (in 2015 dollars) ($857)
Comparison costs $0 2012 Cost range (+ or -) 15 %
Per-participant costs include telephone contacts, in-person contacts, supervision & information support, screening, educational materials, and time spent with a primary care provider. Costs were obtained from Ell et al. (2010). Collaborative care management of major depression among low-income, predominantly Hispanic subjects with diabetes: A randomized controlled trial. Diabetes Care, 33(4), 706-713. Our cost estimate is based on the average number of telephone and in-person contacts from studies. There is a wide variation of cost, since the time the care manager spent with each patient varied.
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.

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
Major depressive disorder 11 1049 -0.353 0.096 62 -0.173 0.104 64 -0.353 0.001
Health care costs 2 224 -0.076 0.152 62 -0.037 0.165 64 -0.076 0.619
Blood pressure 4 326 -0.369 0.183 62 -0.181 0.198 64 -0.369 0.043
Blood sugar 3 279 -0.254 0.134 62 -0.124 0.146 64 -0.254 0.059
Citations Used in the Meta-Analysis

Bogner, H.R., & de Vries, H.F. (2008). Integration of depression and hypertension treatment: A pilot, randomized controlled trial. Annals of Family Medicine, 6(4), 295-301.

Bogner, H.R., & de Vries, H.F. (2010). Integrating type 2 diabetes mellitus and depression treatment among African Americans a randomized controlled pilot trial. The Diabetes Educator, 36(2), 284-292.

Bogner, H.R., de Vries, H.F., Kaye, E. M., & Morales, K.H. (2013). Pilot trial of a licensed practical nurse intervention for hypertension and depression. Family Medicine, 45(5), 323-329.

Davidson, K.W., Rieckmann, N., Clemow, L., Schwartz, J. E., Shimbo, D., Medina, V., . . . Burg, M.M. (2010). Enhanced depression care for patients with acute coronary syndrome and persistent depressive symptoms: Coronary psychosocial evaluation studies randomized controlled trial. Archives of Internal Medicine, 170(7), 600-608.

Davidson, K. W., Bigger, J. T., Burg, M. M., Duer-Hefele, J., Medina, V., Newman, J. D., . . . Vaccarino, V. (2013). Centralized, stepped, patient preference-based treatment for patients with post-acute coronary syndrome depression: CODIACS vanguard randomized controlled trial. JAMA Internal Medicine, 173(11), 997-1004.

Ell, K., Katon, W., Xie, B., Lee, P. J., Kapetanovic, S., Guterman, J., & Chou, C. P. (2010). Collaborative care management of major depression among low-income, predominantly Hispanic subjects with diabetes: A randomized controlled trial. Diabetes Care, 33(4), 706-713.

Katon, W.J., Von Korff, M., Lin, E. H., Simon, G., Ludman, E., Russo, J., . . . Bush, T. (2004). The Pathways Study: A randomized trial of collaborative care in patients with diabetes and depression. Archives of General Psychiatry, 61(10), 1042-1049.

Katon, W.J., Lin, E.H., Von, K.M., Ciechanowski, P., Ludman, E. J., Young, B., . . . McCulloch, D. (2010). Collaborative care for patients with depression and chronic illnesses. The New England Journal of Medicine, 363(27), 2611-2620.

Morgan, M.A.J., Coates, M.J., Dunbar, J.A., Schlicht, K., Reddy, P., & Fuller, J. (2013). The TrueBlue model of collaborative care using practice nurses as case managers for depression alongside diabetes or heart disease: A randomised trial. British Medical Journal Open, 3(1).

Rollman, B.L., Belnap, B.H., LeMenager, M.S., Mazumdar, S., Houck, P.R., Counihan, P.J., . . . Reynolds, C.F. (2009). Telephone-delivered collaborative care for treating post-CABG depression: A randomized controlled trial. JAMA : The Journal of the American Medical Association, 302(19), 2095-2103.

Williams, L.S., Kroenke, K., Bakas, T., Plue, L.D., Brizendine, E., Tu, W., & Hendrie, H. (2007). Care management of poststroke depression: A randomized, controlled trial. Stroke, 38(3), 998-1003.

For more information on the methods
used please see our Technical Documentation.