Washington State Institute for Public Policy
Case management in schools
Pre-K to 12 Education
Benefit-cost estimates updated May 2017.  Literature review updated June 2014.
Case management involves placing a full-time social worker or counselor in a school to help identify at-risk students’ needs and connect students and families with relevant services in and outside of the K–12 system. Three such models have been evaluated and are included in this analysis are (in no particular order) Communities in Schools, City Connects, and Comer School Development Program. In practice, each of these models includes other services (such as extended learning time and educator training), but the program evaluations focus on the impact of the case management component.
BENEFIT-COST
META-ANALYSIS
CITATIONS
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2016). 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 $4,315 Benefits minus costs $14,431
Participants $7,475 Benefit to cost ratio $64.07
Others $2,714 Chance the program will produce
Indirect $156 benefits greater than the costs 96 %
Total benefits $14,660
Net program cost ($229)
Benefits minus cost $14,431
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
Crime $30 $0 $68 $15 $113
Labor market earnings associated with high school graduation $3,773 $8,309 $3,802 $0 $15,884
K-12 grade repetition $0 $0 $0 $0 $0
K-12 special education $3 $0 $0 $1 $4
Property loss associated with alcohol abuse or dependence $0 $0 $0 $0 $0
Health care associated with educational attainment $899 ($246) ($980) $450 $124
Costs of higher education ($390) ($588) ($176) ($196) ($1,350)
Adjustment for deadweight cost of program $0 $0 $0 ($115) ($115)
Totals $4,315 $7,475 $2,714 $156 $14,660
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $222 2013 Present value of net program costs (in 2016 dollars) ($229)
Comparison costs $0 2013 Cost range (+ or -) 10 %
To calculate a per-student annual cost, we used average compensation costs (including benefits) for a social worker as reported by the Office of the Superintendent of Public Instruction, divided by the number of students in a prototypical elementary school. The estimate also includes a half-hour of principal and administrative support time per week.
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.

^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.

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
Alcohol use before end of middle school 3 6199 0.002 0.085 12 0.002 0.085 12 0.032 0.705
Cannabis use before end of middle school 3 6199 0.001 0.085 12 0.001 0.085 12 0.013 0.880
Externalizing behavior symptoms 1 573 -0.016 0.161 12 -0.008 0.083 15 -0.325 0.044
Grade point average^ 7 7448 0.113 0.037 12 0.115 0.148 13 0.097 0.328
High school graduation 3 1335 0.109 0.059 18 0.109 0.059 18 0.215 0.191
Illicit drug use before end of middle school 4 6772 -0.002 0.075 12 -0.002 0.075 12 -0.034 0.654
Internalizing symptoms 4 6772 -0.002 0.075 12 -0.001 0.055 14 -0.030 0.686
Office discipline referrals^ 3 252 0.194 0.149 12 0.141 0.162 13 0.194 0.192
School attendance^ 6 8095 -0.007 0.042 12 0.002 0.054 13 -0.007 0.867
Smoking before end of middle school 3 6199 0.001 0.085 12 0.001 0.085 12 0.015 0.862
Suspensions/expulsions^ 4 1321 -0.025 0.110 12 -0.025 0.110 12 -0.025 0.819
Test scores 11 8553 0.026 0.026 12 0.020 0.028 17 0.061 0.018
Citations Used in the Meta-Analysis

Cook, T.D., Phillips, M., Settersten, R.A., Shagle, S.C., Degirmencioglu, S.M., & Habib, F.N. (1999). Comer's School Development Program in Prince George's County, Maryland: A theory-based evaluation. American Educational Research Journal, 36(3), 543-597.

Cook, T.D., Murphy, R.F., & Hunt, H.D. (2000). Comer's school development program in Chicago: A theory-based evaluation. American Educational Research Journal, 37(2), 535-597.

Corrin, W., Parise, L., Cerna, O., Haider, Z., and Somers, M.A. (2015). Case management for students at risk of dropping out: Implementation and interim impact findings from the Communities in Schools Evaluation. New York: MDRC.

ICF International. (2008). Communities in Schools National Evaluation, Volume 1: School-level report. Retrieved from http://www.communitiesinschools.org/media/uploads/attachments/CIS_School_Level_Report_Volume_1.pdf.

ICF International. (2010). Communities in Schools National Evaluation Volume 6: Randomized Controlled Trial Study, Wichita, Kansas. Http://www.communitiesinschools.org/media/uploads/attachments/CIS_RCT_Study_Wichita_Volume_6.pdf

ICF International. (2010). Communities in Schools National Evaluation Volume 4: Randomized Controlled Trial Study, Jacksonville, Florida. Http://www.communitiesinschools.org/media/uploads/attachments/CIS_RCT_Study_Jacksonville_Volume_4.pdf

ICF International. (2010). Communities in Schools National Evaluation Volume 5: Randomized Controlled Trial Study, Austin, Texas. Http://www.communitiesinschools.org/media/uploads/attachments/CIS_RCT_Study_Austin_Volume_5_final.pdf

Walsh, M., Foley, C., Denny, B.R., Lindsay, L., Coyle, J., & Howard, M. (2012). The impact of City Connects (Progress report 2012). Boston: Boston College Center for Optimized Student Support

Walsh, M., Foley, C., Denny, B.R., Lindsay, L., Coyle, J., & Howard, M. (2011). The impact of City Connects (Annual report 2011). Boston: Boston College Center for Optimized Student Support

For more information on the methods
used please see our Technical Documentation.
360.664.9800
institute@wsipp.wa.gov