Washington State Institute for Public Policy
Interventions to reduce unnecessary emergency department visits: Asthma self-management education for children
Health Care: System Efficiency
Benefit-cost estimates updated December 2016.  Literature review updated December 2014.
Asthma self-management education aims to manage asthma symptoms and avoid emergency department visits by teaching children to identify and avoid asthma triggers, recognize symptoms, and take appropriate action to manage symptoms. In the studies included in this analysis, asthma self-management education was typically delivered by a social worker, nurse, or computer program. We included interventions delivered to children or children and their families in an individuals or group setting. This analysis focuses on interventions initiated in the healthcare system.
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 (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 $28 Benefits minus costs ($36)
Participants $5 Benefit to cost ratio $0.53
Others $31 Chance the program will produce
Indirect ($22) benefits greater than the costs 50 %
Total benefits $41
Net program cost ($77)
Benefits minus cost ($36)
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
Health care associated with general hospitalization $5 $0 $5 $4 $15
Health care associated with emergency department visits $22 $4 $26 $12 $64
Adjustment for deadweight cost of program $0 $0 $0 ($39) ($39)
Totals $28 $5 $31 ($22) $41
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $77 2014 Present value of net program costs (in 2015 dollars) ($77)
Comparison costs $0 2014 Cost range (+ or -) 25 %
The asthma self-management education programs that we reviewed required an average of 1.14 hours of staff time per child. A nurse educator provided the self-management education in most of these programs. We estimated the cost of the program by multiplying the hours of staff time by the average registered nurse's hourly salary in Washington State (http://www.bls.gov/oes/current/oes_wa.htm#29-0000). This product is then multiplied by the ratio of total compensation to wages described in WSIPP's Technical Documentation.
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
Hospitalization 10 1342 0.015 0.101 8 0.000 0.086 10 0.153 0.475
Emergency department visits 7 688 -0.088 0.124 8 0.000 0.086 10 -0.088 0.475
School attendance 4 142 0.002 0.219 8 0.002 0.219 8 0.002 0.994
Citations Used in the Meta-Analysis

Alexander, J.S., Younger, R.E., Cohen, R.M., & Crawford, L.V. (1988). Effectiveness of a nurse-managed program for children with chronic asthma. Journal of Pediatric Nursing, 3(5), 312-317.

Clark, N.M., Feldman, C.H., Evans, D., Levison, M.J., Wasilewski, Y., & Mellins, R.B. (1986). The impact of health education on frequency and cost of health care use by low income children with asthma. The Journal of Allergy and Clinical Immunology, 78(1), 108-15.

Evans, R. ., Gergen, P.J., Mitchell, H., Kattan, M., Kercsmar, C., Crain, E., Anderson, J., ... Wedner, H.J. (1999). A randomized clinical trial to reduce asthma morbidity among inner-city children: results of the National Cooperative Inner-City Asthma Study. The Journal of Pediatrics, 135(3), 332-338.

Farber, H.J., & Oliveria, L. (2004). Trial of an Asthma Education Program in an Inner-City Pediatric Emergency Department. Pediatric Asthma, Allergy & Immunology, 17(2), 107-115.

Fireman, P., Friday, G.A., Gira, C., Vierthaler, W.A., & Michaels, L. (1981). Teaching self-management skills to asthmatic children and their parents in an ambulatory care setting. Pediatrics, 68(3), 341-8.

Homer, C., Susskind, O., Alpert, H.R., Owusu, M., Schneider, L., Rappaport, L.A., & Rubin, D.H. (2000). An evaluation of an innovative multimedia educational software program for asthma management: report of a randomized, controlled trial. Pediatrics, 106(1), 210-205.

Lukacs, S.L., France, E.K., Barón, A.E., & Crane, L.A. (2002). Effectiveness of an asthma management program for pediatric members of a large health maintenance organization. Archives of Pediatrics & Adolescent Medicine, 156(9), 872-876.

Madge, P., McColl, J., & Paton, J. (1997). Impact of a nurse-led home management training programme in children admitted to hospital with acute asthma: a randomised controlled study. Thorax, 52(3), 223-228.

Mitchell, E.A., Ferguson, V., & Norwood, M. (1986). Asthma education by community child health nurses. Archives of Disease in Childhood, 61(12), 1184-1189.

Rubin, D.H., Leventhal, J.M., Sadock, R.T., Letovsky, E., Schottland, P., Clemente, I., & McCarthy, P. (1986). Educational intervention by computer in childhood asthma: a randomized clinical trial testing the use of a new teaching intervention in childhood asthma. Pediatrics, 77(1), 1-10.

Shields, M.C. (1990). The Effect of a Patient Education Program on Emergency Room Use for Inner-City Children with Asthma. American Journal of Public Health, 80(1), 36-38.

Stevens, C.A., Wesseldine, L.J., Couriel, J.M., Dyer, A.J., Osman, L.M., & Silverman, M. (2002). Parental education and guided self-management of asthma and wheezing in the pre-school child: a randomised controlled trial. Thorax, 57(1), 39-44.

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