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Interventions to reduce unnecessary emergency department visits: Asthma self-management education for children

Healthcare: Healthcare System Efficiency
Benefit-cost methods last updated December 2024.  Literature review updated December 2014.
This program was archived December 2024.
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.
 
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 (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 2023 Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $12 Benefits minus costs ($96)
Participants $4 Benefit to cost ratio ($0.05)
Others $20 Chance the program will produce
Indirect ($40) benefits greater than the costs 45%
Total benefits ($5)
Net program cost ($92)
Benefits minus cost ($96)

^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 2023 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
7 10 1342 0.015 0.101 8 0.000 0.086 10 0.153 0.475
7 7 688 -0.088 0.124 8 0.000 0.086 10 -0.088 0.475
7 4 142 0.002 0.219 8 n/a n/a n/a 0.002 0.994
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
Hospitalization Health care associated with general hospitalization ($5) $0 ($5) ($3) ($13)
Emergency department visits Health care associated with emergency department visits $17 $5 $25 $8 $54
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($46) ($46)
Totals $12 $4 $20 ($40) ($5)
Click here to see populations selected
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $77 2014 Present value of net program costs (in 2022 dollars) ($92)
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 2023 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

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.