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Multicomponent interventions including exercise and home hazard reduction (high-risk population)

Health Care: Falls Prevention for Older Adults
Benefit-cost methods last updated December 2019.  Literature review updated January 2018.
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Multicomponent programs provide a combination of two or more interventions designed to prevent falls by older adults. This analysis includes a single study of an intervention that delivered a combined exercise and home hazard reduction program for community-dwelling adults aged 75 and older who were at high risk for falls due to visual impairment. Participants received a one-year Otago Exercise Program. A physiotherapist prescribed the individualized exercises via home visits at weeks one, two, four, and eight and then again after six months. For the entire year of the intervention, participants were also expected to independently exercise at least three times a week and to walk outside twice a week when possible. Participants’ homes were also assessed by an occupational therapist for hazards that could increase the risk of falling. The occupational therapist facilitated the provision of equipment or payment to modify or remove those hazards.
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 (2018). 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 $1,174 Benefits minus costs $7,571
Participants $148 Benefit to cost ratio $8.51
Others $183 Chance the program will produce
Indirect $7,073 benefits greater than the costs 100 %
Total benefits $8,578
Net program cost ($1,008)
Benefits minus cost $7,571
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 falls $1,174 $148 $183 $587 $2,092
Mortality associated with falls $0 $0 $0 $6,990 $6,990
Adjustment for deadweight cost of program $0 $0 $0 ($504) ($504)
Totals $1,174 $148 $183 $7,073 $8,578
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $970 2016 Present value of net program costs (in 2018 dollars) ($1,008)
Comparison costs $0 2016 Cost range (+ or -) 20 %
Per-participant cost estimates are based on weighted average program costs in the included studies. The included study delivered an exercise program with four home visiting hours, provided by a physical therapist. We include four hours of travel time and 0.75 hours of telephone follow-up, per participant. We include a $35 online training fee, three hours of provider time to complete the training, and assume that each trained provider serves 20 participants. We also include the cost of a single set of ankle cuff weights for each participant. The included study also delivered assessment and modifications of home hazards, provided by an occupational therapist. We assume home visits lasted one hour and required 30 minutes of travel time; and follow-up letters required 15 minutes time, on average. We include the cost of a two-day training, provider time spent in attendance, and trainer compensation. We also include the cost of home modifications (materials and labor) and assistive devices. When estimating provider costs, we apply the 2016 mean hourly wage estimate for Washington State reported by the Bureau of Labor Statistics (retrieved March 2018) for the appropriate provider; and increase wages by a factor of 1.441 to account for the cost of employee benefits. Information on the exercise program including provider type, transportation, and telephone follow up retrieved from Carande-Kulis, V., Stevens, J.A., Florence, C.S., Beattie, B.L., & Arias, I. (2015). A cost–benefit analysis of three older adult fall prevention interventions. Journal of Safety Research, 52, 65-70. Information on online training costs for the exercise program and ankle cuff weights provided by Carolyn Ham at the Washington State Department of Health, March 2018.
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.

The effect size for this outcome indicates an incidence rate ratio (IRR), not a standardized mean difference effect size. An IRR less than one indicates a lower rate of the outcome in the treatment group relative to the comparison group; an IRR greater than one indicates a higher rate of the outcome. The treatment n for this outcome represents person-years.

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 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
Falls 83 1 92 0.709 0.090 83 1.000 0.000 84 0.709 0.006

Citations Used in the Meta-Analysis

Campbell, A.J., Robertson, M.C., La Grow, S.J., Kerse, N.M., Sanderson, G.F., Jacobs, R.J., . . . Hale, L.A. (2005). Randomised controlled trial of prevention of falls in people aged ≥75 with severe visual impairment: the VIP trial. BMJ, 331(7520), 817.